I S S N 0 030-6096

Vol.

64

No.2

2018

PUBLISHED BYOSAKA CITY MEDICAL ASSOCIATIONOSAKA JAPANOsaka City Medical Journal
Vo l . 6 4 , N o . 2 ,December 2018

CONTENTS
page
Obsessions and Compulsions are Strongly Associated with Anxiety andDepressive Symptoms in Childhood and Adolescent Autism
Spectrum Disorder
YOSHIHIRO IWAKURA, DAI MIYAWAKI, HIROTO KUSAKA, AYAKO GOTO,NOBUYOSHI ASADA, ERIKA YANAGAWA, NAOMI ASADA, HIROKI TERAKAWA,
KAORU HIRAI, YUSUKE MIKI, and KOKI INOUE ･･････････････････････････････････････････････････ 75
Clinical Significance of Serum Duke Pancreatic Monoclonal Antigen
Type 2 for Diagnosing Biliary Tract Cancer
TOKUJI ITO, SHOGO TANAKA, SHIGEKAZU TAKEMURA, HIROJI SHINKAWA,
GENYA HAMANO, YUKIKO KURASHIMA, TAKANORI AOTA,
MASAKI KODA, TOSHIHIKO SHIBATA, and SHOJI KUBO ････････････････････････････････････････ 87Comparison of Long-term Outcomes between Thoracoscopic Esophagectomy
and Open Esophagectomy by Using the Propensity Score Matchingin 655 Patients with Esophageal Cancer
SHIGERU LEE, HARUSHI OSUGI, SATORU KISHIDA, YUSHI FUJIWARA,RYOYA HASHIBA, KEN GYOBU, SHOJI KUBO, and TOSHIHIKO SHIBATA ････････････････････ 99
Molecular Characterization of Familial Platelet Disorder with Propensity to
Develop Acute Myeloid Leukemia during the course of Leukemogenesis
MASAHARU NAKAYA, SADAO TOKIMASA, TAKASHI HAMAZAKI,
and HARUO SHINTAKU ･･････････････････････････････････････････････････････････････････････････････････ 113
Association between the Left Atrial Emptying Fraction and Silent Brain
Infarction in Patients with Paroxysmal Atrial Fibrillation
YU KAWAI, KENICHI SUGIOKA, SHINICHI IWATA, SHINICHI SAKAMOTO,SERA ISHIKAWA, MASAHIKO TAKAGI, YUKIO MIKI,
and MINORU YOSHIYAMA････････････････････････････････････････････････････････････････････････････････ 121
A Non-clinical Experimental Study of the Ligation Process with Knot Pushers
SHINSUKE NISHIMURA, MASAKI NISHIMURA, MITSUHARU HOSONO,TAKASHI MURAKAMI, YOSUKE TAKAHASHI, TAKAHIRO KITAGAWA,SEIICHI YASUKI, SHUNSUKE KITA, and TOSHIHIKO SHIBATA ････････････････････････････････ 131
Experimental Methanol Poisoning: Electron Microscopic Findings Obtained
between 2 and 14 Days after Administration
NOBUHIKO UEDA, and KUNIHIKO SHIRAKI ･･･････････････････････････････････････････････････････ 143

Osaka City Med. J. Vol. 64, 75-86, 2018

Obsessions and Compulsions are Strongly Associated with
Anxiety and Depressive Symptoms in Childhood andAdolescent Autism Spectrum Disorder
YOSHIHIRO IWAKURA1), DAI MIYAWAKI1), HIROTO KUSAKA1), AYAKO GOTO2),NOBUYOSHI ASADA1), ERIKA YANAGAWA1), NAOMI ASADA1), HIROKI TERAKAWA1),
KAORU HIRAI1), YUSUKE MIKI1), and KOKI INOUE1)
Department of Neuropsychiatry1), Osaka City University Graduate School of Medicine; andDepartment of Psychiatry2), Hannan Hospital

Abstract
Background
Autism spectrum disorder (ASD) is highly comorbid with obsessive-compulsive disorder (OCD) inchildren. Although the association between obsessions and compulsions (OC) and anxiety anddepressive symptoms has been acknowledged, some researchers maintain that in individuals with
ASD, OC are less related to anxiety symptoms. The purpose of this study was to examine correlations
between OC and other factors, including anxiety and depressive symptoms, in both ASD and non-ASD
groups.
Methods
We assessed a referral sample of 138 children (aged 9-15 years, 41.3% male). Multiple regression
analyses were performed separately for the ASD group and the non-ASD group to examine correlations
between OC (as measured by the Leyton Obsessional Inventory-Child Version) and age, sex,socioeconomic status, OCD, attention deficit hyperactivity disorder (ADHD), chronic tic disorder (CTD),
Tourette s syndrome (TS), scores on the State-Trait Anxiety Inventory for Children, and scores on the
Birleson Depression Self-Rating Scale for Children.
Results
Multiple regression analyses revealed that anxiety, depression, and OCD were significantly related
to OC in both the ASD and the non-ASD groups. ADHD, CTD, and TS were not related to OC.
Conclusions
Our findings suggest that OC are associated with anxiety and depressive symptoms, regardless ofthe presence of ASD.
Key Words: ‌Autism Spectrum Disorder; Obsessive-compulsive Disorder; Anxiety;Depression
Received September 5, 2017; accepted November 28, 2017.
Correspondence to: Yoshihiro Iwakura, MD.
Department of Neuropsychiatry, Osaka City University Graduate School of Medicine,
1-4-3 Asahimachi, Abeno-ku, Osaka 545-8585, Japan
Tel: +81-6-6645-3821; Fax: +81-6-6636-0439
E-mail: m2019955@med.osaka-cu.ac.jp- 75 -

Iwakura et al

Introduction
Autism spectrum disorder (ASD) is characterized by substantial impairment in social
communication and social interactions across multiple contexts and by restricted, repetitive patternsof behavior, interests, or activities1).
One research indicates that obsessions and compulsions (OC) are related to anxiety and depressive
symptoms and can lead to isolation and hopelessness2). In one 3-year follow-up study of children andadolescents, anxiety and depressive symptoms predicted the severity of OC after follow-up 3).
Although ASD is highly comorbid with obsessive-compulsive disorder (OCD) in children4,5), someresearchers have suggested that, unlike typical OCD patients, patients with ASD appear to enjoy
their OC and do not experience anxiety from them6). One review suggests that repetitive behavior inchildren with OCD is provoked by unwanted and bothersome thoughts that cause anxiety. In
contrast, repetitive behavior in children with ASD may not cause distress7). It has been proposed that
individuals with ASD tend not to subjectively evaluate OC as negative (as distressing, unwanted,
senseless, and ego-dystonic) and that they might have little awareness about their OC, partiallyowing to autistic individuals impaired ability to process and talk about their own internal state ofmind8). Furthermore, some studies have identified different types of OC between individuals with
ASD and those without ASD (non-ASD)9-14). OCD and neurodevelopmental disorders such as ASD,
attention deficit hyperactivity disorder (ADHD), and tic disorder (TD) may share underlying genetic
factors15). Therefore, OC in patients with ASD, ADHD, and TD could be attributed to underlying some
genetic factors rather than to anxiety and depressive symptoms.
However, many researchers have reported that autistic children and adolescents have a higher
prevalence of major depressive disorder and anxiety disorders, including OCD 16-21). Moreover, as ourclinical experience asserts, patients with OCD experience substantial anxiety and depressive
symptoms, regardless of the presence of ASD.
As above, difference of association between OC and anxiety and depressive symptoms in ASD and
non-ASD is controversial. Hence, we investigated the association between OC and anxiety anddepressive symptoms, taking into account factors that has associated with OCD in previous research,such as ADHD, chronic TD (CTD), and Tourette s syndrome (TS). Our aims were 1) to ascertain thatanxiety and depressive symptoms are positively correlated with OC regardless of the presence of
ASD, 2) to investigate the relationship between OC and other factors such as anxiety, depression,
ADHD, CTD, and TS.

Methods
Subjects
The study subjects were 164 elementary or junior high school students aged 9-15 years, who wereconsecutively referred to the children s psychiatry outpatient clinic of Osaka City University Hospital(Osaka, Japan) between January 2011 and December 2013. The subjects attended the clinic for atleast 3 months to be assessed by a trained multidisciplinary team, which included experienced childpsychiatrists, a psychologist, and a psychiatric social worker. Children with intellectual disability (n＝17) (IQ ＜70; Wechsler Intelligence Scale for Children-Third Edition; WISC-Ⅲ22)), children withacute psychotic states (n＝5), and children with severe neurological impairments or intractableepilepsy (n＝4) were excluded from this study. The WISC-Ⅲ was used to evaluate the intelligence of- 76 -

OC, Anxiety, and Depression in Child ASD

all subjects with ASD. For the non-ASD group, we obtained information about academic achievementand daily living skills from parents and teachers. All children with suspected intellectual disability(full IQ ＜70) were assessed using the WISC-Ⅲ.
The remaining 138 children were divided into two groups, 73 ASD children and 65 non-ASD
children. The diagnostic approach for ASD was based on the following three sources: 1) acomprehensive developmental history; 2) the clinician s interview with each child and their parents;and 3) direct observations of the children by two child psychiatrists. A diagnosis of ASD was madeusing the criteria in the American Psychiatric Association s Diagnostic and Statistical Manual of
Mental Disorders, Fifth Edition (DSM 5)1).
Procedure
We explained to participants the study purpose, procedures, potential risks, and alternatives toparticipation. We obtained written informed consent from all the children and their parents. The
study protocol was reviewed and approved by the Human Subject Review Committee of Osaka City
University. The approval number was 2382.
To diagnose comorbid psychiatric disorders, we used the Japanese version of the Schedule for
Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime version(K-SADS-PL-J). This is a semi-structured interview designed to assess current and past episodes ofpsychopathology in children and adolescents according to DSM-Ⅳ-TR criteria and is administeredthrough interviews with the child and a parent. This diagnostic tool is known for its scrupulousness
and high inter-rater reliability23). Finally, a multidisciplinary team meeting was held to elucidate thebest-estimate diagnosis for all participants once the interviews were completed.
Measures
Individuals who met the inclusion criteria were administered a series of clinical interview andself-report measures, which assessed OC, anxiety, and depressive symptoms. All measures were
presented in Japanese and had been validated in that language.
1. Leyton Obsessional Inventory-Child Version (LOI-CV)
The LOI-CV is a self-report 20-item questionnaire that measures the presence or absence (using
Yes/No responses) of several obsessive preoccupations and behaviors. Items with a positive response
are rated in terms of interference with personal functioning (range 0-3, no interference-interferes alot)24). Therefore, this instrument comprises two subscales: symptom presence (maximum score, 20)
and interference (maximum score, 60). The LOI-CV has been shown to be a valid screening
instrument for assessing OC in children and adolescents25). Internal reliability was high for the total
scale (α＝0.86)26). The LOI-CV showed acceptable internal consistency (α ＝0.79) in a study of 50
American children and adolescents with OCD27). We chose the LOI-CV from several published OC
measures because it has been widely used in Japan with community samples and was therefore
suitable for our subjects, almost all of whom had not been diagnosed with OCD.
2. The State-Trait Anxiety Inventory for Children (STAIC)The STAIC is designed to assess state and trait anxiety in children and contains two 20-item
scales. The child responds to each item by selecting one of several options. Each subscale score
ranges from 20 to 60. The STAIC-State scale asks children how they feel at a particular moment in
time; for example, I feel very nervous, nervous, not nervous . The STAIC-Trait scale asks how theygenerally feel; for example, I am shy hardly ever, sometimes, often28) .
3. The Birleson Depression Self-Rating Scale for Children (DSRS)- 77 -

Iwakura et al

The DSRS is a self-rating depression scale for children 29). Unlike the Children s Depression
Inventory (CDI), which was developed from the Beck Depression Inventory for adults, the DSRS wasdeveloped in clinical practice with children and makes fewer cognitive demands than the CDI30,31). It
contains 18 statements. The young person is asked to match these statements to his/her own
situation during the last week and to assign an intensity rating (applies most of the time ,sometimes , or never ). A score of 2, 1, or 0 is awarded depending on the direction of the statement.
Its usefulness in child populations has been demonstrated32,33).
Statistical analysis
All statistical analyses were performed using SPSS version 22.0 statistical software (SPSS Japan,
Inc., Tokyo, Japan). Descriptive data were presented as means, standard deviations, medians, andranges. Statistical significance was determined using the Mann-Whitney U test or Student s t-test,
as appropriate. The chi-square test was used to compare categorical variables. Spearman correlation
coefficients were used to test relationships between LOI-CV score, STAIC score, and DSRS score
separately for the ASD and the non-ASD groups. To identify the factors associated with LOI-CV
score, we conducted separate multiple regression analyses for the ASD group and non-ASD groupusing LOI-CV score as the dependent variable and age, sex, STAIC total score, DSRS total score,diagnosis of OCD, ADHD, CTD or TS, and parental absence as independent variables. P-values ＜0.05(two-sided probability) were deemed to indicate statistical significance.

Results
Table 1 shows the comparison of demographic characteristics of the participants in the ASD and
non-ASD groups. Of the 138 children (57 males and 81 females; mean age, 12.7 years), 73 werediagnosed with ASD. The ASD group had a mean age of 12.4 years and contained 40 males (54.8%).
The non-ASD group had a mean age of 13.1 years and contained 17 males (26.2%). The ASD groupcontained a significantly higher proportion of males than the non-ASD group (χ2＝11.63, df＝1, p＝0.001). There were no significant between-group differences in socioeconomic status (receiving public
assistance or not and having a parent absent or not), comorbid rate (for all comorbidities but anorexia
nervosa, enuresis, and ADHD), LOI-CV score, and DSRS score. The mean age (p＝0.015), thecomorbid rate of anorexia nervosa (p＝0.011), and STAIC scores were significantly lower in the ASD
group than in the non-ASD group. Proportion of males (p＝0.001) and comorbid rates of enuresis (p＝0.039) and ADHD (p＝0.024) were significantly higher in the ASD group than in the non-ASD group.
Table 2 shows between-group comparisons of LOI-CV scores for several variables. LOI-CV total
scores were significantly higher in females (p＝0.044), the parent-absent group (p＝0.004), and the
OCD group (p＝0.001).
Tables 3 shows correlations between continuous variables in the ASD group and non-ASD group(age, LOI-CV total score, STAIC total score, DSRS score). Both groups showed significant correlations
for the same variables (and no significant correlations between age and other variables). LOI-CV
score was significantly correlated with STAIC and DSRS scores. STAIC and DSRS scores were highlyand significantly correlated (r＝0.715 in both groups).
We had planned to use age, sex, STAIC score, DSRS score, diagnosis of OCD, ADHD, CTD or TS,
and parental absence as independent variables in the multiple regression analyses. However,
because of the high correlation between STAIC total scores and DSRS scores (r ＝0.715), we wereunable to use both these variables as independent variables in the multiple regression analyses owing- 78 -

- 79 -

13.2 (8.3-15.8)(41.3)(5.1)(29.0)(17.4)(6.5)(11.6)
(2.9)
(0.7)
(5.8)
(5.1)
(22.5)(9.4)(18.1)(11.6)
(0.7)
(3.6)
(0.0)
(21.0)(17.4)(19.6)(14.5)(13.0)(9.4)(3.6)
16 (0-64)
76 (45-67)
34 (20-40)
42 (22-38)
15 (4-28)

12.7 (1.8)
57
7
40
24
9
16
4
1
8
7
31
13
25
16
1
5
0
29
24
27
20
18
13
5
18.8 (13.6)
77.7 (17.8)
35.9 (11.5)
41.9 (9.1)
15.4 (6.2)

All(n＝138)74.0 (16.6)
33.3 (10.7)
40.7 (8.9)
14.6 (5.6)

18.7 (12.6)

13
3
5
2
0
2
5
17
7
14
12
0
5
0
9
18
18
9
13
10
3

3
20

12.4 (1.8)
40

81.9 (18.2)
38.8 (11.7)
43.12 (11.7)
16.4 (6.8)

18.9 (14.7)

16 (0-50)
71 (45-112)
30 (20-56)
40 (22-60)
14 (4-29)

11
6
11
2
1
6
2
14
6
11
4
1
0
0
20
6
9
11
5
3
2

4
20

13.1 (1.8)
17

83 (50-111)
42 (20-60)
43 (24-57)
17 (5-33)

15 (0.0-64.0)(16.9)(9.2)(16.9)
(3.1)
(1.5)
(9.2)
(3.1)
(21.5)(9.2)(16.9)
(6.2)
(1.5)
(0.0)
(0.0)
(30.8)(9.2)(13.8)(16.9)
(7.7)
(4.6)
(3.1)

(6.2)
(30.8)

13.3 (9.2-15.8)(26.2)

Non-ASD group(n＝65)(17.8)
(4.1)
(6.8)
(2.7)
(0.0)
(2.7)
(6.8)
(23.3)(9.6)(19.2)(16.4)
(0.0)
(6.8)
(0.0)
(12.3)(24.7)(24.7)(12.3)(17.8)(13.7)(4.1)(4.1)(27.4)

12.7 (8.3-15.8)(54.8)ASD group(n＝73)＊

1799.5 b
1736 b1985 b
1.782 a2315 b

＊7.044 c5.696 c2.554 c0.586 c3.102 c3.325 c0.105 c

0.014
＊
0.006
0.098
0.077

＊

0.808

0.011
＊
0.024
0.134
0.476
0.127
0.084
1.000

1.000
0.192
0.108
0.645
0.471
0.148
0.447
0.841
1.000
0.826
0.068
0.471
＊
0.039

0.707
0.709

0.015
＊
0.001

p

0.019 c1.479 c3.404 c0.014 c1.131 c2.653 c1.016 c0.06 c0.005 c0.118 c3.548 c1.131 c4.619 c0.298 c0.19 c2058 b
11.634 c

χ2/t/U

Notes: Values are expressed as mean (SD) and median (range) or n (%). a t-test. b Mann-Whitney U-test. c Chi-square analysis. ＊ p＜0.05.
Abbreviations: K-SADS-PL-J, The Japanese version of the Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime version; ASD, autism
spectrum disorder; ADHD, attention deficit hyperactivity disorder; LOI-CV, Leyton Obsessional Inventory-Child Version; STAIC, State-Trait Anxiety Inventory for Children; and DSRS,
Birleson Depression Self-Rating Scale for Children.

Demographic variables
Age
Male gender, n (%)
Socioeconomic status
Receipt of public assistance, n (%)
Absence of a parent, n (%)
K-SADS-PL-J diagnoses
Major depressive disorder
Dysthymia
Adjustment disorder
Bipolar disorder
Psychotic disorder not otherwise specified
Panic disorder
Separation anxiety disorderSocial phobia
Specific phobia
Generalized anxiety disorder
Obsessive-compulsive disorder
Posttraumatic stress disorder
Enuresis
Encopresis
Anorexia nervosa
ADHD
Oppositional defiant disorder
Conduct disorder
Chronic tic disorder or Tourette s syndrome
Chronic motor or vocal tic disorder
Tourette s syndrome
Self-report scores
LOI-CV total scores
STAIC
Total scores
State scores
Trait scores
DSRS total scores

Table 1. Participant characteristics

OC, Anxiety, and Depression in Child ASD

Iwakura et al
Table 2. Comparison of Leyton Obsessional Inventory-Child Version (LOI-CV) scores
LOI-CV total scores
Mean (SD)Median (range)

n＝57
n＝81

16.2 (12.7)

14 (0-50)

20.6 (14.0)

17 (2-64)n＝721.0 (14.7)

15 (5-46)

n＝131

18.7 (13.5)

16 (0-64)n＝40

24.0 (14.5)

17.5 (4-58)

( −)
n＝91
Obsessive-compulsive disorder
( ＋)
n＝16

16.6 (12.6)

14.5 (0-64)

30.0 (15.0)

26 (9-58)

( −)
ASD
( ＋)

n＝122

17.3 (12.7)

15 (0-64)

n＝73

18.7 (12.6)

16 (0-50)

( −)

n＝65

18.9 (14.7)

15 (0-64)

ADHD
( ＋)

n＝24

19.8 (13.2)

17 (3-46)

( −)

n＝114

18.6 (13.7)

15 (0-64)

Sex
Male
FemalePublic assistance
( ＋)
( −)
Absence of a parent( ＋)

Chronic tic disorder/Tourette s syndrome
( ＋)
n＝18
(−)

n＝120

17.6 (11.7)

16 (1-46)

18.9 (13.8)

16 (0-64)

Up1844.000

0.044

408.500

0.636

1344.000

0.004＊

483.000

0.001＊

2315.000

0.808

1271.000

0.589

1059.000

0.896＊

Notes: Mann-Whitney U test was used because the LOI-CV scores were not normally distributed. Values are
expressed as mean (SD), median (range) or n (%).
Abbreviations: ASD, autism spectrum disorder; ADHD, attention deficit hyperactivity disorder; and LOI-CV, Leyton
Obsessional Inventory-Child Version.

Table 3. Spearman’s correlations between age and LOI-CV, STAIC, and DSRS scores
Age

ASD group

non-ASD group

LOI-CV total score

Age
LOI-CV total score
STAIC total score−0.034

0.214

0.589

DSRS total score

0.137

0.557

Age
LOI-CV total score−0.032STAIC total score

0.201

0.562

DSRS total score

0.125

0.594

STAIC total score

DSRS-C total score

＊＊
＊＊

0.715

＊＊

＊＊
＊＊

0.715

＊＊

＊＊

Notes: p＜0.01.
Abbreviations: LOI-CV, Leyton Obsessional Inventory-Child Version; STAIC, State-Trait Anxiety Inventory forChildren; DSRS, Birleson Depression Self-Rating Scale for Children; and ASD, Autism Spectrum Disorder.

to multicollinearity. Therefore, we performed (for both the ASD group and the non-ASD group) two
multiple regression analyses with STAIC or DSRS score as an independent variable. Table 4 shows
the results of multiple regression analyses For the ASD group. In the analysis 1 (including STAIC
score as independent variable), the independent variables that predicted LOI-CV total score were

- 80 -

OC, Anxiety, and Depression in Child ASD
Table 4. ‌Multiple regression results showing predictors of LOI-CV total scores in the autism spectrum
disorder group

analysis 1

B

SE

Constant

4.326

11.6840.712−19.008

27.661

Sex

1.461

2.633

0.058

0.581

−3.797

6.719

1.203

Age

−0.240p-value

95% CI of B

VIF

−0.033−2.033

1.554

1.717

−4.407

6.985

1.134

1.243

16.332

1.374

Absence of a parent

1.289

0.898
2.852

0.046

0.790
0.653

OCD

8.788

3.778

0.261

0.023

ADHD

5.642

3.530

0.195

0.115

−1.40812.692

1.622−1.484

3.559
0.078

−0.0450.678−8.592

5.625

1.300

0.533

＜0.001

0.247

0.560

1.171

CTD or TS

analysis 2βVariable

STAIC

0.403

Constant−2.476

＊

＊

0.064

0.834
0.550

21.0401.461

11.7752.669−25.992

Sex−3.727

6.934

1.202

Age

0.107

0.894

0.015

0.905

−1.679Absence of a parent
OCD

0.218
10.287

2.900
3.782

0.008
0.305

0.940
＊
0.008

−5.575

1.893
6.010

1.655
1.140

2.374

17.840

1.338

ADHD

3.271

3.668

0.113

0.376

−4.05410.5961.702−1.0873.603−0.033−8.282

1.149

0.235

0.509

0.764
＊
＜0.001

6.109
1.627

1.294
1.148

CTD or TS
DSRS

0.680

Notes: R2＝0.406; Durbin-Watson＝2.071 in analysis 1; and R2＝0.389; Durbin-Watson＝1.958 in analysis 2.
Abbreviations: B, unstandardized coefficient; SE, standard error; β, standardized partial regression coefficient; VIF,
variance inﬂation factor; LOI-CV, Leyton Obsessional Inventory-Child Version; ASD, autism spectrum disorder; OCD,
obsessive-compulsive disorder; ADHD, attention deficit hyperactivity disorder; CTD, chronic tic disorder; TS, Tourette s
syndrome; STAIC State-Trait Anxiety Inventory for Children; and DSRS, Birleson Depression Self-Rating Scale forChildren.

STAIC score (β＝0.533; p＜0.001) and OCD (β＝0.261; p＝0.023); in the analysis 2 (including DSRS
score as independent variable), the predictors were DSRS score (β＝0.509; p＜0.001) and OCD (β＝0.305; p＝0.008). Table 5 shows the result of multiple regression analyses for the non-ASD group. In
the analysis 3 (including STAIC as independent variable), the independent variables that predicted
LOI-CV total score were STAIC score (β＝0.435; p＜0.001), OCD (β＝0.259; p＝0.019), and parental
absence (β＝0.274; p＝0.014); in the analysis 4 (including DSRS score as independent variable), thepredictors were DSRS score (β＝0.519; p＜0.001) and OCD (β＝0.261; p＝0.012).

Discussion
To the best of our knowledge, no studies have compared ASD and non-ASD groups on theassociation between OC and anxiety and depressive symptoms and simultaneously considered factors
possibly related to OC, such as age, sex, the diagnosis of ADHD, CTD, TS, and parental absence. In
the present study, we aimed to 1) ascertain whether anxiety and depressive symptoms were positively
correlated with OC regardless of the presence of ASD, 2) to investigate the relationship between OC
and other possibly related factors. The results suggested that OC is related to the presence of OCD
and anxiety and depressive symptoms, regardless of the presence of ASD. We expected parental
absence to be a confounding factor in the non-ASD group because of its correlation with DSRS scores.
In fact, in the non-ASD sample, the DSRS score mean in the parental absence group (mean＝19.9; SD＝6.7) was significantly higher than in the other group (mean＝14.9; SD＝6.3) (p＝0.005).

Taking into account the relationship between OC severity and anxiety and depressive symptoms,- 81 -

Iwakura et al
Table 5. Multiple‌
regression results showing predictors of LOI-CV total scores in the non-autism spectrum
disorder group
Variableanalysis 3

BSEConstant−0.96312.166Sex−1.660

Age

0.222

3.969
0.908

p-value
0.937−25.325

23.398−0.050

0.677
0.808

−9.608

6.288

1.412

−1.596

2.041

1.223

1.799

15.476

1.153

2.623

28.773

1.143−10.93111.4551.215−14.178

10.734

1.275

0.163

0.538

1.330

0.027

95% CI of B

VIF

Absence of a parent

8.637

3.415

0.274

0.014

＊

OCD

15.698

6.530

0.259

0.019

＊

ADHD

0.262

5.590

0.005

0.963

−1.722

6.220
0.094

−0.032

0.783

0.435

＜0.001

0.848
0.841

−25.225

20.8020.022−6.544

8.013

1.328

0.956
0.069
＊
0.012

−1.777−0.491

1.681
12.877

1.239
1.235

3.609

28.004

1.115−13.753

7.544

1.233

−10.83912.987

1.308

0.652

1.602

1.313

CTD or TS

analysis 4

β

STAIC

0.350

Constant−2.212

Sex

0.734

Age

−0.048Absence of a parent
OCD

6.193
15.807ADHD−3.104

11.493
3.635
0.863
3.338
6.091

−0.006−0.062

0.020

0.562
0.857

0.519

＜0.001CTD or TS

1.074

5.318
5.949

DSRS

1.127

0.237

0.196
0.261

＊

＊

Notes: R2＝0.420; Durbin-Watson＝2.122 in analysis 3; and R2＝0.483; Durbin-Watson＝2.193 in analysis 4.
Abbreviations: B, unstandardized coefficient; SE, standard error; β, standardized partial regression coefficient; VIF,
variance inﬂation factor; LOI-CV, Leyton Obsessional Inventory-Child Version; ASD, autism spectrum disorder; OCD,
obsessive-compulsive disorder; ADHD, attention deficit hyperactivity disorder; CTD, chronic tic disorder; TS, Tourette s
syndrome; STAIC State-Trait Anxiety Inventory for Children; and DSRS, Birleson Depression Self-Rating Scale forChildren.

these results are in accord with findings from several previous studies 2,3). Mack et al comparedclinical characteristics and symptom severity of children with OCD plus ASD with those of children
with OCD plus TS or OCD alone, using the Children s Yale-Brown Obsessive Compulsive Scale (CYBOCS), which is considered the gold standard measure of OC severity in youth34,35). They found thatchildren in all groups experienced similar levels of impairment12). Mito et al compared the severity
and prevalence of OC, anxiety, and depression in an ASD group and a non-ASD group of OCD
patients. They reported that elevated ASD scores had little impact on severity and prevalence ofOC36). However, they defined ASD simply as high autism quotient scores, which is an insufficientmeasure. These previous studies are limited because they focused only on patients diagnosed with
OCD. Substantial numbers of adolescents suffer from subclinical OCD, which is characterized by OC
that are not severe enough to meet the full OCD criteria and has a prevalence ranging from 2.7% to19%37,38).
Our results are inconsistent with findings from one previous study. Ruta et al examined OC
features and symptom severity in children and adolescents with Asperger s syndrome using the CYBOCS. The Asperger s syndrome group showed greater OC severity than the control group13).
However, this study used a univariate analysis and did not consider possible confounding factors suchas anxiety and depressive symptoms.
Although many studies have examined the association between OC and ASD from various
perspectives, they suffer from methodological problems. We included subjects regardless of OCD
diagnosis and used a range of information to more accurately diagnose ASD. We also investigated the- 82 -

OC, Anxiety, and Depression in Child ASD

association between OC and factors thought to be related to OCD.
Many researchers have pointed that ASD, ADHD, and TS are highly comorbid with OCD inchildren4,5,39,40). However, some researchers have suggested that individuals with ASD appear to enjoy
their OC and do not experience anxiety from them4,5). Moreover, individuals with ASD and otherneurodevelopmental disorders may show a particular type of OC.
The concept of obsessive-compulsive spectrum disorders (OCSD) was proposed in response toobservations of disparate disorders marked by obsessive thinking and/or compulsive behavior,including ASD and TS41,42). Hollander et al subdivided OCSD into three clusters: 1) body image/bodysensitization/body weight concern disorders; 2) impulse control disorders; and 3) neurologicaldisorders with repetitive behaviors. ASD and TD were included in the last category. They suggested
that, for disorders in the last cluster, OC are based on underlying neurological dysfunction rather
than on the anxiety typically found in OCD 41).
Ortiz et al investigated comorbidities and clinical characteristics of children with OCD and defined
two subtypes of OCD: one subtype is characterized by childhood onset, a predominance of males, highfamilial aggregation, and comorbid neurodevelopmental disorders such as ADHD, TS, and CTD; thesecond subtype is phenotypically more related to anxiety and depressive disorders, is more common
in females, and has a later onset during adolescence 43). Other researchers have suggested thatneurodevelopmental disorders such as ASD, ADHD, and TD share underlying genetic factors thatconverge at the level of cortico-striatal-thalamocortical circuits15).
These previous research findings suggest that OC may be related to neurodevelopmental disorders
such as ASD, ADHD, CTD, and TS, regardless of anxiety and depressive symptoms, and may be lessrelated to anxiety and depressive symptoms in ASD. However, we found that OC was significantly
associated with anxiety and depressive symptoms in both the ASD and non-ASD groups. We foundno relation between OC and ADHD, CTD, and TS.
Many studies have reported that OC are distressing, impair function, and are related to anxiety
and depressive symptoms2,3,44-49). Therefore, to prevent exacerbation of OCD symptoms, potential
treatment of patients with OCD should focus on treatment of anxiety and depressive symptoms3,50).
Hence, although recent research has focused on OCD heterogeneity, we should consider comorbid
anxiety and depressive symptoms regardless of comorbid ASD and other neurodevelopmental
disorders when we meet patients who present with OC.
Limitations
As our study samples were children and adolescents, we cannot generalize the findings to adult
populations. Because we focused on patients subjective symptoms in this study, we only used selfreport measures. However, because of the difficulties that individuals with ASD can experience indescribing their internal states, it is not known whether self-report measures are effective in
identifying OC, anxiety, and depression in this group. Mazefsky et al reported the poor performanceof a self-report measure to identify OCD in children with ASD51). However, other studies have shownstrong correlations between parent and child self-reports of anxiety and depression in ASD52-54).
We did not consider whether the participants had been received pharmacotherapy or not in thisstudy. Because pharmacotherapy possibly alleviate OC, further study considering the history ofpharmacotherapy are needed.
In this study, we examined OC in terms of symptom severity rather than clinical diagnoses andtherefore did not investigate comprehensive OCD psychopathology. However, as mentioned above,- 83 -

Iwakura et alprevious studies indicate that many adolescents suffer from subclinical OCD37,38). In one 2-year followup study, adolescents with subclinical OCD and those scoring highly on the LOI-CV were more likely
to fulfill clinical OCD criteria after follow-up55). Moreover, OC in all age groups, particularly younger
sufferers, is under-recognized because individuals tend to be secretive about their symptoms35,56).
These characteristics of OC lead to delays in detection, diagnosis, and treatment. It is therefore
important to investigate OC in children and adolescents regardless of whether they have OCD toprevent pathogenesis or exacerbation of OCD.
Conflicts of interest
The authors declare that they have no conﬂicts of interest.
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- 86 -

Osaka City Med. J. Vol. 64, 87-97, 2018

Clinical Significance of Serum Duke Pancreatic Monoclonal Antigen
Type 2 for Diagnosing Biliary Tract Cancer
TOKUJI ITO, SHOGO TANAKA, SHIGEKAZU TAKEMURA, HIROJI SHINKAWA, GENYA HAMANO,YUKIKO KURASHIMA, TAKANORI AOTA, MASAKI KODA, TOSHIHIKO SHIBATA, and SHOJI KUBO
Department of Hepato-Biliary-Pancreatic Surgery,
Osaka City University Graduate School of Medicine

Abstract
BackgroundTo evaluate the usefulness of serum Duke pancreatic monoclonal antigen type 2 (DUPAN-2)
concentrations in patients with biliary tract cancer (BTC).
Methods
The serum concentrations of DUPAN-2, carbohydrate antigen 19-9 (CA19-9), and carcinoembryonicantigen (CEA) were prospectively measured in 90 patients with BTC and 47 patients with benign
biliary tract disease before surgery and in 54 patients with BTC after surgery. The usefulness of eachtumor marker was investigated.
Results
The receiver operating characteristic (ROC) curve for the serum concentration of DUPAN-2 inpredicting BTC had the greatest area under the curve (AUC, 0.821; vs CA19-9, 0.788 and CEA, 0.698).
The optimal cutoff value for DUPAN-2 was determined from the ROC curve (30 IU/mL). The sensitivity
and specificity of DUPAN-2 were 74.4% and 83.0%, respectively. The diagnostic accuracy (positive
predictive value ＋ negative predictive value) of DUPAN-2 was 77.4% (CA19-9, 67.2%; CEA, 46.2%).
Moreover, for patients with stage 0-I BTC, DUPAN-2 showed the highest sensitivity (60.9% vs CA199, 34.8% and CEA, 17.4%). Among the 36 patients with preoperative serum DUPAN-2 ≧30 IU/mL,
the value decreased postoperatively in 34 patients (94%).
Conclusions
The measurement of the serum concentration of DUPAN-2 was useful for diagnosing BTC, even at
an early stage.
Key Words: ‌Duke pancreatic monoclonal antigen type 2; Biliary tract cancer;
Sensitivity and specificity; Tumor

Received September 5, 2017; accepted November 28, 2017.
Correspondence to: Shoji Kubo, MD, PhD.
Department of Hepato-Biliary-Pancreatic Surgery, Osaka City University Graduate School of Medicine,
1-4-3 Asahimachi, Abeno-ku, Osaka 545-8585, Japan
Tel: +81-6-6645-3841; Fax: +81-6-6646-6057
E-mail: m7696493@msic.med.osaka-cu.ac.jp- 87 -

Ito et al

Introduction
Biliary tract cancers (BTCs) represent the second most common type of hepatobiliary cancer1) andare typically classified as intrahepatic cholangiocarcinoma (ICC), perihilar/hilar cholangiocarcinoma(CCs; pCC), distal CC (dCC), and gallbladder carcinoma (GBC)2). The clinical course of BTC is poor
because of its silent clinical characteristics, the difficulties associated with diagnosing the diseaseat an early stage, and the limited available therapeutic options3). The incidence and mortality
associated with BTC have continued to increase worldwide4). The clinical presentation and use ofimaging techniques cannot completely distinguish BTC from benign biliary tract diseases (BBTD)5-8).
Moreover, laboratory assessments for BTC are not sufficiently sensitive or specific. Currently, theserum carbohydrate antigen 19-9 (CA19-9) concentration is routinely determined in patients withbiliary tract disease. However, the sensitivity and specificity of CA19-9 in diagnosing BTC vary
widely9-12), and elevated serum CA19-9 concentrations have been observed in some patients with
BBTD13,14). Other serum markers, such as carcinoembryonic antigen (CEA), have been used to detect
BTC, but the use of these markers in screening has been reported to be limited because of their low
specificity and sensitivity11,15,16). The Japanese practice guidelines for managing BTC state that notumor markers specific to BTC are available and that the diagnostic ability can be improved with a
combination of tumor markers (e.g., CA19-9 and CEA)17). Unfortunately, new useful biomarkers forthe diagnosis of BTC have yet to be developed18). Thus, the use of other serum tumor markers would
be beneficial for diagnosing BTC.
Duke pancreatic monoclonal antigen type 2 (DUPAN-2) was discovered in 1982 as a highmolecular weight glycoprotein defined by a murine monoclonal antibody against a pancreatic
ductal adenocarcinoma cell line19). DUPAN-2 has been established as an important serum tumor
marker for pancreatic cancer 20) and has been reported to be a prognostic factor for pancreaticcancer after surgery21,22). Immunohistochemical studies have shown that DUPAN-2 is distributed invarious adenocarcinomas23). Approximately 40% of BTC patients reportedly show serum DUPAN-2
concentrations of ＞400 IU/mL20,24). However, a cutoff value of ＞400 IU/mL was determined for
diagnosing pancreatic cancer20,24). Thus, the optimal cutoff value and accuracy of serum DUPAN-2 as
a tumor marker for diagnosing BTC has not been investigated.
In the present study, we collected clinical data, including the serum concentrations of DUPAN-2,
CA19-9, and CEA, from patients with BTC and BBTD and investigated the clinical significance of
DUPAN-2 as a tumor marker for BTC.

Methods
Patients
This study enrolled 90 patients with BTC (BTC group) and 49 with BBTD (control group) treatedsurgically at the Department of Hepato-Biliary-Pancreatic Surgery, Osaka City University Hospital,
between January 2013 and April 2017. The laboratory test results, including serum concentrationsof DUPAN-2, CA19-9, and CEA were measured for the diagnosis, were prospectively collected. Amongthe 90 patients, the DUPAN-2 concentrations of 54 were able to be measured routinely (3-6 months)
after surgery, and the concentrations of the remaining 36 could not be measured due to the short timesince surgery (＜3 months) in 2 patients and the requirement for follow-up at referral hospitals for 34
patients (26 of whom died). In cases of preoperative biliary decompression, the laboratory test results
including the tumor markers after decompression were used.

- 88 -DUPAN-2 in Biliary Tract Cancer

Clinical information was obtained by a thorough review of the patients medical histories. The
diagnosis of BTC was pathologically made for all 90 patients. BTC was classified as ICC (n＝29), pCC(n＝22), dCC (n＝21), and GBC (n＝18). The control group included patients with acute or chroniccholecystitis (n＝33), gallbladder polyps (n＝4), hepatolithiasis (n＝5), choledocholithiasis (n＝2), andcongenital biliary disease (n＝3).
This study was approved by the Institutional Review Board of our institution (approval number,
3166; Osaka City University) and was conducted in accordance with the mandates of the 2008
Declaration of Helsinki.
Clinical data
Baseline preoperative clinical data that were collected included age; sex; number and proportionof patients with jaundice when tumor marker concentrations were measured; number and proportionof patients who had undergone preoperative biliary decompression; serum concentrations of total
bilirubin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), γ-glutamyltranspeptidase(γ-GTP), and alkaline phosphatase (ALP); primary tumor stage according to the International Union
Against Cancer (UICC)/American Joint Committee on Cancer staging system25); histological findings(number and proportion of patients with lymph node metastasis, vascular invasion, and perineuralinvasion); and serum concentrations of DUPAN-2, CA19-9, and CEA.
Measurement of DUPAN-2, CEA, and CA19-9 concentrations
DUPAN-2 concentrations were measured by using enzyme immunoassay. For comparison, CEA
and CA19-9 concentrations were measured by electrochemiluminescence immunoassay. DUPAN-2
serum concentrations of ＞1600 IU/mL were recorded as 1600 IU/mL and concentrations of ＜25 IU/
mL were recorded as 25 IU/mL. CA19-9 serum concentrations of ＜2 IU/mL were recorded as 2 IU/
mL, and CEA serum concentrations of ＜0.5 ng/mL were recorded as 0.5 ng/mL.
Statistical analysis
Pearson s correlation coefficient was used to investigate the correlations between the concentrationsof DUPAN-2 and the concentrations of CA19-9, CEA, biliary enzymes, and transferase and between
the concentrations of CA19-9 and CEA; values of −0.4 to 0.4 were considered to reﬂect the absence ofcorrelation. To compare the abilities of tumor markers to distinguish patients with BTC from thosewith BBTD, receiver operating characteristic (ROC) curves were constructed that correlated with thetrue- and false-positive rates [sensitivity and (1-specificity)]. In addition, the area under the ROC
curve (AUC) and 95% confidence interval (CI) were calculated for each marker. The optimal cutoff
values of serum DUPAN-2 were determined by Youden s index.
Continuous variables were expressed as the median (25th and 75th percentiles). Inter-groupdifferences were assessed by performing the Mann-Whitney U test. Differences in categoricalvariables were assessed by performing the chi-squared test or Fisher s exact test. p-values of ＜0.05
were considered to indicate statistical significance. All statistical analyses were performed by using
SPSS® v.22.0 (IBM-SPSS, Inc., Chicago, IL, USA).

Results
Tumor markers
Significant differences in the preoperative serum concentration of DUPAN-2 [median (interquartile
range)] were observed between patients with BTC [105 IU/mL (27-485 IU/mL)] and those with benign
biliary disease [25 IU/mL (25-26 IU/mL), p＜0.001, Fig. 1]. The serum concentrations of CA19-9 and- 89 -

Ito et al

Figure. 1 The distribution of individual serum Duke pancreatic monoclonal antigen type 2 (DUPAN-2) concentrations
in patients with biliary tract cancer (BTC) and benign biliary tract disease (BBTD). Data are presented as the upperand lower quartile and range (box) and the median value (horizontal line).

Table 1. ‌Comparison of the clinicopathological characteristics between patients with biliary tract cancer
and patients with benign biliary tract disease
BTC group(n＝90)

Control group(n＝47)

105 (27, 485)
45 (11, 363)
3.1 (2.1, 4.5)

25 (25, 26)
6 (3, 11)2 (1.3, 2.9)

＜0.00168 (63, 74)
53/37

62 (51, 70)
15/32

0.014
0.004

29 (32)22 (25)21 (23)18 (20)37 (41)3 (6)＜0.0010.6 (0.5, 0.9)
28 (22, 46))
27 (17, 54)
125 (40, 276)351 (260, 706)

0.5 (0.4, 0.7)
22 (17, 27)
16 (14, 27)
31 (19, 53)
202 (177, 287)

0.012
0.001
0.002
＜0.001＜0.001＊

Tumor markers
DUPAN-2 (IU/mL)
CA19-9 (IU/mL)
CEA (ng/mL)
Age (years old)
Sex (male/female)
Diagnosis of biliary tract cancer, n (%)
Intrahepatic cholangiocarcinoma
Perihilar/hilar cholangiocarcinoma
Distal cholangiocarcinoma
Gallbladder cancer
Preoperative biliary decompression, n (%)
Laboratory data
Total bilirubin (mg/dL)
Aspartate aminotransferase (IU/L)
Alanine aminotransferase (IU/L)
g-glutamyltranspeptidase (IU/L)
Alkaline phosphatase (IU/L)UICC stage [n (%)]
0-Ⅰ
Ⅱ
Ⅲ
Ⅳ

p value＜0.001＜0.001

23 (26)32 (36)14 (16)20 (22)

Continuous values are expressed as the median (25th and 75th percentiles). ＊ One patient who underwent exploratory
laparotomy was excluded. BTC, biliary tract cancer; DUPAN-2, Duke pancreatic monoclonal antigen type 2; CA19-9,
carbohydrate antigen 19-9; CEA, carcinoembryonic antigen; and UICC, International Union Against Cancer.

- 90 -DUPAN-2 in Biliary Tract Cancer

CEA in the patients in the BTC group were also significantly higher than those in the patients in thecontrol group (Table 1).
No correlations were observed between the concentration of DUPAN-2 and those of CA19-9, CEA,
AST, ALT, γ-GTP, or ALP (coefficients of correlation: CA19-9, 0.022; CEA, 0.039; total bilirubin, −0.013;
AST, −0.055; ALT, −0.051; γ-GTP, −0.023; and ALP, −0.022). he coefficient of correlation between
CA19-9 and CEA was 0.192.
Clinical characteristics of patients with BTC in comparison to patients with BBTD
An elderly male predominance was observed in patients in the BTC group (Table 1). Preoperative
biliary decompression for obstructive jaundice had been performed in 37 (41%) of the 90 patientsin the BTC group and 3 (6%) of the 47 patients in the control group (p ＜0.001). The serum
concentrations of total bilirubin, AST, ALT, γ-GTP, and ALP in the patients in the BTC group werehigher than those in the patients in the control group. The tumor stages of the patients in the BTC
group (according to the UICC staging system) were stage 0 (n＝1), stage Ⅰ (n＝23), stage Ⅱ (n＝32),
stage Ⅲ (n＝14), and stage Ⅳ (n＝20).
ROC curve analysis
ROC curves were constructed to compare the ability of the 3 markers to differentiate between
patients with BTC and those with BBTD. The curves that distinguished BTC from benign biliary
disease are shown in Figure 2. The ROC curve for the prediction of BTC showed a greater AUC for
the serum concentration of DUPAN-2 (0.821, 95% CI: 0.752-0.890) than for the serum concentrationsof CA19-9 (0.788, 95% CI: 0.711-0.865) and CEA (0.698, 95% CI: 0.607-0.788). The optimal cutoff
value of the serum DUPAN-2 concentration for distinguishing BTC from BBTD was 30 IU/mL.

Figure. 2 The receiver operating characteristic (ROC) curves of Duke pancreatic monoclonal antigen type 2(DUPAN-2), carbohydrate antigen 19-9 (CA19-9), and carcinoembryonic antigen (CEA) concentrations in patients withbiliary tract cancer (BTC) were compared with those in patients with benign biliary tract disease (BBTD). Optimal
cutoff values of serum DUPAN-2 were determined by Youden index (circle).

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Ito et al
Table 2. Usefulness of DUPAN-2, CA19-9, and CEA for diagnosing biliary tract cancer
Combination of tumor markers
DUPAN-2 DUPAN-2
CA19-9(＞400)(≧30)
Sensitivity%
28.9
Number26/90
Specificity%
100
Number47/47
Positive predictive value%
100
Number
26/26
Negative predictive value%
42.3
Number
47/111
Diagnostic accuracy%
53.3
Number73/137

CEA

CA19-9＋ DUPAN-2＋ DUPAN-2＋ DUPAN-2＋
CEA
CA19-9
CEA
CA19-9＋CEA

74.4
67/90

54.4
49/90

22.2
20/90

58.9
53/90

82.2
74/90

76.7
69/90

83.3
75/90

83
39/47

91.5
43/47

93.6
44/47

87.2
41/47

76.6
36/47

78.7
37/47

72.3
34/47

89.3
67/75

92.5
49/53

87
20/23

89.8
53/59

87.1
74/85

87.3
69/79

85.2
75/88

62.9
39/62

51.2
43/84

38.6
44/114

52.6
41/78

69.2
36/52

63.8
37/58

69.4
34/49

77.4
106/13767.2
46.7
92/137 64/137

68.6
94/13780.3
110/13777.4
106/137

79.6
109/137

DUPAN-2, Duke pancreatic monoclonal antigen type 2; CA19-9, carbohydrate antigen 19-9; and CEA carcinoembryonicantigen.

Accuracy of DUPAN-2, CA19-9, and CEA as tumor markers
The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy ofthe various tumor makers in the diagnosis of BTC are listed in Table 2. The sensitivity, specificity,
positive predictive value, negative predictive value, and accuracy of a DUPAN-2 cutoff value of ＞400
IU/mL for diagnosing BTC were 28.9% (26/90), 100% (47/47), 100% (26/26), 42.3% (47/111), and 53.3%(73/137), respectively. Among the 3 tumor markers, a DUPAN-2 cutoff value of ≧30 IU/mL showed
the highest sensitivity (74.4%), negative predictive value (62.9%), and diagnostic accuracy (77.4%)
for diagnosing BTC. The specificity and positive predictive values of all 3 markers exceeded 80% and85%, respectively. Moreover, the sensitivity and diagnostic accuracy of DUPAN-2 alone were superior
to those of CA19-9 ＋CEA. The combination of DUPAN-2 ＋CA19-9 and CA19-9 ＋CEA increased
the sensitivity but decreased the specificity and was not associated with a remarkable increase inaccuracy relative to that of DUPAN-2 alone. In the BTC group, 22 (59.5%) of the 37 patients who
were found to be negative for CA19-9＋CEA were positive for DUPAN-2, whereas 8 (34.8%) of the 23
patients who were negative for DUPAN-2 were positive for CA19-9＋CEA. The sensitivity, specificity,
positive predictive value, negative predictive value, and accuracy of the various tumor markers in thepatients with UICC stage 0-Ⅰ and stage Ⅱ-Ⅳ are listed in Table 3. In patients with stage 0-Ⅰ BTC,DUPAN-2 showed the highest sensitivity and diagnostic accuracy (60.9% and 75.7%, respectively)
among the 3 markers (CA19-9, 34.8% and 72.9%; CEA, 17.4% and 68.6%; and CA19-9＋CEA, 43.5%
and 72.9%, respectively). Moreover, in patients with stage Ⅱ-Ⅳ BTC, DUPAN-2 showed the highest
sensitivity (80.3%), negative predictive value (75.0%), and diagnostic accuracy (81.4%). Although thedifference was not statistically significant, the serum concentration of DUPAN-2 tended to be higher
in patients with Stage Ⅱ-Ⅳ BTC than in those with Stage 0-Ⅰ BTC (46 vs 110 IU/mL, p＝0.095).

- 92 -DUPAN-2 in Biliary Tract Cancer
Table 3. Accuracy of DUPAN-2, CA19-9, and CEA according to the UICC stage
Stage 0-Ⅰ

Sensitivity%
NumberSpecificity%
NumberPositive predictive value%
Number
Negative predictive value%
NumberDiagnostic accuracy%
NumberStage Ⅱ-Ⅳ

DUPAN-2

CA19-9

CEA

CA19-9＋CEA

DUPAN-2

CA19-9

CEA

CA19-9
＋CEA

60.9
14/23

34.8
8/23

17.4
4/23

43.5
10/23

80.3
53/66

62.1
41/66

24.2
16/66

65.2
43/66

83
39/47

91.5
43/47

93.6
44/47

87.2
41/47

63.6
14/22

66.7
8/12

57.1
4/7

62.5
10/16

86.9
53/61

91.1
41/45

84.2
16/19

87.8
43/49

81.3
39/48

74.1
43/58

69.8
44/63

75.9
41/54

75
39/52

63.2
43/68

46.8
44/94

64.1
41/64

75.7
53/70

72.9
51/70

68.6
48/70

72.9
51/70

81.4
92/113

74.3
84/11353.1
60/113

74.3
84/113DUPAN-2, Duke pancreatic monoclonal antigen type 2; CA19-9, carbohydrate antigen 19-9; CEA, carcinoembryonicantigen; and UICC, International Union Against Cancer.

Postoperative transition of DUPAN-2
Of the 54 patients in whom the serum concentrations of DUPAN-2 were measured postoperatively,
the preoperative serum DUPAN-2 concentration was ≧30 IU/mL in 42 patients (pre-positive group)
and was ＜30 IU/mL in the remaining 12 patients (pre-negative group). In the pre-positive group, 36
had no recurrence, but 6 had recurrence within 3 to 6 months after surgery. Among the 36 patients
without recurrence, serum DUPAN-2 concentration decreased in 34 patients (94%) and decreased to＜30 IU/mL in 25 patients (69%) within 3 to 6 months after surgery. Of the 25 patients in whom thepostoperative serum DUPAN-2 concentration decreased to ＜30 IU/mL in the pre-positive group, 5 hadrecurrence; in these 5 patients, the serum DUPAN-2 concentration was re-elevated to ≧30 IU/mL.
On the other hand, among the 6 patients with recurrence within 3 to 6 months, the postoperative
serum DUPAN-2 concentration decreased in 3 patients (50%, p＝0.015 vs patients without recurrence)and decreased to ＜30 IU/mL in only 1 patient (17%, p＝0.023 vs patients without recurrence). In the
pre-negative group, serum DUPAN-2 concentration did not change postoperatively, even in 2 patientswith postoperative recurrence.

Discussion
It is well known that the serum CA19-9 concentration increases in some patients with BTC;
however, this manifestation is heterogeneous, with a sensitivity of 34.2%-90% and specificity of
54%-98%9-12,26-29). Moreover, the concentration of CA19-9 has been shown to increase in 13.8%-15.2%
of patients with BBTD10,30), 28% of patients with acute cholecystitis31) and 35.6% of patients withcholelithiasis32). In the present study, the increase in the concentration of CA19-9 was low in thecontrol group (8.5%), probably because the proportion of patients with biliary obstruction in whom
increased levels of CA19-9 may be secreted or leak into the blood stream31) was low. In addition, it- 93 -

Ito et al

must be kept in mind that Lewis antigen-negative patients can show false-negative results33). Our
results were in line with those of numerous studies suggesting that the serum CEA concentration isinferior to the serum CA19-9 concentration for diagnosing BTC10,33,34). The sensitivity and specificity
of serum CEA for detection of BTC have been reported to be 13.7%-68.6% and 78.4%-86.7%,
respectively10,12,35,36). Moreover, the serum CEA concentration has been shown to increase in only
20%-45% of patients with ICC37-42). Thus, the combination of CA19-9 and CEA (positivity for either
marker) is most commonly used to detect BTC; however, the results of our study suggest a sensitivityof 58.9%, which is inadequate.
When we set the cutoff value to ≧30 IU/mL (as calculated from the ROC curve), DUPAN-2 showeda diagnostic value superior to that of the conventional markers (CA19-9, CEA, and CA19-9＋CEA).
Moreover, our study indicated serum DUPAN-2 concentration decreased (＜30 IU/mL) postoperatively,
and was re-elevated (≧30 IU/mL) in patients with recurrence. This evidence suggests that DUPAN-2(≧30 IU/mL) is a useful tumor marker that can be used for diagnosing BTC. Moreover, whereas
59.5% of patients with BTC who were negative for CA19-9＋CEA were positive for DUPAN-2, 34.8%of the patients who were negative for DUPAN-2 were positive for CA19-9＋CEA (sensitivity of the 3tumor markers, 83.3%). Thus, the combination of DUPAN-2 and CA19-9＋CEA would also be usefulfor diagnosing BTC.
The serum concentrations of 4 of the 10 patients (40%) with BTC were ＞400 IU/mL in theprevious study20), whereas the serum concentrations of DUPAN-2 in 26 of 90 patients (28.9%) in thisstudy were ＞400 IU/mL. Although it is difficult to compare the characteristics of subjects between
the previous and present study, due to the unclear cancer stage and small population in the previous
study20), this difference may be related to the low proportion of patients with advanced BTC in thisstudy, as all subjects in our study were operable. A study including patients with advanced disease(inoperable cases) may be able to emphasize the usefulness of the measurement of serum DUPAN-2,
as the serum concentration of DUPAN-2 tended to be higher in patients with Stage Ⅱ-Ⅳ BTC than inthose with Stage 0-Ⅰ BTC.
The cutoff value of the serum DUPAN-2 concentration was set as ＞400 IU/mL in previous
studies20,24) and is ＞150 IU/mL in Japan. To determine the cutoff value for pancreas cancer, thecontrol group included patients with pancreatitis in whom the serum concentration of DUPAN-2 areoften increased. In the present study, the serum concentrations of DUPAN-2 in most patients in thecontrol group were low. Although the serum concentration of DUPAN-2 is reported to be inﬂuenced
by hepatitis and cirrhosis20), most patients in the control group in the present study did not have
hepatitis or cirrhosis, and the laboratory test results were mostly within the normal reference ranges,
as shown in Table 1. These patient characteristics in the control group in this study might haveaffected the establishment of the cutoff value (≧30 IU/mL) of DUPAN-2 and the high diagnostic
accuracy in this study. Therefore, the evaluation of serum DUPAN-2 in patients with hepatitis andcirrhosis as a control group is necessary. An investigation of the relationship between the serum
concentration of DUPAN-2 and the expression of DUPAN-2 in cancerous and noncancerous (hepatitis
and cirrhosis) may clarify their association with liver disease.
An important feature of tumor markers is that they are useful for detecting early-stage diseases.
Stage Ⅰ tumors are characterized by small and non-invasive growth without lymph node metastasis25).
Such conditions are difficult to diagnose on the basis of imaging examinations43,44) and/or conventional
tumor markers9,17,43,44). The sensitivity of CA19-9, CEA, and CA19-9＋CEA for patients with stage 0-Ⅰ- 94 -DUPAN-2 in Biliary Tract Cancer

BTC was very low. On the other hand, the sensitivity (60.9%) and negative predictive value (81.3%)
of DUPAN-2 for patients with stage Ⅰ BTC were higher. These findings suggest that DUPAN-2 would
be useful for diagnosing patients with early-stage BTC. Among 36 patients with preoperative serum
DUPAN-2 concentration ≧30 IU/mL, the postoperative serum DUPAN-2 concentration decreased in
34 patients (94%) and decreased to ＜30 IU/mL in 25 (69%) of 36 patients without recurrence from
3 to 6 months after surgery. In addition, postoperative recurrence reflected re-elevation of serum
DUPAN-2 concentration. The finding that BTC caused elevated serum DUPAN-2 concentration
before surgery suggested that the latter could be useful for diagnosis of postoperative cancer
recurrence if the preoperative serum DUPAN-2 concentration is ≧30 IU/mL. However, for BTC
patients with a preoperative serum DUPAN-2 concentration ＜30 IU/mL, diagnosis of recurrence
might be ineffective.
This study had some limitations. Samples from healthy volunteers will be needed to further
evaluate the accuracy of DUPAN-2 for diagnosing BTC. In the present study, however, these samples
could not ethically be obtained. Moreover, we evaluated the decrease in the serum DUPAN-2
concentration after surgery in patients with high preoperative concentrations; however, we could
not completely analyze the re-increase in the serum DUPAN-2 concentration in patients withpostoperative recurrence because of the short follow-up period. Further studies with a large numberof patients in a multicenter setting and a validation study will be necessary to obtain a definitive
conclusion.
In conclusion, we investigated the usefulness of measuring the serum concentration of DUPAN-2
in patients with BTC in comparison with that of measuring the serum concentrations of CA19-9 and
CEA, which are 2 conventional tumor markers. A serum DUPAN-2 concentration of ≧30 IU/mL or
a combination of a DUPAN-2 concentration of ≧30 IU/mL with CA19-9 and CEA may be useful for
diagnosing BTC, even at an early stage. Our results suggest that measurement of serum DUPAN-2
concentration would be useful for diagnosis of postoperative cancer recurrence.
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intrahepatic cholangiocarcinoma. Br J Surg 1998;85:1068-1070.
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with increased serum CYFRA 21-1 level. J Gastroenterol 1998;33:447-453.
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Pancreat Surg 1999;6:142-148.
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44. Tsukada K, Takada T, Miyazaki M, Miyakawa S, Nagino M, Kondo S, et al. Diagnosis of biliary tract andampullary carcinomas. J Hepatobiliary Pancreat Surg 2008;15:31-40.

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Osaka City Med. J. Vol. 64, 99-111, 2018

Comparison of Long-term Outcomes between Thoracoscopic
Esophagectomy and Open Esophagectomy by Using the Propensity
Score Matching in 655 Patients with Esophageal Cancer
SHIGERU LEE, HARUSHI OSUGI, SATORU KISHIDA, YUSHI FUJIWARA,RYOYA HASHIBA, KEN GYOBU, SHOJI KUBO, and TOSHIHIKO SHIBATA
Department of Gastroenterological Surgery, Osaka City University Graduate School of Medicine

Abstract
Background
The recent development of minimally invasive surgery has been beneficial, therefore the number ofpatients underwent thoracoscopic esophagectomy (TSE) has been increasing worldwide. Nevertheless,a multicenter randomized controlled trial of long-term oncological outcomes of TSE for patients withesophageal cancer in comparison with open esophagectomy (OE) has not been yet in manuscript form.
Methods
We compared the data between 454 patients who underwent curative TSE and 201 patients who
underwent curative OE from May 1995 to December 2014. In total, 174 paired cases of the 655
enrolled patients, 87 paired cases of 397 patients without metastatic mediastinal lymph node, and 66
paired cases of 258 patients with metastatic mediastinal lymph node−matched using the propensity
score (PS) method−were selected for statistical analysis.
Results
After PS matching, the 5-year overall survival rate was 55.6% and 55.0% in the TSE and OE groups,
respectively; no significant difference was observed in the survival curves. After PS matching among
those without mediastinal lymph node metastasis, the 5-year overall survival rate was 76.3% and62.5% in the TSE and OE groups, respectively, and after PS matching among those with mediastinal
lymph node metastasis, the 5-year overall survival rate was 41.5% and 43.6% in the TSE and OE
groups, respectively; no significant difference was observed in the survival curves.
Conclusions
Regardless of mediastinal lymph node metastasis, the oncological outcomes of TSE for patientswith esophageal cancer do not significantly differ compared to those of OE. TSE should be considered
as a standard procedure for resectable esophageal cancer.
Key Words: ‌Thoracoscopic esophagectomy; Esophageal cancer; Propensity scorematching; Long-term oncological outcome
Received September 5, 2017; accepted November 28, 2017.
Correspondence to: Shigeru Lee, MD.
Department of Gastroenterological Surgery, Osaka City University Graduate School of Medicine,
1-4-3 Asahimachi Abeno-ku, Osaka 545-8585, Japan
Tel: +81-6-6645-3880; Fax: +81-6-6646-6057
E-mail: sgr-lee@med.osaka-cu.ac.jp- 99 -

Lee et al

Introduction
Esophageal resection is the mainstay of curative treatment in resectable esophageal cancer.
However, surgeries for esophageal cancer are highly invasive and frequently result in complications.
Since the first report on thoracoscopic surgery for esophageal cancer published by Cuschieri andcolleagues in 19921), and as thoracoscopic surgery devices have evolved, the use of thoracoscopic
surgery for esophageal cancer has been increasing worldwide, with the goal of reducing invasivenessand incidence of complications. The conditions in Japan are similar − a 2011 nationwide survey
reported that, of 5354 annual cases of surgery for esophageal cancer, thoracoscopic esophagectomy(TSE) was performed in 1436 cases (26.8%) 2). The first multicenter randomized controlled trial (RCT)of perioperative outcomes of TSE, in comparison with open esophagectomy (OE), for patients withesophageal cancer was recently reported3). Biere and colleagues concluded that, in the perioperative
period, the amount of intraoperative bleeding, incidence of postoperative pneumonia, and durationof hospitalization are significantly lower with TSE than with OE. Moreover, the overall and diseasefree survival duration after the operation is the most important oncological outcome parameter.
However, no multicenter RCTs have investigated the long-term oncological outcomes of TSE.
The number of observational studies using the propensity score (PS) method has been increasing
in recent years4-6). PS matching was proposed by Rosenbaum and Rubin in 19837) and is a methodof assessment that adjusts the balance of patient characteristics between groups, thus making it auseful method of statistical analysis in cases where an RCT is difficult to perform. In the present
study, we report our experience with TSE and compare its long-term oncological outcome to that of
OE during the same period using PS matching method.

Methods
Patients
Since May 1995, we have routinely performed TSE with extensive mediastinal lymphadenectomy
according to the same surgical principles as open surgery. From May 1995 to December 2014,795 patients with thoracic esophageal cancer were candidates for radical esophagectomy without
preoperative radiotherapy at our hospital. The contraindications for TSE are: (1) contiguous tumor
spread, (2) preoperative radiotherapy due to contiguous tumor spread, (3) severely extensive pleuraladhesions, and (4) pulmonary function that is incapable of sustaining single-lung ventilation. TSE
was performed in 527 patients and planned OE was performed in 268 patients. TSE was converted
to conventional OE in 56 patients due to pleural adhesions in 22 patients, contiguous tumor spreadin 18 patients, suspected contiguous tumor spread in 10 patients, intrathoracic bleeding in 4
patients, and pulmonary function that is incapable of sustaining single-lung ventilation in 2 patients.
Complete TSE was performed in 471 patients. In 17 patients, the tumor or metastatic lymph nodes
had penetrated other vital structures, and therefore, palliative esophagectomy was performed
thoracoscopically. Thus, curative TSE with extended lymph node dissection was completed in 454
patients (TSE group). In patients who had previously undergone gastrectomy for gastric cancer or
peptic ulcer, we performed reconstruction using a jejunal pedicled graft via the posterior mediastinal
route under open thoracotomy, due to the safety associated with a reconstructive conduit. From May
1995 to December 2014, in 268 patients were performed OE for esophageal cancer, but 67 patients
received no curative operation. In total, 201 patients who had any of the above contraindications for
TSE and hence underwent curative resection by open thoracotomy or conversion to open thoracotomy- 100 -

Long-term Outcomes of TSE & OE after PS Matchingwere defined as the OE group.
Preoperative evaluations included physical examination, chest radiography, laboratory tests,
respiratory function tests, electrocardiography, upper gastrointestinal endoscopy with biopsy,
barium swallowing, computed tomography (CT) from the neck to the abdomen, and endoscopic
ultrasonography. Positron-emission tomography (PET) was also performed from April 2006.
Clinicopathological staging was performed according to the 2009 International Union Against Cancer
TNM classification (7th edition)7).
Surgery
The thoracoscopic procedure is performed with the patients in the left lateral position. The
trachea was intubated with a double-lumen tube, and the right lung is deﬂated during the thoracic
procedure. Four 11.5-mm trocars are inserted as follows: third intercostal space in the anterior
axillary line, 5th intercostal space in the posterior axillary line, 7th intercostal space in the middle
axillary line, and 7th intercostal space in the anterior axillary line. A 5-cm minithoracotomy iscreated in the 5th intercostal space in the middle axillary line, where the camera and a 3-cm wide
retractor designed by us are inserted. In patients with lower esophageal cancer, abdominothoracic
resection comprising radical lymphadenectomy (including the lymph nodes at the celiac trunk, left
gastric artery, paracardial, periesophageal, bifurcational, the upper mediatinal, and the surrounding
laryngeal recurrent nerve) was performed. In patients with upper or mid-esophageal cancer,
cervicoabdominothoracic (three-field) resection comprising radical lymphadenectomy was performed.
The magnifying effect of a video, according to the microanatomy by positioning the camera at close
vicinity to the dissection, is essential to perform the higher quality of dissection than open surgery(Fig. 1). The conventional open surgery procedure is performed with the patients in the left lateralposition and the right lung is deﬂated with a double-lumen tube in the same way as the thoracoscopic
procedure. The conventional open surgery was performed using right posterolateral thoracotomy.
Propensity score analysis
We performed one-to-one matching between TSE group and OE group on the basis of estimated PS
by using multivariate logistic regression analysis (stepwize method) for each patient. The usefulness
and details of the PS approach in clinical studies have been discussed elsewhere7,9,10). The applicationof PS matching involves estimation of PS, followed by matching of patients according to the estimatedPS and comparison of the outcomes in the matched patients. A one-to-one matched analysis using
nearest-neighbor matching (Greedy matching) was performed on the basis of the estimated PS of
the patients. A match occurred when a patient in the TSE group had an estimated score within 0.20
standard deviation of another in the OE group.
Statistical analysis
Descriptive statistics were presented for all patients and propensity score-matched patients.
Patient characteristics, perioperative results, and surgical performance were analyzed. Continuous
variables were compared by use of t-tests or Mann-Whitney s U-test, and categorical variables werecompared by use of the chi-square test, Fisher s exact test. Univariate analyses were performed
using Cox regression analysis with the forced entry method. We created Kaplan-Meier curves andused the log-rank test to assess prognosis after surgery. A value of p ＜0.05 was considered to besignificant statistically each analysis. All statistical analysis were conducted with IBM SPSS version
22 (IBM, Armonk, NY, USA)- 101 -

Lee et al

Figure. 1 Mediastinum after thoracoscopic radical esophagectomy. a, Right recurrent laryngeal nerve region. b, Leftrecurrent laryngeal nerve region. c, Infra-aortic arch region. d, Subcarinal region.

Results
The median and mean±standard deviation duration of follow-up among patients who survived
in the TSE group before propensity matching were 4.07 years and 4.95±3.87 years, respectively,
whereas those of patients in the OE group were 3.76 years and 4.89±4.06 years, respectively; no
significant difference in these values is present between the two groups. Thirty-five patients (5.3%)
who survived were not followed up more than 5 years after the operation, including 23 (5.0%) in
the TSE group and 12 (6.0%) in the OE group; this number did not significantly differ between thetwo groups. No intraoperative mortalities were noted in either group. The 30-day and operative
mortality rates of all patients in the present study were 0.8% (5/655) and 1.4% (9/655), respectively.
The 30-day mortality rate was 0.7% (3/454) in the TSE group and 1.0% (2/201) in the OE group (p＝0.649), whereas the operative mortality rate was 0.9% (4/454) in the TSE group and 2.5% (5/201) in
the OE group (p＝0.103). A trend toward improved operative mortality was noted in the TSE group,
although this trend was not statistically significant.
The results of univariate analysis are summarized in Table 1. In univariate analysis, thefollowing were all significant prognosticators: age; preoperative combined disease such as diabetes
mellitus, cardiovascular disease; respiratory disease; history of premalignant condition; pT factor;
pN factor; distant metastasis (M factor); permeation of the lymphatic vessels (ly); vascular invasion(v); pTNM stage; and number of metastatic lymph nodes. The characteristics of patients before PS
matching are summarized in Table 2. Significant differences were observed between the two groups- 102 -

Long-term Outcomes of TSE & OE after PS Matching
Table 1. ‌Univariate analysis of the prognostic influence of patient characteristics on overall survival in
655 patients performed curative resection
VariablesnHR

95% CI

p value65.3±8.32＊

1.027

1.011-1.043

0.001

540/1151.021

0.741-1.405

0.901

412

1.354

1.039-1.766

0.025

BMI

21.2±2.85＊

0.926

0.886-0.969

0.001

Respiratory function%VC

111.2±16.6＊

0.987

0.980-0.995

0.001

2.54±0.62＊

0.793

0.649-0.970

0.024

Preoperative another cancer
Metachronous
Synchronous

67
65

1.661
1.161

1.150-2.400
0.778-1.734

0.007

Neoadjuvant chemotherapy

176

1.073

0.772-1.491

0.676

Adjuvant chemotherapy

258

1.488

1.160-1.909

0.002

613/42

1.521

0.973-2.379

0.066

63
343
199

1.261
0.913

0.844-1.885
0.698-1.193

0.259
0.257
0.504

Age (per year)
Gender (Male/Female)
Combined disease

FEV1.0 (L)Histology (Squamous cell carcinoma/
Others including adenocarcinoma)
Location
Upper
MiddleLower
Depth of tumor invasion
pT0

0.464

＜0.001

8

pT1
pT2

282
100

0.366
0.356

0.091-1.478
0.267-0.475＜0.001

pT3

265

0.602

0.421-0.862

0.006

Lymph node metastasis
pN0

0.158

＜0.001

308

pN1

170

0.177

0.123-0.253＜0.001

pN2

108

0.265

69

0.593

0.181-0.388
0.408-0.862＜0.001

pN3
Lymphatic vessel invasion

384

3.018

2.241-4.064＜0.001

Blood vessel invasion

107

2.336

1.755-3.107＜0.001Distant metastasis

43

2.779

1.895-4.074＜0.001

Pathological stage
pStage 04

0.006＜0.001

pStage 1
pStage 2

236
154

0.000
0.195

0.000-6.013
0.125-0.306

pStage 3
pStage 4

218
43

0.301
0.671

0.190-0.475
0.449-1.002

0.943＜0.001＜0.001

0.051

Significant differences are marked in bold. ＊ Values depicted are expressed as mean±SD. BMI, body mass index;
VC, vital capacity; FEV, forced expiratory volume; HR, hazard ratio; and CI, confidence intervals.

- 103 -

Lee et al
Table 2. Characteristics of all patients before and after propensity score matching
Before propensity score matching(n＝655)After propensity score matching(n＝348)

TSE group(n＝454)

OE group(n＝201)

p value

TSE group(n＝174)

OE group(n＝174)p valueStandardized
differences

64.5±8.23

66.9±8.28

0.001

66.7±8.19

66.2±8.41

0.010

0.041

Gender (Male/Female)363 (80.0%)/
91 (20.0%)

177 (88.1%)/
24 (11.9%)

0.012

149 (85.6%)/
25 (14.4%)

150 (86.2%)/
24 (13.8%)

0.878

0.032

Combined disease

269 (59.3%)

143 (71.1%)

0.004

123 (70.7%)

120 (69.0%)

0.731

0.012

BMI (mean±SD)20.9±2.88

21.1±2.81

0.102

21.0±2.57

20.9±2.92

0.744

0.037

%VC (mean±SD)112.8±16.3

106.5±16.3＜0.001

107.1±14.9107.3±16.4

0.670

0.013

FEV1.0 (L, mean±SD)2.60±0.64

2.42±0.58

0.001

2.44±0.58

2.43±0.60

0.781

0.006

Metachronous

30 (6.6%)

37 (18.4%)＜0.00121 (12.1%)

25 (14.4%)

0.527

0.056

Synchronous

32 (7.1%)

33 (16.4%)＜0.00121 (12.1%)

24 (13.6%)

0.632

0.031

Neoadjuvant chemotherapy

125 (27.5%)

51 (25.4%)

0.565

46 (26.4%)

39 (22.4%)

0.382

0.073

Adjuvant chemotherapy

180 (39.6%)

81 (40.3%)

0.821

70 (39.3%)

68 (38.2%)

0.450

0.023

Number of harvested mediastinal
lymph node (mean±SD)32.28±12.28

32.08±11.13

0.919

33.59±13.20

31.94±10.79

0.352

0.136

Number of metastatic mediastinal
lymph node (mean±SD)

2.34±4.73

2.69±4.68

0.168

1.36±2.83

1.33±2.28

0.732

0.029

Total number of metastatic lymph
node (mean±SD)

2.34±4.73

2.69±4.68

0.168

2.74±4.64

2.69±4.62

0.988

0.009

0.499

0.051

425 (93.6%)

188 (93.5%)

162 (93.1%)

165 (94.8%)

29 (6.4%)

13 (6.5%)

12 (6.9%)9 (5.2%)8 (1.8%)/446 (98.2%)
233 (51.3%)/
221 (48.7%)302 (66.5%)/
152 (33.5%)

0 (0%)/
201 (100%)
57 (28.4%)/
144 (71.6%)
88 (43.8%)/
113 (56.2%)

0 (0%)/
174 (100%)
56 (32.2%)/
118 (67.8%)
81 (46.6%)/
93 (53.2%)

0 (0%)/
174 (100%)
56 (32.2%)/
118 (67.8%)
82 (47.1%)/
92 (52.9%)

1.000

0.000

1.000

0.000

0.914

0.034

219 (48.2%)/
235 (51.8%)335 (73.8%)/
119 (26.2%)
411 (90.5%)/
43 (9.5%)

89 (44.3%)/
112 (55.7%)
143 (71.1%)/
58 (28.9%)
175 (87.1%)/
26 (12.9%)78 (44.8%)/
96 (55.2%)
120 (69.0%)/
54 (31.0%)
153 (87.9%)/21 (12.1%)

77 (44.3%)/
97 (55.7%)
123 (70.7%)/
51 (29.3%)
152 (87.4%)/
22 (12.6%)

0.914

0.023

0.726

0.029

0.871

0.034

Lymphatic vessel invasion

255 (56.2%)

129 (64.2%)

0.055

103 (59.2%)

111 (63.8%)

0.378

0.067

Blood vessel invasion

65 (14.3%)

42 (20.9%)

0.036

32 (18.7%)

33 (19.0%)

0.892

0.014

Distant metastasis

27 (5.9%)

17 (8.5%)

0.228

16 (9.0%)

16 (9.0%)

1.000

0.000

4 (0.9%)/450 (99.1%)
189 (41.6%)/
265 (58.4%)
287 (63.2%)/
167 (36.8%)
428 (94.3%)/
26 (5.7%)

0 (0.0%)/201 (100%)
51 (25.4%)/
150 (74.6%)
107 (53.2%)/
94 (46.8%)
184 (91.5%)/
17 (8.5%)

0.182

0 (0%)

0 (0%)

1.000

0.000

53 (30.5%)/
121 (69.5%)
91 (52.3%)/
83 (47.7%)
163 (93.7%)/
11 (6.3%)

47 (27.0%)/127 (73.0%)
95 (54.6%)/
79 (45.4%)
159 (91.4%)/
15 (8.6%)

0.477

0.134

0.667

0.072

0.415

0.091

Age (mean±SD)

Respiratory function

Preoperative another cancer

Histology
Squamous cell carcinoma
Others included adenocarcinoma

0.969

Depth of tumor invasion
pT0/1-3
pT0-1/2-3
pT0-2/3

0.058＜0.001＜0.001

Lymph node metastasis
pN0/1-3
pN0-1/2-3
pN0-2/3

0.349
0.482
0.183

Pathological stage
pStage 0/1-4
pStage 0-1/2-4
pStage 0-2/3-4
pStage 0-3/4＜0.001

0.016
0.193

Significant differences are marked in bold. TSE, thoracoscopic esophagectomy; OE, open esophagectomy; and BMI, body mass index.

- 104 -

Long-term Outcomes of TSE & OE after PS Matching

Figure. 2 The cumulative overall survival (OS) and disease-free survival (DFS) of all patients after propensity scorematching. TSE, thoracoscopic esophagectomy; OE, open esophagectomy; and 95% CI, 95% confidence intervals.

in each of the following: age; gender; preoperative combined diseases; %VC; FEV1.0%; pT factor;
and pTNM stage. The variables that were significantly different between the two groups and all
significant prognosticators on univariate analysis were then used to perform PS matching.
As a result, 174 matched groups were created for each characteristic (c statistic＝0.732). The
patient characteristics after PS matching are summarized in Table 2. The standardized differencesin all the meaningful characteristics between the matched groups were ≦0.1. The Kaplan-Meiersurvival curves were created for the TSE group and the OE group and were then assessed with alog-rank test. Before PS matching, the 5-year overall survival rate was 63.5% in the TSE group and
54.2% in the OE group; thus, the TSE group demonstrated a significantly favorable prognosis in its
survival curve (p＝0.030, not presented). After PS matching, however, the 5-year overall survival rate
was 55.6% in the TSE group and 55.0% in the OE group; thus, there was no significant difference inthe survival curves (p＝0.263) (Fig. 2). After PS matching, the 5-year disease-free survival rate was
49.7% in the TSE group and 48.1% in the OE group; thus, no significant difference was noted in thesurvival curves (p＝0.284) (Fig. 2).
Among the 397 patients without mediastinal lymph node metastasis, PS matching was similarly
performed using the previously mentioned characteristics, resulting in the creation of 87 matchedgroups for each characteristic (c statistic＝0.759). The patient characteristics before and after PS
matching are summarized in Table 3. The standardized differences in all the characteristics between
matched groups were ≦0.1. After PS matching, the 5-year overall survival rate was 76.3% in the- 105 -

Lee et al
Table 3. Characteristics‌of patients without metastatic mediastinal lymph node before and after propensity
score matching
Before propensity score matching(n＝397)After propensity score matching(n＝174)

TSE group(n＝287)

OE group(n＝110)p value

TSE group(n＝87)

OE group(n＝87)

p valueStandardized
differences

64.5±8.22

68.0±8.22＜0.00166.2±7.49

67.0±8.32

0.910

0.072

Gender (Male/Female)234 (81.5%)/
53 (18.5%)

97 (90.0%)/
11 (10.0%)

0.040

78 (89.7%)/
9 (10.3%)

76 (87.4%)/
11 (12.6%)

0.635

0.097

Combined disease

176 (61.3%)

79 (71.8%)

0.051

60 (69.0%)

63 (72.4%)

0.617

0.076

BMI (mean±SD)21.5±2.90

21.1±2.81

0.116

21.1±2.80

21.3±2.92

0.744

0.080

%VC (mean±SD)112.5±16.0

105.1±16.3＜0.001108.4±15.4107.7±15.9

0.670

0.013

FEV1.0 (L, mean±SD)

2.57±0.61

2.37±0.55

0.001

2.45±0.57

2.42±0.56

0.781

0.006

Metachronous

20 (7.0%)22 (20.0%)＜0.001

11 (12.6%)

11 (12.6%)

1.000

0.000

Synchronous

23 (8.0%)

14 (12.7%)

0.148

8 (9.2%)10 (11.5%)

0.619

0.076

Neoadjuvant chemotherapy

78 (27.2%)

25 (22.7%)

0.365

22 (25.3%)

20 (23.0%)

0.723

0.054

Adjuvant chemotherapy

59 (20.6%)

24 (21.8%)

0.782

21 (24.1%)

18 (21.8%)

0.719

0.055

Number of harvested mediastinal
lymph node (mean±SD)32.04±11.94

30.96±11.48

0.319

33.59±13.20

31.94±10.79

0.352

0.146

Total number of metastatic lymph
node (mean±SD)

0.63±2.33

0.61±2.05

0.381

0.78±2.61

0.86±3.09

0.482

0.036

0.650

0.069

268 (93.4%)

107 (97.3%)

84 (96.6%)

85 (97.7%)

19 (6.6%)

3 (2.7%)3 (3.4%)2 (3.4%)

pT0/1-3

6 (2.1%)/281 (97.9%)

0 (0%)/
110 (100%)

0.126

0/
0 (0%)0/0 (0%)

1.000

0.000

pT0-1/2-3

187 (65.2%)/
100 (34.8%)

43 (39.1%)/
67 (60.9%)＜0.00143 (47.8%)/
47 (52.2%)

41 (45.6%)/
49 (54.4%)

0.497

0.045

pT0-2/3

228 (79.4%)/
59 (20.6%)

59 (53.6%)/
51 (46.4%)＜0.00155 (61.1%)/
35 (38.9%)

54 (60.0%)/36 (40.0%)

0.749

0.023

pN0/1-3

219 (76.3%)/
68 (23.7%)

89 (80.9%)/21 (19.1%)

0.325

65 (74.7%)/
22 (25.1%)

68 (78.2.%)/19 (21.8%)

0.721

0.081

pN0-1/2-3

268 (93.4%)/
19 (6.6%)

104 (94.5%)/
6 (5.5%)0.669

81 (93.1%)/
6 (6.9%)83(95.4%)/4 (4.6%)

0.747

0.099

pN0-2/3

284 (98.7%)/
3 (1.3%)108 (98.2%)/
2 (1.8%)0.537

85 (97.7%)/
2 (2.3%)85 (97.7%)/
2 (2.3%)

1.000

0.000

Lymphatic vessel invasion

116 (40.4%)

52 (47.3%)

0.216

41 (47.1%)

42 (48.3%)

0.879

0.239

Blood vessel invasion

30 (10.5%)

14 (12.7%)

0.518

10 (11.5%)

10 (11.5%)

1.000

0.000

Distant metastasis

5 (1.7%)3 (2.7%)0.532

3 (3.4%)3 (3.4%)

1.000

0.000

pStage 0/1-4

4 (1.4%)/283 (98.6%)

0 (0.0%)/110 (100%)0.213

0 (0%)/
87 (100%)

0 (0%)/
87 (100%)

1.000

0.000

pStage 0-1/2-4

189 (65.9%)/
98 (34.1%)

51 (46.4%)/
59 (53.6%)＜0.00142 (48.3%)/
45 (51.7%)

45 (51.7%)/
42 (48.3%)

0.649

0.034

pStage 0-2/3-4

250 (87.1%)/
37 (12.9%)

95 (86.4%)/
15 (13.6%)

0.844

74 (85.1%)/
13 (14.9%)

74 (85.1%)/
13 (14.9%)

1.000

0.000

pStage 0-3/4

282 (98.0%)/5 (1.7%)107 (97.3%)/
3 (2.7%)0.532

84 (96.6%)/
3 (3.4%)84 (96.6%)/
3 (3.4%)

1.000

0.000

Age (mean±SD)

Respiratory function

Preoperative another cancer

Histology
Squamous cell carcinoma
Others included adenocarcinoma

0.129

Depth of tumor invasion

Lymph node metastasis

Pathological stage

Significant differences are marked in bold. TSE, thoracoscopic esophagectomy; OE, open esophagectomy; and BMI, body mass index.

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Long-term Outcomes of TSE & OE after PS Matching

Figure. 3 The cumulative overall survival (OS) and disease-free survival (DFS) of patients without metastatic
mediastinal lymph node after propensity score matching. TSE, thoracoscopic esophagectomy; OE, open esophagectomy;
and 95% CI, 95% confidence intervals.

TSE group and 62.5% in the OE group (p＝0.080). The 5-year disease-free survival rate was 69.2% in
the TSE group and 57.3% in the OE group (p＝0.061) (Fig. 3). There was no significant difference inthe survival curves between the two groups, however, a trend toward improved survival curve after
operation was noted in the TSE group.
Among the 258 patients with mediastinal lymph node metastasis, PS matching was similarly
performed using the previously mentioned characteristics, resulting in the creation of 66 matchedgroups for each characteristic (c statistic＝0.703). The patient characteristics before and after PS
matching are summarized in Table 4. The standardized differences in all the characteristics between
matched groups were ≦0.1. After PS matching, the 5-year overall survival rate was 41.5% in the TSEgroup and 43.6% in the OE group; thus, there was no significant difference in the survival curves (p＝0.671) (Fig. 4). After PS matching, the 5-year disease-free survival rate was 29.3% in the TSE groupand 33.2% in the OE group; thus, there was similarly no significant difference in the survival curves (p＝0.878) (Fig. 4).

Discussion
More than two decades have passed since the first report of TSE for patients with esophageal
cancer by Cuschieri and colleagues in 19921). However, TSE is not technically easy, and the operator
needs to be sufficiently experienced to achieve satisfactory outcomes11-13). The recent development of- 107 -

Lee et al
Table 4. ‌Characteristics of patients with metastatic mediastinal lymph node before and after propensity
score matching
Before propensity score matching(n＝258)
TSE group(n＝167)Age (mean±SD)

OE group(n＝91)

p value

After propensity score matching(n＝132)
TSE group(n＝66)

OE group(n＝66)

p valueStandardized
differences

64.6±8.29

65.6±8.16

0.362

65.0±9.1765.2±8.08

0.936

0.014

129 (77.2%)/
38 (22.8%)

78 (85.7%)/
13 (14.3%)

0.105

53 (80.3%)/
13 (19.7%)

54 (81.8%)/
12 (18.2%)

0.826

0.039

Combined disease

93 (55.7%)

64 (70.3%)

0.021

38 (57.6%)

41 (62.1%)

0.723

0.000

BMI (mean±SD)21.1±17.0

20.7±17.0

0.347

20.8±17.0

20.9±17.0

0.885

0.025

%VC (mean±SD)113.5±17.0

109.2±16.6

0.049

110.6±17.5109.1±16.6

0.825

0.039

FEV1.0 (L, mean±SD)

2.64±0.68

2.50±0.58

0.104

2.53±0.73

2.53±0.60

0.663

0.076

Gender (Male/Female)

Respiratory function

Preoperative another cancer
Metachronous

10 (6.0%)

15 (16.5%)

0.008

9 (13.6%)

7 (10.6%)

0.791

0.000

Synchronous

9 (5.4%)19 (20.9%)＜0.0019 (13.6%)

9 (13.6%)

1.000

0.000

Neoadjuvant chemotherapy

47 (28.1%)

26 (28.6%)

0.886

17 (25.8%)

16 (24.2%)

0.841

0.035

Adjuvant chemotherapy

119 (71.3%)

56 (61.5%)

0.126

44 (66.7%)

43 (65.2%)

0.865

0.032

Number of harvested mediastinal
lymph node (mean±SD)32.71±10.73

33.30±10.73

0.494

33.29±12.19

33.21±11.53

0.764

0.098

Number of metastatic mediastinal
lymph node (mean±SD)

2.92±3.32

3.29±3.540.245

2.98±3.69

3.27±3.26

0.245

0.083

Total number of metastatic lymph
node (mean±SD)

5.27±6.29

5.19±5.51

0.780

5.68±7.61

5.30±5.61

0.860

0.057

0.729

0.068

157 (94.0%)

81 (89.0%)

63 (95.5%)

62 (93.9%)

10 (6.0%)

10 (11.0%)

3 (4.5%)4 (6.1%)2 (1.2%)/165 (98.8%)
46 (27.5%)/
121 (72.5%)
74 (44.3%)/
9 (55.7%)

0 (0%)/
91 (100%)
14 (15.4%)/
77 (84.6%)
29 (31.9%)/
62 (68.1%)

0/0 (0%)
17 (23.0%)/
57 (77.0%)
23 (34.8%)/
43 (65.2%)0/0 (0%)
14 (18.1%)/
48 (81.9%)
23 (34.8%)/
43 (65.2%)

1.000

0.000

0.497

0.099

1.000

0.000

0 (0%)/
167 (100%)
67 (40.1%)/
100 (59.9%)
127 (76.0%)/40 (24.0%)

0 (0%)/
91 (100%)
39 (42.9%)/52 (57.1%)
67 (73.6%)/
24 (26.4%)

0/0 (0%)
24 (36.4%)/
42 (63.6%)
51 (77.3%)/
15 (22.7%)0/0 (0%)
27 (40.9%)/39 (59.1%)
49 (74.2%)/
17 (25.8%)

1.000

0.000

0.789

0.093

0.747

0.071

Lymphatic vessel invasion

139 (83.2%)

77 (84.6%)

0.861

60 (90.9%)

59 (89.4%)

0.770

0.051

Blood vessel invasion

35 (21.0%)

28 (30.8%)

0.095

18 (27.3%)

17 (25.8%)

0.892

0.034

Distant metastasis

21 (12.4%)

14 (15.4%)

0.569

9 (13.6%)

10 (15.2%)

0.804

0.043

0 (0%)/
167 (100%)0 (0%)/
167 (100%)
37 (22.2%)/
130 (77.8%)
146 (86.4%)/
21 (13.6%)

0 (0%)/
91 (100%)
0 (0%)/
91 (100%)
12 (13.2%)/
79 (86.8%)
77 (84.6%)/
14 (15.4%)

0 (0%)/
66 (100%)
0 (0%)/
66 (100%)
10 (15.2%)/
56 (84.8%)
57 (86.4%)/
9 (13.6%)

0 (0%)/
66 (100%)
0 (0%)/
66 (100%)
11 (16.7%)/
55 (83.3%)
56 (84.8%)/
10 (15.2%)

1.000

0.000

1.000

0.000

0.812

0.041

0.804

0.043

Histology
Squamous cell carcinoma
Others included adenocarcinoma

0.151

Depth of tumor invasion
pT0/1-3
pT0-1/2-3
pT0-2/3

0.542
0.031
0.062

Lymph node metastasis
pN0/1-3
pN0-1/2-3
pN0-2/3

1.000
0.693
0.763

Pathological stage
pStage 0/1-4
pStage 0-1/2-4
pStage 0-2/3-4
pStage 0-3/4

1.000
1.000
0.098
0.569

Significant differences are marked in bold. TSE, thoracoscopic esophagectomy; OE, open esophagectomy; and BMI, body mass index.

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Long-term Outcomes of TSE & OE after PS Matching

Figure. 4 The cumulative overall survival (OS) and disease-free survival (DFS) of patients with metastatic
mediastinal lymph node after propensity score matching. TSE, thoracoscopic esophagectomy; OE, open esophagectomy;
and 95% CI, 95% confidence intervals.

minimally invasive surgery has yielded many benefits, therefore the number of patients undergoing
TSE has been increasing worldwide. In recent times, TSE in the prone or semi prone position is being
increasingly performed in many countries3,14), however; we continue to perform TSE in the left lateralposition, because this approach is very safety, and educational for OE. As TSE in the left lateralposition can be immediately converted to open surgery, we did not experience any intraoperative life
threatening complication.
Biere and colleagues concluded that the short-term benefits were better with TSE than with OE
in the first report of multicenter RCT of perioperative outcomes of TSE3). However, in a Japanesenationwide web-based database report, Takeuchi and colleagues reported that the overall morbidity
was significantly higher in the minimally invasive esophagectomy group than in the OE group2).
Moreover, the 30-day mortality rate and operative mortality rate after esophagectomy for cancer were1.2% and 3.4%, respectively, in this report. Furthermore, in a review of over 1000 patients performed
TSE, Luketich and colleagues reported that the combined 30-day mortality rate, including in-housemortality, after minimally invasive esophagectomy was 2.8%14). Hence, the 30-day mortality rate
and operative mortality rate after esophagectomy for cancer in the present study of 0.8% and 1.4%,
respectively, it appears acceptable; in particular, those after TSE were 0.7% and 0.9%, respectively,
and those after OE were 1.0% and 2.5%, respectively, and there was no significant difference between
the two groups. Specifically, the total 30-day mortality rate after TSE (0.7%) was acceptable.

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Lee et al

Although a low mortality rate after esophagectomy was recently achieved, it remains high ascompared with that after gastrectomy or colectomy2,15-18). Several reports state that the mortality rate
after esophagectomy is correlated with the hospital volume and surgeon volume11-13). Esophagectomy
requires experienced surgeons and a well-trained perioperative care team. Fujita and colleagues
reported that the 30-day mortality rate and hospital mortality rate of a low-volume hospital andhigh-volume hospital were 2.0% and 6.0% and 0.6% and 2.1%, respectively11). The 5-year average ofannual radical esophagectomies performed at our hospital is approximately 80. In the 2011 Japanesenationwide web-based database report, 5354 patients underwent esophagectomy for cancer across
713 hospitals 2). The average number of patients who underwent esophagectomy in one hospital is7.5, which means that many patients underwent esophagectomy in low volume hospitals in Japan.
This situation may be attributable to the difference between hospital death or morbidity after
esophagectomy in rest of Japan and our hospital. TSE requires a good expertise of the operating
surgeons and of all assisting team, we have previously reported the learning curve of TSE foresophageal cancer22). In our team, TSE could be performed with beneficial outcomes after experiencein treating 34 cases. Hence, the perioperative benefits of TSE in hospitals other than high-volume
centers may remain controversial.
A multicenter RCT of the long-term oncologic outcomes of TSE for patients with esophageal
cancer, in comparison with OE, has not been conducted. Hence, the long-term oncologic feasibilityof thoracoscopic surgery for esophageal cancer is not established. To confirm the oncological benefitsof TSE, an RCT is needed. However, we previously reported that the reduction of %VC on 3 months
after operation was significantly lower in TSE than OE19) and the amount of bleeding in thoracic
procedure was significantly lesser in TSE than OE20-22). Thus, an RCT of TSE in comparison with
OE among patients with esophageal cancer is difficult to perform because most of the patients withresectable esophageal cancer would prefer TSE.
In recent years, reports of the use of a PS method in observational studies have been increasing4-6).
The advantage of using the PS method is that it balances the patient characteristics between groups,
thus enabling the elimination of almost all selection bias 7,9,10). By using this method to compare
strictly and examine long-term survival following TSE and OE for thoracic esophageal cancer, a trend
toward improved survival curve after operation for esophageal cancer without mediastinal lymph
node metastasis was noted in the TSE group, however, we observed that TSE and OE demonstrate no
significant differences in terms of overall survival and disease-free survival. Moreover, patients withmediastinal lymph node metastasis demonstrated no significant difference in, and nearly identicaloutcomes for, overall survival and disease-free survival between TSE and OE. The other advantagesof TSE include favorable esthetic outcomes, reduction in bleeding, and preservation of postoperative
respiratory function. When these advantages are taken into account, TSE can be considered
superior to OE as a treatment procedure for resectable thoracic esophageal cancers, regardless ofthe presence of mediastinal lymph node metastasis. Thus far, a few systematic literature reviews of
the oncological outcomes comparing minimum invasive esophagectomy to open esophagectomy havebeen published. Dantoc M and colleagues concluded that meta-analytic evidence found equivalent
oncologic outcomes to conventional open esophagectomy23). The long-term oncological outcomes of ourstudy matched using the PS method are similar to the results of meta-analysis that did not mention
the existence of mediastinal lymph node metastasis.

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Long-term Outcomes of TSE & OE after PS Matching

References
1. Cuschieri A, Shimi S, Banting S. Endoscopic oesophagectomy through a right thoracoscopic approach. J R Coll
Surg Edinb 1992;37:7-11.
2. Takeuchi H, Miyata H, Gotoh M, Kitagawa Y, Baba H, Kimura W, et al. A risk model for esophagectomy using
data of 5354 patients included in a Japanese nationwide web-based database. Ann Surg 2014;260:259-266.
3. Biere SS, van Berge Henegouwen MI, Maas KW, Bonavina L, Rosman C, Garcia JR, et al. Minimally invasive
versus open oesophagectomy for patients with oesophageal cancer; a multicenter, open-label, randomized
controlled trial. Lancet 2012;379:1887-1892.
4. Gum PA, Thamilarasan M, Watanabe J, Blackstone EH, Lauer MS. Aspirin use and all-caouse mortakity
among patients being evaluated for known or suspected coronary artery desease. JAMA 2001;286:1187-1194.
5. Stukel TA, Fisher ES, Wennberg DE, Alter DA, Gottlieb DJ, Vermeulen MJ. Analysis of observational studies
in the presence of treatment selection bias; effects of invasivecardiac management on AMI survival score andinstrumental variablw methods. JAMA 2007;297:278-285.
6. Griswold ME, Lacalio AR, Mulrow C. Propensity score adjustment with multilevel data: setting your site on
decreasing selectin bias. Ann Intern Med 2010;152:393-395.
7. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects.
Biometrika 1983;70:41-55.
8. Sobin LH, Gospodarowwicz MK, Wittekind C. UICC TNM Classification of Malignant Tumours, 7th edn. Oxford,
wiley-Blackwell 2009. pp63-72.
9. D Agostino RB Jr. Propensity score methods for bias reduction in the comparison of a treatment to a nonrandomized control group. Stat Med 1998;17:2265-2281.
10. Austin PC, Mamdani MM. A comparison of propensity score methods: a case study estimating the effectivenessof post-AMI statin use. Stat Med 2006;25:2084-2106.
11. Fujita H, Ozawa S, Kuwano H, Ueda Y, Hattori S, Yanagawa T, et al. Esophagectomy for cancer: clinicalconcerns support centralizing operations within the larager hospitals. Dis Esophagus 2010;23:145-152.
12. Migliore M, Choong CK, Lim E, Goldsmith KA, Ritchie A, Wells Fc. A surgeon s case volume of esophagectomy
for cancer strongly inﬂuences the operative mortality rate. Eur J Cardiothorac Surg 2007;32:375-380.
13. Rodgers M, Jobe BA, O Rourke RW, Sheppard B, Diggs B, Hunter JG. Case volume as a predictor of inpatientmortality after esophagectomy. Arch Surg 2007;142:829-839.
14. Luketich JD, Pennathur A, Awais O, Levy RM, Keeley S, Shende M, et al. Outcomes after minimally invasive
esophagectomy; review of over 1000 patients. Ann Surg 2012;256:95-103.
15. Moriwaki Y, Kobayashi S, Kunisaki C, Harada H, Imai S, Kido Y, et al. Is D2 lymphadenectomy ingastrectomy safe with regard to the skill of the operation? Dig Surg 2001;18:111-117.
16. Watanabe M, Miyata H, Gotoh M, Baba H, Kimura W, Tomita N, et al. Total gastrectomy risk model: datafrom 20,011 Japanese patients in a nationwide internet-based database. Ann Surg. 2014;260:1034-1039.
17. Kobayashi H, Miyata H, Gotoh M, Baba H, Kimura W, Kitagawa Y, et al. Risk model for right hemicolectomy
based on 19,070 Japanese patients in the National Clinical Database. J Gastroenterol 2014;49:1047-1055.
18. Birkmeyer JD, Siewers AE, Finlayson EV, Stukel TA, Lucas FL, Batista I, et al. Hospital volume and surgicalmortality in the United States. N Engl J Med 2002;346:1128-1137.
19. Taguchi S, Osugi H, Higashino M, Tokuhara T, Takada N, Takemura M, et al. Comparison of three-fields
esophagectomy for esophageal cancer incorporating open or thoracoscopic thoracotomy. Surg Endosc 2003;17:1445-1450.
20. Osugi H, Takemura M, Higashino M, Takada N, Lee S, Kinoshita H. A coparison of video-assisted
thoracoscopic oesophageactomy and radical lymph node dissection for squamous cell cancer of the oesophagus
with open operation. Br J Surg 2003;90:108-113.
21. Osugi H, Takemura M, Lee S, Nisihikaawa T, Fukuhara K, Iwasaki H, et al. Thoracocscopic esophagectomy
for intrathoracic esophageal cancer. Ann Thorac Cardiovasc Surg 2005;11:221-227.
22. Osugi H, Takemura M, Higashino M, Takada N, Lee S, Ueno M, et al. Learning curve of viedo-assitedthoracoscopic esophageactomy and extensive lymphadecetomy for squamous cell cencer of the thoracic
esophagus and results. Surg Endosc 2002;17:515-519.
23. Dantoc M, Cox MR, Eslick GD. Evidence to support the use of minimally invasive esophagectomy foresophageal cancer: a meta-analysis. Arch Surg 2012;147:768-776.

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Osaka City Med. J. Vol. 64, 113-119, 2018

Molecular Characterization of Familial Platelet Disorder with
Propensity to Develop Acute Myeloid Leukemia during
the course of Leukemogenesis
MASAHARU NAKAYA, SADAO TOKIMASA, TAKASHI HAMAZAKI, and HARUO SHINTAKU
Department of Pediatrics, Osaka City University Graduate School of Medicine

Abstract
Background
Familial platelet disorder with propensity to develop acute myeloid leukemia (FPD/AML) is an
autosomal dominant disorder characterized by congenital thrombocytopenia and a predisposition for
AML. This disease is caused by germline mutations in RUNX1, a gene encoding a hematopoietic
transcription factor located at chromosome 21q22. To explore the mechanisms of leukemogenesis in
FPD/AML, we focused on and characterized the molecular genetics of an FPD/AML patient with early
onset of AML.
Methods
Conventionally used and very accurate G-banding chromosome analysis, micro-array-based
comparative genomic hybridization, and fluorescence in situ hybridization were used during theremission and relapse phases. RNA sequencing and real-time polymerase chain reaction were
performed during the relapse phase.
Results
In the patient investigated in this study, we found a congenital complicated structural anomaly only
on chromosome 21, which caused separation of the RUNX1 gene. Upon leukemogenesis, the 5 regionof RUNX1 was amplified several folds with the breakpoint of RUNX1 being located between exons 3
and 4. Neither additional fusion gene products nor previously reported mutations were observed.
Conclusions
These data suggest amplification of an aberrant RUNX1 gene promotes the development ofleukemia in patients with FPD/AML.
Key Words: ‌FPD/AML; RUNX1; Leukemogenesis

Introduction
Familial platelet disorder with propensity to develop acute myeloid leukemia (FPD/AML)
Received September 13, 2017; accepted November 28, 2017.
Correspondence to: Sadao Tokimasa MD, PhD
Department of Pediatrics, Osaka City University Graduate School of Medicine,
1-4-3 Asahimachi, Abeno-ku, Osaka 545-8585, Japan
Tel: +81-6-6645-3816; Fax: +81-6-6636-8737
E-mail: tokimasa@med.osaka-cu.ac.jp- 113 -

Nakaya et al

is an autosomal dominant disorder characterized by thrombocytopenia and a predisposition
for myelodysplastic syndrome (MDS)/acute myeloid leukemia (AML). It is caused by germline
aberrations in the hematopoietic transcription factor RUNX1, which is located at chromosome
21q22. Most cases of FPD/AML are a result of germline point mutations in the RUNX1 gene, butthere are rare cases with large deletions at 21q221). RUNX1 encodes a transcription factor, whichcontains an amino-terminal DNA-binding RUNT homology domain (RHD) and a carboxyl-terminaltransactivation domain, essential for definitive hematopoiesis 2). The predisposition of myeloid
leukemia varies between individual patients. Although the average age of onset of leukemia in FPD/AML patients is 34 years, the youngest recorded patient was 6 years old3).
The mechanisms of leukemogenesis are complex and largely uncharacterized. Several additional
genetic events involved at this stage have been identified, including mutations in CBL4), CDC25C1),
and TET25). Various parts of RUNX1 can combine with other genes to create fusion genes, such as
RUNX1/ETO6). Therefore, haploinsufficiency of the RUNX1 gene alone in FPD/AML patients is not
sufficient for leukemogenesis and a certain second hit may be required3).
To explore the mechanisms of leukemogenesis in FPD/AML patients, we extensively characterized
the molecular genetics of RUNX1 in a FPD/AML patient with early onset of AML. Uniquechromosomal anomalies were discovered in the RUNX1 locus, including amplification of a specificregion of this gene over the course of leukemogenesis.

Methods
Case
The patient investigated in this study was male and the second child of healthy unrelated parents.
His family history was unremarkable. He had a funnel chest, flexible ankle and mild mental
retardation. Mild thrombocytopenia was noted soon after birth and no serious bleeding episodes were
documented by the age of 7 years. At the age of 7 years, he developed AML (The French-AmericanBritish [FAB] classification M4). Several courses of chemotherapy were administered and resulted incomplete remission. However, the patient showed relapse one year later and received a transplant of
unrelated umbilical cord blood. He has been disease-free for more than 3 years.
Sample isolation and characterization
This present study was approved by the ethics committee of the Osaka City University (No. 2476)
and the informed written consent was obtained from the parents of the patient.
Peripheral blood lymphocytes (PBLs) were isolated using a Ficoll gradient. RUNX1 mutation
analysis was performed on the patient s PBLs during complete remission.
Cytogenetic analysis
Karyotype analysis was performed using highly accurate G-banding at a resolution of 400-550
bands (LSI Medience Corporation, Tokyo, Japan). The definition of a cytogenetic clone and descriptionsof karyotypes were according to the International System for Human Cytogenetic Nomenclature.
Micro-array-based comparative genomic hybridization (array-CGH)
Genomic copy numbers were measured using the Human Genome CGH Microarray 60k (Agilent
Technologies, Santa Clara, CA) as previously described7).
Fluorescence in situ hybridization
Fluorescence in situ hybridization (FISH) was performed using RUNX1-specific probes (LSI
Medience Corporation, Tokyo, Japan) according to the manufacturer s instructions.

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Leukemogenesis in FPD/AML
Table 1. Primer sequences

SOX1
SETD4
intergenic region
RUNX1
exon 1
introns 1-2
exon 2exon 3exon 4exon 5exon 6
introns 6-7.1
introns 6-7.2
introns 7-8
exon 8CLIC6

Forward Primer

Reverse Primer

ATTATTTTGCCCGTTTTCCC
CATGCCGACTTTCGTTAGGTTAGCACCCCAGTGAAAAAGGTCAAGGAAACACAATCGCTG
AGGGCAGAAATGAGCAAGAG
CTGGGGTAGGCAAATTACCATCGCTCCGAAGGTAAAAGAAGATGTGAGGGGCCTGAATAACAGCGTTTACCATAGGTGCATTAAAGGCCCCTGAACGTGTA
GGCTGGCAATGATGAAAACTGGGCAGCATGAAACTAAGGACCAACAATTAATGCGCCTCTGTTCATTGGGACCAAGTGCTTTCTAGCCTGCTCCTCCAAAGAGCTGCACCAAACTGTGAACACGCGCTACCACACCTACTGTTCTAAGCCTCCCAGCATTATGCTGTCTGAAGCCATCG
GGCTCTTTCTCCCTCCATCTGGAAGCCAAGCTCTGTTTTG
GTTAGGACCCTGCAAACAGC
CCGACAAACCTGAGGTCATT
CCTGGCCAATCTTCCATTTA
ACTTCCAATGGGCACAACTCCTCAAAGTGAGGCACGCATAGGTACCAAGATGTGGGGTTG
ATCCCAAGAGCTGAAAAGCAGAGGCGCCGTAGTACAGGTGCACCAAGAGAAACACAGCA

Quantification of gene copy numbers
Copy numbers of specific genomic regions were quantified using real-time PCR. Genomic DNA
was extracted from bone marrow cells. The copy number of a target region was expressed relative
to a reference gene, SOX1. PCR was performed with the SYBR Green qPCR premix (Invitrogen)and analyzed using the 7300 real-time PCR system (Applied Biosystems). Primer sequences arepresented in Table 1.
RNA sequencing
To prepare the library, the SureSelect Strand-Specific RNA library kit (Agilent Technologies,CA) was used according to the manufacturer s instructions. Brieﬂy, total mRNA obtained from thePBLs was poly-A purified, fragmented, and reverse transcribed into first-strand cDNA using random
primers. Following second-strand cDNA synthesis, end repair, addition of a single A base, adaptor
ligation, and 13 cycles of PCR amplification, the enriched cDNA libraries were sequenced using an
Illumina HiSeq 1500 system (Kazusa DNA Research Institute in Chiba, Japan) with 100 bp singleend RNA-sequence reads. Sequence files were generated in FASTQ format. Reads were thenprocessed and aligned to the Homo sapiens reference genome (NCBI build 37.2) using TopHat. The
unit of measurement was fragments per kilobase of exon per million fragments mapped. Obtained
FASTQ files were analyzed for mapping and detection of fused genes using Strand NGS software 2.5(Agilent Technologies, CA).

Results
Point mutations in the RUNX1 gene were not detected by direct sequencing (data not shown).
Screening for chimeric genes, such as RUNX1-ETO, in the bone marrow at the onset of leukemia,
revealed no such genes. Conventional chromosomal analysis in the remission marrow identified inv(21) (p11.2q21) (data not shown). Chromosome analysis by the highly accurate technique revealed
that one homologous chromosome 21 might be normal and the other had a complicated structure(Fig. 1 A and B). The short arm of the rearranged chromosome 21 was deleted without inducing- 115 -

Nakaya et al

Figure 1. Chromosomal analysis by high-resolution G-banding. G-Banding image of normal chromosome 21 (A) andof the rearranged chromosome 21 (B).

Figure 2. Array-CGH. The copy number of RUNX1 in the genome was normal during remission (A) and increased
during relapse (B).

any specific phenotype. The bands from q10 to q21 and from q22.3 to the telomere were duplicated,while the bands from q21 to q22.1 was deleted. Array-CGH analysis determined the copy number of
RUNX1 was normal in the remission bone marrow and amplified in the relapse bone marrow (Fig. 2).
Moreover, examination of RUNX1 by FISH revealed RUNX1 had split signals during remission andamplified signals during relapse (Fig. 3).

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Leukemogenesis in FPD/AML

Figure 3. Dual color FISH using RUNX1 5 and 3 probes. The split red and green signals indicate translocation of
RUNX1 and the yellow signal indicates RUNX1 with the absence of translocation during remission (A). The increased
number of green signals indicates the amplification of the 5 side RUNX1 gene during relapse (B). FISH, Fluorescencein situ hybridization.

Figure 4. Copy number changes in the RUNX1 genomic region and neighboring genes. Genomic DNA was extracted
from bone marrow cells. Copy numbers of indicated regions were calculated relative to the reference region (SOX1)
based on real-time PCR. White bar, normal control; hatched bar, patient during remission; and gray bar, leukemic
cells.

To determine which regions of RUNX1 were amplified during leukemogenesis, we measured the
copy numbers of the genomic region of RUNX1 and neighboring genes. The copy numbers were

- 117 -

Nakaya et al

expressed relative to a reference gene, SOX1, located on a different chromosome from RUNX1. Basedon array-CGH and FISH analysis, we expected increases of several fold in copy number of the 5regions of RUNX1 when comparing remission to relapse. As shown in Figure 4, an increase of several
fold in copy number was observed in the 5 neighboring gene (SETD4), 5 intergenic region, and exons
2 and 3 of RUNX1. However, significant changes were not observed in exon 4 of RUNX1 and any 3
regions further downstream in the genome of leukemic cells. These data suggest the break point of
the chromosomal abnormality resided between exons 3 and 4 of RUNX1. Amplification of the exon 2
and 3 region may be involved in leukemogenesis.
To explore the mechanisms of leukemogenesis in FPD/AML, we extracted RNA from patient bonemarrow cells during relapse and analyzed it using RNA sequencing. Although RNA sequencing isan efficient tool for detecting fusion genes in cancer8), neither additional fusion gene products nor
previously reported additional mutations, such as CDC25C1) were observed in this patient.

Discussion
In this study, we explored the molecular genetic changes that occur over the course of leukemogenesis
with FPD/AML. Heterozygous disruption of the RUNX1 gene is known to cause FPD, but is not
sufficient to induce the development of AML. Therefore, we exhaustively searched for the second
hit in an FPD/AML patient who developed AML earlier than in previously reported FPD cases. We
found the followings in this patient: 1) a congenital complicated structural anomaly in chromosome
21; 2) the RUNX1 gene was separated due to the chromosomal anomaly, which could explain theclinical presentation of FPD; 3) upon leukemogenesis, the 5 region of RUNX1 was amplified several
fold; 4) the breakpoint of RUNX1 was located between exons 3 and 4; and 5) neither additional fusion
gene products nor previously reported additional mutations were observed based on RNA sequencing.
These data suggest amplification of aberrant RUNX1 genes promotes leukemogenesis in patientswith FPD/AML.
Only about half of individuals with FPD/AML develop hematological malignancies over the courseof their life with long latency, suggesting additional genetic events are required for progression to theovert malignant phase3). Yoshimi et al recently found somatic CDC25C mutations in more than halfof patients with FPD/AML in Japan, where the mutated CDC25C disrupted the G2/M checkpoint andpromoted the cell cycle1). A French group reported a high frequency of RUNX1 biallelic mutations
in patients with FPD/AML. Although a variety of mutations have been identified at the AML stage,
CDC25C mutations were not reported in their study9). CDC25C mutations were also not detected ina study on 13 individuals from FPD/AML families from the United States10) suggesting environmental
factors and/or ethnicity may play important roles in leukemic transformation.
Somatic aberrations of RUNX1, including point mutations and chromosomal translocations, often
occur in MDS, AML, and acute lymphocytic leukemia11). Moreover, reverse engineering analysis of
TLX1- and TLX3-mediated T-cell acute lymphocytic leukemia revealed wild-type RUNX1 may serve
as a tumor suppressor and abolish the oncogenic effects of TXL1 and TLX3. The loss of function of
RUNX1 promotes oncogenesis12). On the other hand, Yanagida et al experimentally demonstrated
an increased dose of RUNX1 acts as a positive modulator of myeloid leukemogenesis. These authors
speculated that an extra-copy of RUNX1 through trisomy 21 may be related to Down s syndromerelated acute megakaryoblastic leukemia13). Antony-Debré et al reported that of the nine patientswith FPD/AML who developed acute leukemia, three have a duplication of the RUNX1-mutated or- 118 -

Leukemogenesis in FPD/AML-deleted chromosome14). In our study, we observed a breakage in RUNX1 between exons 3 and 4,
which disrupted the RHD. The truncated RHD abrogates DNA-binding and transactivation capacity,while interfering with the wild-type protein during heterodimerization with CBFβ in a dominantnegative manner 15). Collectively, we speculate the patient in our study manifested FPD due tohaploinsufficiency of RUNX1 and amplification of the truncated RUNX1 may have led to early onsetof AML.
To better manage and treat FPD/AML patients, further understanding of the pathogenesis anddisease progression to hematopoietic malignancies in FPD/AML is required.
References
1. Yoshimi A, Toya T, Nannya Y, Takaoka K, Kirito K, Ito E, et al. Spectrum of clinical and genetic featuresof patients with inherited platelet disorder with suspected predisposition to hematological malignancies: anationwide survey in Japan. Ann Oncol 2016;27:887-895.
2. Sood R, Kamikubo Y, Liu P. Role of RUNX1 in hematological malignancies. Blood 2017;129:2070-2082.
3. Hayashi Y, Harada Y, Huang G, Harada H. Myeloid neoplasms with germ line RUNX1 mutation. Int J
Hematol 2017;106:183-188.
4. Shiba N, Hasegawa D, Park MJ, Murata C, Sato-Otsubo A, Ogawa C, et al. CBL mutation in chronic
myelomonocytic leukemia secondary to familial platelet disorder with propensity to develop acute myeloid
leukemia (FPD/AML). Blood 2012;119:2612-2614.
5. Manchev VT, Bouzid H, Antony-Debre I, Leite B, Meurice G, Droin N, et al. Acquired TET2 mutation in one
patient with familial platelet disorder with predisposition to AML led to the development of pre-leukaemic
clone resulting in T2-ALL and AML-M0. J Cell Mol Med 2017;21:1237-1242.
6. Mangan JK, Speck NA. RUNX1 mutations in clonal myeloid disorders: from conventional cytogenetics to next
generation sequencing, a story 40 years in the making. Crit Rev Oncog 2011;16:77-91.
7. Shimojima K, Komoike Y, Tohyama J, Takahashi S, Paez MT, Nakagawa E, et al. TULIP1 (RALGAPA1)
haploinsufficiency with brain development delay. Genomics 2009;94:414-422.
8. Maher CA, Kumar-Sinha C, Cao X, Kalyana-Sundaram S, Han B, Jing X, et al. Transcriptome sequencing todetect gene fusions in cancer. Nature 2009;458:97-101.
9. Preudhomme C, Renneville A, Bourdon V, Philippe N, Roche-Lestienne C, Boissel N, et al. High frequency of
RUNX1 biallelic alteration in acute myeloid leukemia secondary to familial platelet disorder. Blood 2009;113:
5583-5587.
10. Churpek JE, Pyrtel K, Kanchi KL, Shao J, Koboldt D, Miller CA, et al. Genomic analysis of germ line andsomatic variants in familial myelodysplasia/acute myeloid leukemia. Blood 2015;126:2484-2490.
11. De Braekeleer E, Douet-Guilbert N, Morel F, Le Bris MJ, Ferec C, De Braekeleer M. RUNX1 translocations
and fusion genes in malignant hemopathies. Future Oncol 2011;7:77-91.
12. Della Gatta G, Palomero T, Perez-Garcia A, Ambesi-Impiombato A, Bansal M, Carpenter ZW, et al. Reverse
engineering of TLX oncogenic transcriptional networks identifies RUNX1 as tumor suppressor in T-ALL. Nat
Med 2012;18:436-440.
13. Yanagida M, Osato M, Yamashita N, Liqun H, Jacob B, Wu F, et al. Increased dosage of Runx1/AML1 acts as apositive modulator of myeloid leukemogenesis in BXH2 mice. Oncogene 2005;24:4477-4485.
14. Antony-Debré I, Duployez N, Bucci M, Geffroy S, Micol JB, Renneville A, et al. Somatic mutations associatedwith leukemic progression of familial platelet disorder with predisposition to acute myeloid leukemia.
Leukemia 2016;30:999-1002.
15. Michaud J, Wu F, Osato M, Cottles GM, Yanagida M, Asou N, et al. In vitro analyses of known and novel
RUNX1/AML1 mutations in dominant familial platelet disorder with predisposition to acute myelogenous
leukemia: implications for mechanisms of pathogenesis. Blood 2002;99:1364-1372.

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Osaka City Med. J. Vol. 64, 121-130, 2018

Association between the Left Atrial Emptying Fraction and Silent
Brain Infarction in Patients with Paroxysmal Atrial Fibrillation
YU KAWAI1), KENICHI SUGIOKA1), SHINICHI IWATA1), SHINICHI SAKAMOTO2),
SERA ISHIKAWA1), MASAHIKO TAKAGI1), YUKIO MIKI2), and MINORU YOSHIYAMA1)
Departments of Cardiovascular Medicine1) and Diagnostic and Interventional Radiology2),
Osaka City University Graduate School of Medicine

Abstract
Background
Patients with atrial fibrillation (AF) often show a high prevalence of silent brain infarction (SBI),
which is an independent risk factor for the development of symptomatic stroke. The left atrial
emptying fraction (LAEF) is also known to be associated with an increased risk of symptomatic strokein patients with AF; however, little is known regarding the association between SBI and LAEF inpatients with paroxysmal AF.
Methods
We investigated 77 neurologically asymptomatic patients with paroxysmal AF (56 men, medianage 66 years) who were scheduled to undergo transcatheter pulmonary vein isolation or electrical
cardioversion. All patients underwent brain magnetic resonance imaging to screen for SBI prior to
the scheduled ablation or cardioversion. Comprehensive transthoracic echocardiography was
performed to calculate the LAEF.
Results
SBI was observed in 21 patients (27%). Univariate analysis showed a negative association between
LAEF and SBI [odds ratio (OR) 0.92, 95% confidence interval（CI）0.87-0.98, p＝0.005]. Receiver
operating characteristic curve analysis indicated that the optimal cut-off value for SBI (area under
the curve 0.70) was 45.5% with a sensitivity of 62% and a specificity of 79%. Multivariate logistic
regression analysis indicated that LAEF ＜45.5% remained independently associated with SBI (OR
6.35, 95% CI 1.82-22.1, p＝0.004) after adjusting for the CHA2DS2-VASc score and the estimatedglomerular filtration rate.
Conclusions
An impaired LAEF is associated with SBI in patients with paroxysmal AF and might be a usefulparameter for risk stratification. Intensive intervention in high-risk patients may avoid SBI andreduce the subsequent stroke risk.
Received June 20, 2017; accepted April 17, 2018.
Correspondence to: Yu Kawai, MD.
Department of Cardiovascular Medicine, Osaka City University Graduate School of Medicine,
1-4-3 Asahimachi, Abeno-ku, Osaka 545-8585, Japan
Tel: +81-6-6645-3801; Fax: +81-6-6646-6808
E-mail: yuukawai1122@gmail.com- 121 -

Kawai et al

Key Words: ‌Paroxysmal atrial fibrillation; Silent brain infarction; Echocardiography;
Left atrial emptying fraction

Introduction
Recent studies have focused on silent brain infarction (SBI) that is incidentally detected on brain
magnetic resonance imaging (MRI) in patients with atrial fibrillation (AF)1). In patients presenting
with SBI, most infarcts (80%-90%) are subcortical in location, and this condition is, therefore, classified
as small-vessel occlusive disease or lacunar infarction caused by lipohyalinosis, microatheromas, oremboli2). The remaining (10%-20%) infarcts are cortical or large infarcts that are more likely to besecondary to cardiac embolism2). Because AF is associated with both micro- and macro-embolism3,4),
the American Heart Association/American Stroke Association statement recommends screening for
AF in patients presenting with SBI2). Moreover, SBI is detected in approximately 25% of patientswith AF who report no history of stroke5) and is associated with occurrence of a stroke in future6) or
cognitive decline7) in patients with AF. Therefore, identification of high-risk patients who may benefit
from more intensive interventions is important to provide customized treatment for each patient,which is aimed at prevention of SBI.
Assessment of left atrial (LA) function could be an alternative strategy to facilitate risk stratification
beyond traditional risk factors among AF patients with SBI. Impaired LA function is associated withan increased risk of an LA thrombus or thromboembolism8-12). However, the association between LA
function (i.e., LA emptying function; LAEF) and the presence of SBI has not been addressed by clinicalstudies.
We aimed to assess the relationship between LAEF and the presence of SBI in patients withparoxysmal AF.

Methods
This cross-sectional single center study included 213 consecutive, neurologically asymptomaticpatients with nonvalvular AF who underwent percutaneous pulmonary vein isolation or electrical
cardioversion between 2011 and 2015 at the Osaka City University Hospital. We excluded patients
who had undergone prior pulmonary vein isolation or any valve replacement procedure, those diagnosed
with mitral stenosis, and those without MRI findings because of contraindications or patient s refusal.
We selected 77 patients diagnosed with paroxysmal AF from among the remaining 157 patients.
Paroxysmal AF was diagnosed in patients with a history of AF in whom an electrocardiogram indicatedsinus rhythm when transthoracic echocardiography (TTE) was performed. The study protocol
conformed to the guidelines of the Declaration of Helsinki (Second Revision, 1983) and was approvedby the Ethics Committee of the hospital (approval number: 3214). Written informed consent was
obtained from each patient prior to inclusion in the study.
Clinical variables such as age, body mass index, hypertension, diabetes mellitus, dyslipidemia,
congestive heart failure, vascular disease, smoking status, chronic kidney disease, and information
regarding prior treatment were obtained for each patient. Hypertension was defined as patientreported history of hypertension, a systolic blood pressure ≧140 mm Hg or a diastolic blood pressure≧90 mm Hg upon admission, or treatment with an oral antihypertensive drug13). Diabetes mellitus

was defined as a fasting blood glucose level ≧126 mg/dL, a hemoglobin A1c (HbA1c) level ≧6.5%,
existing diagnosis of diabetes mellitus or the reported use of an oral hypoglycemic drug 14).

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LAEF and SBI in Paroxysmal AF

Dyslipidemia was defined as a serum cholesterol level ≧220 mg/dL or a low-density lipoproteincholesterol level ≧140 mg/dL upon admission or the reported use of a cholesterol-lowering drug15). A
history of vascular disease was defined as the presence of myocardial infarction or peripheral arterydisease. Patients were classified as non-smokers if they had never smoked or if they had stopped
smoking for ≧10 years prior to inclusion in this study. Chronic kidney disease was defined as an
estimated glomerular filtration rate ＜60 mL/min/1.73 m2 (category ≧G3)16,17). We calculated the
CHA2DS2-VASc score using the above information18). Duration of paroxysmal AF and anticoagulation
therapy was determined from the patients reports or medical records and were categorized into 2
groups: duration ＜6 months or ≧6 months.
All enrolled patients underwent 2-dimensional TTE that was performed using commerciallyavailable systems with patients placed in the left lateral decubitus position. Echocardiographic
quantification was performed based on the American Society of Echocardiography guidelines 19). Enddiastolic left ventricular (LV) diameter, end-systolic LV diameter, end-diastolic interventricular septal
thickness, end-diastolic LV posterior wall thickness, and LV ejection fraction were measured. The LV
mass was calculated based on the LV linear dimensions using the following formula: {0.8×1.04×[(end-diastolic LV diameter＋end-diastolic LV posterior wall thickness＋end-diastolic interventricularseptal thickness)3−(end-diastolic LV diameter)3]＋0.6} g and was indexed to the body surface area.
Maximal and minimal LA volumes were measured using the biplane modified Simpson s method
using apical 4- and 2-chamber views. The maximal LA volume was obtained just prior to the openingof the mitral valve, and the minimal LA volume was obtained at the moment of mitral valve closure.
Indexed LA volumes (LAVI) were calculated based on the patient s body surface area. These data
were used to calculate the LAEF using the formula: LAEF＝[(maximal LAVI −minimal LAVI)/
maximal LAVI]×10020) (Fig. 1). Early E and late A transmitral velocities were measured using apulsed-wave Doppler based on the apical 3-chamber view with the sample volume positioned at the
tip of the mitral leaﬂets21).
All MRI examinations were performed using a 3.0-Tesla (T) unit (Achieva Quasar Dual; Philips
Medical Systems, Best, The Netherlands) or a 1.5-T unit (Achieva Nova Dual; Philips Medical
Systems, Best, The Netherlands) with a standard head coil. Axial T1-weighted images (3.0-T unit:
repetition time 400 ms, echo time 15 ms, field of view 220 mm 2, imaging matrix 256×181, 5 mm
thickness and 1 mm gap; 1.5-T unit: repetition time 737 ms, echo time 15 ms, field of view 220 mm2,
imaging matrix 256×180, 5 mm thickness and 1 mm gap) and axial T2-weighted images (3.0-T unit:
repetition time 4000 ms, echo time 90 ms, field of view 220 mm2, imaging matrix 448×300, 5 mm
thickness and 1 mm gap; 1.5-T unit: repetition time 4560 ms, echo time 90 ms, field of view 220 mm2,
imaging matrix 352×272, 5 mm thickness and 1 mm gap) were obtained to evaluate SBI. SBI was
defined as an area of low intensity observed on T1-weighted images and an area of high intensity
observed on T2-weighted images with a diameter ≧3 mm22) (Fig. 2). Lesions that demonstrated ahigh intensity on diffusion images were excluded from the analysis. The presence of SBI was
confirmed by an experienced neuroradiologist (S.S.) who had been blinded to the clinical informationof the patients enrolled in this study.
Statistical methods
Continuous variables were expressed as median values (interquartile ranges), and categoricalvariables as numbers and percentages. The distribution of clinical or echocardiographic variables
was evaluated among patients with SBI versus those without SBI. We compared the groups using- 123 -

Kawai et al

Figure 1. Echocardiographic assessment of left atrial volume using the biplane modified Simpson s method.
A＝maximal left atrial volume using apical 4-chamber view.
B＝minimal left atrial volume using apical 4-chamber view.
C＝maximal left atrial volume using apical 2-chamber view.
D＝minimal left atrial volume using apical 2-chamber view.

the unpaired t test for continuous variables with a normal distribution and the Mann-Whitney U test
for continuous variables with a non-normal distribution. Categorical variables were compared usinga chi-square test or the Fisher exact test (N ≧20). Univariate logistic regression analysis was
performed to identify clinical and echocardiographic variables that were associated with the presenceof SBI. A p value of ＜0.05 (except with regard to age and diabetes mellitus, which were included in
the CHA2DS2-VASc score) was used to select variables that would be subjected to multiple logistic
regression analysis. Moreover, we performed multivariate logistic regression analysis using propensity
score as a covariate to minimize the potential selection bias. Because the cut-off value is useful forrisk stratification in clinical settings, we used LAEF as a binary variable (LAEF ＜45.5% or ≧45.5%),
which is the optimal cut-off value for predicting the presence of SBI (area under the curve 0.70) witha sensitivity of 62% and a specificity of 79% derived from receiver operating characteristic curve
analysis. The covariates in Model 1 included the LAEF and the propensity score derived from thegeneral risk factors for SBI (age, HbA1c, low-density lipoprotein cholesterol, systolic blood pressure,diastolic blood pressure, smoking, and estimated glomerular filtration rate) which had a concordanceindex of 0.70. The covariates in Model 2 included the LAEF and the propensity score derived from- 124 -

LAEF and SBI in Paroxysmal AF

Figure 2. A representative case of silent brain infarction (SBI). This patient shows SBI in the left cerebellar
hemisphere (arrow) concomitant with paroxysmal atrial fibrillation and a decreased left atrial emptying fraction (43%).

the variables associated with the presence of SBI noted using univariate analysis (age, congestive
heart failure, hemoglobin, estimated glomerular filtration rate, antiplatelet drug usage, andangiotensin-converting enzyme inhibitor/angiotensin Ⅱ receptor blocker usage) which had aconcordance index of 0.72. We also used inverse probability of treatment weighting method in these 2models to confirm our results. We used dummy variables for analyses as following; 1 ＝male, 0＝
female; 1＝smoker, 0＝non-smoker; 1＝duration of atrial fibrillation ≧6 months, 0＝duration of atrial
fibrillation ＜6 months; 1＝duration of anticoagulant usage ＜6 months, 0＝duration of anticoagulant
usage ≧6 months; 1 ＝LAEF ＜45.5%, 0 ＝LAEF ≧45.5%; other clinical variables and usage of
medications: 1＝presence, 0＝absence. p values ＜0.05 were considered statistically significant. All
statistical analyses were carried out using SPSS version 24 (IBM Corp., Armonk, NY, USA).

Results
Among the 77 patients diagnosed with paroxysmal AF, SBI was observed in 21 (27%). Amongthese 21 patients, subcortical and small (3-15 mm) infarcts were detected in 15, cortical or large
infarcts in 14, and both varieties in 8. Baseline clinical characteristics of patients with and without
SBI are shown in Table 1. All patients had been administered anticoagulants. Age, diabetes mellitus,
congestive heart failure, chronic kidney disease, the CHA2DS2-VASc score, and use of antiplatelet
agents and angiotensin-converting enzyme inhibitor/angiotensin Ⅱ receptor blockers were variables
that were observed to be positively associated with the presence of SBI. Hemoglobin and estimatedglomerular filtration rate were variables that were negatively associated with the presence of SBI.
Echocardiographic characteristics of patients with and without SBI are shown in Table 2. LAEF was
negatively associated with the presence of SBI, whereas the other variables including the LV ejection
fraction, LV mass index, maximal LAVI, and mitral E velocity were not associated with the presence- 125 -

Kawai et al
Table 1. Baseline clinical characteristics of patients with and without silent brain infarction

Age, years
Males, n (%)
Body mass index, kg/m2
Hypertension, n (%)
Systolic blood pressure, mm Hg
Diastolic blood pressure, mm Hg
Diabetes mellitus, n (%)
Smoker, n (%)
Dyslipidemia, n (%)
Congestive heart failure, n (%)
Duration of atrial fibrillation (≧6 months), n (%)
Duration of anticoagulant usage (＜6 months), n (%)
Hemoglobin A1c, %Total cholesterol, mg/dL
High-density lipoprotein cholesterol, mg/dL
Low-density lipoprotein cholesterol, mg/dL
Triglycerides, mg/dL
Albumin, g/dL
Hemoglobin, g/dL
C-reactive protein, mg/dL
eGFR, mL/min/1.73m2
Chronic kidney disease, n (%)
CHA2DS2-VASc score
Medications
Antiplatelet agents, n (%)
Anticoagulants, n (%)
Vitamin K antagonists, n (%)
Direct oral anticoagulants, n (%)
Antiarrhythmic agents, n (%)
Statins, n (%)
ACEI/ARB, n (%)
Calcium channel blockers, n (%)β-blocker, n (%)
Antidiabetic medication, n (%)

SBI (＋)(N＝21)

SBI (−)(N＝56)

p

68 (66-74)
16 (76)65 (54-70)
40 (71)

0.01
0.68

25 (23-27)
16 (76)126 (120-136)
71 (69-78)
8 (38)
7 (33)
6 (29)

24 (22-27)
31 (55)130 (113-135)
76 (69-80)
9 (16)
20 (36)22 (39)

0.18
0.10
0.97
0.24
0.04
0.85
0.38

6 (29)
11 (52)1 (2)41 (73)

0.001
0.08

8 (30)
5.8 (5.7-6.2)
167 (157-197)
41 (37-46)
101 (85-122)

28 (50)5.7 (5.5-6.0)
176 (159-188)
43 (39-53)

0.35
0.05
0.90
0.14

135 (106-176)
4.2 (4.2-4.3)
13.6 (12.9-14.9)
0.09 (0.05-0.11)

102 (89-118)
117 (85-153)
4.3 (4.1-4.5)
14.5 (13.7-15.1)
0.08 (0.02-0.14)

0.98
0.23
0.22
0.04
0.31

60 (48-73)
10 (48)70 (62-82)
12 (21)

0.004
0.02

3.0 (2.0-4.0)

1.5 (1.0-2.3)

0.003

3 (14)
21 (100)
7 (33)
14 (67)
13 (62)6 (29)
29 (38)8 (38)
9 (43)
6 (29)0 (0)56 (100)
11 (20)45 (80)34 (61)
15 (27)12 (16)15 (27)15 (27)
6 (11)

0.02
0.17
0.17
0.92
0.88
0.001
0.33
0.18
0.06

Continuous variables were expressed as median values (interquartile ranges), and categorical variables as numbers
and percentages. SBI, silent brain infarction; eGFR, estimated glomerular filtration rate; ACEI, angiotensinconverting enzyme inhibitor; and ARB, angiotensin Ⅱ receptor blocker.

of SBI. Table 3 shows the clinical and echocardiographic variables associated with the presence of
SBI and their OR obtained using univariate and multivariate analysis. LAEF (as a continuous
variable) was inversely associated with the presence of SBI after adjusting for the CHA2DS2-VASc
score and the estimated glomerular filtration rate (OR 0.92, 95% CI 0.86-0.98, p＝0.007). Moreover,
the CHA2DS2-VASc score (OR 1.94, 95% CI 1.11-3.40, p＝0.02) and the LAEF ＜45.5% (OR 6.35, 95%
CI 1.82-22.13, p＝0.004), which is the optimal cut-off value for predicting the presence of SBI (areaunder the curve 0.70) with a sensitivity of 62% and a specificity of 79% derived from receiver
operating characteristic curve analysis, remained independently associated with the presence of SBI
after adjusting for the estimated glomerular filtration rate. Furthermore, LAEF ＜45.5% (a binary- 126 -

LAEF and SBI in Paroxysmal AF
Table 2. Echocardiographic findings in patients with and without silent brain infarction
SBI (＋)(N＝21)

SBI (−)(N＝56)

p

End-diastolic left ventricular diameter, mm
End-systolic left ventricular diameter, mm
Interventricular septal thickness, mm
Posterior wall thickness, mm
Left atrial diameter, mm
Left ventricular ejection fraction, %Mitral E velocity, cm/s

49 (43-55)
30 (26-35)
9 (9-10)9 (8-10)41 (38-46)
60 (55-60)
65 (48-77)

47 (44-49)
28 (26-31)
9 (8-10)9 (8-10)39 (34-43)
60 (60-60)

0.37
0.21
0.09
0.45
0.07
0.08

Mitral A velocity, cm/s
Mitral E deceleration time, ms
Left ventricular mass index, g/m2

63 (44-75)
246 (229-275)

60 (55-66)
63 (48-80)
225 (190-255)

0.63
0.87
0.63

103 (93-125)
36 (29-45)
43 (36-56)

98 (89-115)
35 (27-41)
53 (47-60)

0.10
0.15
0.002

Maximal left atrial volume index, mL/m2
Left atrial emptying fraction, %Continuous variables were expressed as median values (interquartile ranges), and categorical variables as numbers
and percentages. SBI, silent brain infarct.

Table 3. Clinical and echocardiographic variables associated with silent brain infarction
Univariate analysis

Multivariate analysis

OR (95% CI)p

OR (95% CI)

pAge, per 1year
Male sex
Diabetes mellitus
Hypertension
Dyslipidemia
Smoking
Estimated glomerular filtration rate, per 1 mL/min/1.73m2
Chronic kidney disease
Duration of anticoagulant use ＜6 months

1.08 (1.01-1.15)
1.28 (0.40-4.08)
3.21 (1.04-9.98)
2.58 (0.83-8.02)
0.62 (0.21-1.83)
0.90 (0.31-2.60)
0.95 (0.92-0.99)
3.33 (1.15-9.70)

0.08
0.68
0.04
0.10
0.38
0.85
0.01
0.03

0.98 (0.94-1.02)

0.23

0.62 (0.22-1.72)

0.35

Duration of atrial fibrillation ≧6 months

0.40 (0.14-1.14)
2.02 (1.27-3.20)

0.09
0.003

1.94 (1.11-3.40)

0.02

1.02 (1.00-1.05)

0.10

CHA2DS2-VASc score, per 1point
Left ventricular mass index, per 1 g/m2
Maximal left atrial volume index, per 1 mL/m2

1.03 (0.99-1.06)
0.15
0.92 (0.87-0.98)
0.005
5.96 (2.01-17.68) 0.001

Left atrial emptying fraction, per 1%
Left atrial emptying fraction ＜45.5%

6.35 (1.82-22.13) 0.004

OR, odds ratio; and CI, confidence interval.

variable) remained independently associated with the presence of SBI using propensity scores (Table4). Finally, we confirmed the significant association between LAEF ＜45.5% and the presence of SBI
using inverse probability of treatment weighting method (model 1; OR 5.26, 95% CI 1.64-16.91, p＝0.005, model 2; OR 3.75, 95% CI 1.15-12.21, p＝0.03).

Discussion
In the present study, we observed that an impaired LAEF was significantly associated with thepresence of SBI in patients with paroxysmal AF after adjusting for accepted risk factors or the
CHA 2DS2-VASc score and the estimated glomerular filtration rate. These results suggest that an- 127 -

Kawai et al
Table 4. Multivariate logistic regression analysis for silent brain infarction: Propensity score adjustment
Model 1LAEF ＜45.5%

Model 2OR (95% CI)p

OR (95% CI)p6.08 (1.89-19.60)

0.003

3.88 (1.20-12.61)

0.024

Model 1 adjusts for the propensity score derived from the general risk factors of silent brain infarction (age,hemoglobin A1c, low-density lipoprotein cholesterol, systolic blood pressure, diastolic blood pressure, smoking, andestimated glomerular filtration rate). Model 2 adjusts for the propensity score derived from variables associated withsilent brain infarction noted using univariate analysis (age, congestive heart failure, hemoglobin, estimated glomerular
filtration rate, antiplatelet drug usage, and angiotensin-converting enzyme inhibitor/angiotensin Ⅱ receptor blocker
usage). OR, odds ratio; CI, confidence interval; and LAEF, left atrial emptying fraction.

impaired LAEF may be associated with microthrombus formation, which is a risk factor for thepresence of SBI in patients with paroxysmal AF. To our knowledge, this is the first study todemonstrate that LAEF (calculated using TTE) is associated with the presence of SBI in patientswith paroxysmal AF.
Our study showed that LAEF was statistically significantly associated with the presence of SBI ―a finding that is in agreement with that of previous studies showing that the LA function plays animportant role in predicting SBI. The Cardiovascular Abnormalities and Brain Lesions (CABL) study
showed that LAEF assessed using echocardiography was significantly associated with the presence of
SBI in the general population without a history of stroke23). However, this study primarily focused on
patients with a sinus rhythm. To date, no study has investigated the influence of LAEF on thepresence of SBI in patients with paroxysmal AF.
Our study revealed that LAEF is associated with the presence of SBI in patients with paroxysmal
AF. Based on our results, we hypothesized that an impaired LAEF plays an important role in the
progression of thrombogenesis in the LA with the subsequent development of SBI in patients withparoxysmal AF. The mechanisms underlying our finding remain unclear. There is, however, considerable
evidence to explain the role of impaired LAEF in the process of thrombogenesis. Impaired LAEF has
been proven to be associated with the presence of an LA thrombus, which leads to the development ofa symptomatic stroke in patients with AF11). Similarly, an impaired LAEF is known to be associatedwith spontaneous echo contrast, which is a risk factor for cerebral microembolism in patients with AF11).
Moreover, LAEF is associated with the CHA2DS2-VASc score12), which is a well-accepted tool for risk
stratification with regard to thrombogenesis or symptomatic stroke in patients with AF. Although we
focused only on paroxysmal AF, LAEF itself may accelerate LA thrombogenesis and cause subsequent
SBI even in patients with paroxysmal AF.
A few studies have reported that LAVI was shown to be associated with the presence of SBI inpatients with AF 8-10); however, our study showed no association between LAVI and SBI in patientswith paroxysmal AF. This difference might be at least partly attributable to the differences in study
cohorts (studies that investigated any type of AF vs our study that investigated only paroxysmal AF).
Impaired LAEF is known to be an earlier stage of abnormality than that noted in LA enlargement24).
Paroxysmal AF may indicate a shorter history of AF; thus, LAEF may be a better predictor than LAVI
to predict the presence of SBI in patients with paroxysmal AF.
Limitations
Limitations of our study: 1) Our study included a relatively small number of patients. Thus, future- 128 -

LAEF and SBI in Paroxysmal AF

studies including a larger number of patients are necessary to confirm whether LAEF is significantly
associated with the presence of SBI. 2) Because cross-sectional data cannot investigate causality, aprospective study would be necessary to establish whether LAEF can conclusively predict the presenceof SBI. 3) Because our study population comprised patients scheduled for transcatheter pulmonaryvein isolation or electrical cardioversion, a selection bias might have inﬂuenced our study results. 4)
Because it is difficult to ascertain the mechanisms of SBI (particularly in patients presenting withlacunar infarction), there exists the possibility that our study also included non-embolic causes of
SBI. 5) Although a 1.5-T MRI is an acceptable modality for the assessment of SBI, the detection rateof SBI may be different between 1.5-T and 3.0-T MRI testing25). 6) This study did not evaluate the LAparameters using novel methods such as a 3-dimensional echocardiographic method26) or the speckle
tracking method27).
Conclusions
Impaired LAEF is associated with the presence of SBI in patients with paroxysmal AF, and LAEF
might be a useful parameter for risk stratification of thromboembolism in patients presenting withparoxysmal AF.
Sources of funding
This study was partly supported by the Grants-in-Aid for Scientific Research (No. 25461087) fromthe Japan Society for the Promotion of Science, Tokyo, Japan.
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Osaka City Med. J. Vol. 64, 131-142, 2018

A Non-clinical Experimental Study of the Ligation Processwith Knot Pushers
SHINSUKE NISHIMURA1), MASAKI NISHIMURA2), MITSUHARU HOSONO1),
TAKASHI MURAKAMI1), YOSUKE TAKAHASHI1), TAKAHIRO KITAGAWA2),
SEIICHI YASUKI2), SHUNSUKE KITA2), and TOSHIHIKO SHIBATA1)
Department of Cardiovascular Surgery1), Osaka City University Graduate School of Medicine; andOsaka Research Institute of Industrial Science and Technology2)

Abstract
Background
There have been no quantitative evaluations of the ligation process with knot pushers. The
purpose of this study is to evaluate the traction method of the suture, the differences between suturetypes, and the inﬂuence of water addition.
Methods
Three types of sutures were employed: Suture-A (braided polyester), Suture-B (braided silk), andSuture-C (monofilament polyvinylidene difluoride). The pushing force of the knot pusher wasmeasured. The tension force was achieved with weights. The pushing force was evaluated in six
weight conditions termed Group (100-100), Group (200-200), Group (300-300), Group (200-100),
Group (300-100), and Group (300-200). We compared the pushing force in dry and wet conditions.
Results
The pushing force was 114±1 gf for Group (100-100), 328±5 gf for Group (200-200), 478±2 gf forGroup (300-300), 109±1 gf for Group (200-100), 100±3 gf for Group (300-100), and 231±3 gf for Group(300-200). The pushing force with Suture-A, -B, and -C was 104±1, 112±2, and 97±1 gf, respectively(p＜0.0001). There was no significant difference in the pushing force between dry and wet conditionsin Suture-A and Suture-C, while the pushing force was significantly larger in the wet condition with
Suture-B.
Conclusions
When surgeons perform knot pusher ligation, it is important to push down the suture beside theknot and not to pull the loop side suture too much. It was shown that addition of water did not
significantly affect the pushing force for hydrophobic sutures.
Key Words: ‌Ligation technique; Knot pusher; Pushing force

Received December 20, 2017; accepted April 17, 2018.
Correspondence to: Shinsuke Nishimura, MD.
Department of Cardiovascular Surgery, Osaka City University Graduate School of Medicine,
1-4-3 Asahimachi, Abeno-ku, Osaka 545-8585, Japan
Tel: +81-6-6645-3980; Fax: +81-6-6646-3071
E-mail: s.nishimura0710@gmail.com- 131 -

Nishimura et al

Introduction
The number of minimally invasive cardiac surgeries (MICS) has been increasing in recent years1-5).
The deep operation site in conjunction with the small skin incision make it difficult to perform
manual ligation, so we have to use ligature instruments like knot pushers. However, there aretechnical differences between manual ligation and knot pusher ligation6). In knot pusher ligation, thesliding knot technique is a common method used for deep site ligation7).
Usually, knot pusher ligation requires working with an assistant. The operator holds the knot
pusher with one hand and grabs one side of the suture with the other hand while an assistant grabs
the other side of the suture. The operator makes a half hitch and then pushes down the knot to theseating position. We sometimes feel that the knot is not advanced smoothly to the seating position,
and we know that the resistance for pushing down the knot depends on the type of suture.
We empirically know the surgeon s actions such as changing the pushing direction of the knot
pusher, adjusting the traction force, or adding water to the hands and sutures affect the ligation
process. While several studies have reported the knot strength and knot security, there have been noquantitative evaluations of the ligation process with a knot pusher 8-18). In this study, we made aligation-simulating model to quantitatively reveal the ligation process with a knot pusher and carriedout non-clinical engineering experiments. We evaluated the pushing force that was important toperform stressless ligation without applying useless force in actual operations.

Methods
Knot pusher and suture
There are a variety of knot pushers manufactured with different materials and shapes19). In ourstudy, a Geister knot pusher (ValveGate® 34-7495, Tuttligen, Germany) was used. There are two
ways to use this knot pusher in terms of contact with the suture (Fig. 1), and we used the knot pusher
as shown in Figure 1A.
We employed three commercially available non-absorbable surgical sutures used in cardiovascularsurgery in Japan (Table 1). Cardiac surgeons usually use 2-0 braided sutures for fixing an annuloplasty
ring, and 4-0 monofilament sutures for closing the atrium. Thus we selected the size of the sutures
according to the clinical usage. Two of the sutures were braided (Suture-A and -B) and the third wasa monofilament suture (Suture-C). Suture-A is Teffdesser Ⅱ® (CROWNJUN, Tokyo, Japan), Suture-B

Figure 1. A and B, Tip shape of the knot pusher. There are two ways for the knot pusher to contact the suture.

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Study of the Ligation Process with Knot Pushers
Table 1. Sutures used in this experimentA
B
C

Trade name

Type

Material

USP size

Teffdesser Ⅱ
Braided silk
Asﬂex

Braided Suture
Braided Suture
Monofilament Suture

Polyester coated with PTFE
Silk
Polyvinylidene diﬂuoride

2-0
2-0
4-0

USP, United States Pharmacopeia; and PTFE, polytetraﬂuoroethylene.

Figure 2. Schema of the experimental apparatus. The knot pusher was connected to the load cell and the suture was
fixed to the seating point. Constant tension force was applied via pulleys with weights on each side. Two apparatus
settings were tested: the central position setting (A), and the side position setting (B).

is Braided silk® (CROWNJUN, Tokyo, Japan), and Suture-C is Asﬂex® (CROWNJUN, Tokyo, Japan).
The sizes of the sutures were 2-0 or 4-0 in United States Pharmacopeia (USP).
Experimental apparatus
The schematic illustration of the experimental apparatus created for this study is shown in Figure
2. The general material testing machine (AG-10kNG, SHIMADZU CORPORATION, Kyoto, Japan)
was used for the ligation model apparatus. The knot pusher was connected to a jig that was fixed to
the load cell, which is a sensor that detects force and converts it to an electrical signal. A pedestal
was put in the basement of the apparatus, and a seating point was created on the pedestal with ahook. The suture for the test was fixed to the hook with manual ligation. A sliding knot was formed
with the suture. In other words, the left side of the suture was set as the suture axis and a half hitch
was made with the right side of the suture. The knot pusher tip was then put on the loop side of thesuture in a neutral position. Weight was fixed to each edge of the suture via pulleys to provide
constant tension force.
The distance between the two pulleys was 50 mm to simulate the small chest incision made in- 133 -

Nishimura et al

MICS. The depth from the starting point of the knot pusher tip to the seating point was 160 mm.
The seating point made with the hook could be moved horizontally by shifting the pedestal. We
tested two apparatus settings: the central position setting in which the seating point was set justbelow the knot pusher (Fig. 2A), and the side position setting in which the seating point was
positioned laterally 10 mm to the left of the knot pusher line (Fig. 2B). In the central position setting
we assumed that the knot pusher pushed down on the knot itself, while in the side position setting
we assumed the knot pusher pushed down on the loop side of the suture beside the knot.
The knot pusher was connected to the load cell and was lowered toward the seating point at aconstant speed of 10 mm/s. During the ligation process the pushing force was measured every 0.05 s
by the load cell. The graph indicates the pushing force on the vertical axis and the pushing depth on
the horizontal axis (Fig. 3). The pushing force was slightly elevated as the knot pusher was lowered,and the force was relatively constant from 30 mm to 120 mm in depth. Therefore, we evaluated thepushing force at the middle point (75 mm in depth) in the test. Fluctuations in the pushing force are
related to the smoothness of the ligation process.
Experimental conditions
Before starting the experiment, we measured the traction force applied to the axis of the suture by
five cardiovascular surgeons using the manual sliding knot technique. The traction force wasmeasured using a digital force gauge (ZP-20N, IMADA, Toyohashi, Japan). The traction force applied
to the axis of the suture ranged from100-250 gf. Therefore, we used weights of 100, 200, and 300 gf
in our experiments.
The group was named according to the weights applied on the axis and loop sides of the suture.
Group (200-100) indicates the axis side suture was connected to the 200 gf weight, and the loop sidesuture was connected to the 100 gf weight. We evaluated the pushing force in three even weight

Figure 3. This graph is a typical example of the relationship between the pushing depth and the detected pushingforce. We evaluated the pushing force at a pushing depth of 75 mm, and we evaluated the stability of the ligation
process by the amplitude of the ﬂuctuation of the line from a pushing depth of 30 mm to 120 mm.

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Study of the Ligation Process with Knot Pushers

conditions termed Group (100-100), Group (200-200), and Group (300-300), and in three unevenweight conditions termed Group (200-100), Group (300-100), and Group (300-200).
Experiment 1
We used Suture-A and applied various weights in the central position setting.
Experiment 2
We used Suture-A with various weight conditions to evaluate the effect of the pushing position on
the pushing force. There are two ways for advancing the knot in the ligation process; the knot pusher
pushes the knot itself or pushes the suture beside the knot. To simulate the former method, we
adopted the central position setting (Fig. 2A), and to simulate latter method we adopted the side
position setting (Fig. 2B). We compared the pushing force in both settings.
Experiment 3
We compared the pushing force using Suture-A, Suture-B, and Suture-C. Experiment 3 was
performed under the side position setting using weight condition Group (200-100).
Experiment 4
We compared the pushing force in dry and wet conditions. Distilled water was supplied to theknot pusher tip with a constant ﬂow of 5 mL/min using a syringe pump to produce the wet condition(Fig. 4). Experiment 4 was done under the side position setting using weight condition Group (200100).
Statistical analysis
We performed the ligation tests five times with the same suture for each condition, and each time

Figure 4. Experimental setup for producing wet conditions. Distilled water was dripped on the knot pusher tip at a
rate of 5 mL/min to evaluate the effect of the wet condition.

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Nishimura et al

we measured the pushing force as mentioned above. The pushing force was expressed as the average±standard deviation.

Statistical analysis was performed with one-way analysis of variance(ANOVA). Dunnett s test and Tukey s multiple range tests were performed with analysis for multigroups. Dunnett s test was performed in experiments 1 and 2 to compare each weight Group. Tukey s
multiple range test was used to compare each suture in experiment 3. Student s t-test was used tocompare results of the same weight Group in different apparatus settings and the results of dry andwet conditions.

Results
Experiment 1
In even weight conditions, the knot pusher kept pushing the knot itself to the seating point (Fig.
5A). However, in the uneven weight conditions, the knot was displaced to the heavier weight side,consequently the knot pusher kept pushing beside the knot (Fig. 5A).
The average pushing force in each weight group is shown in Figure 6A. In even weight conditions,the pushing force at the middle depth (75 mm) was 114±1 gf in Group (100-100), 328±6 gf in Group(200-200), and 478±2 gf in Group (300-300). In uneven weight conditions, the pushing force was 109±1 gf in Group (200-100), 100±3 gf in Group (300-100), and 231±3 gf in Group (300-200). There

were significant differences between Group (200-100) and the other groups (p＜0.0001) (Fig. 6A).
Experiment 2
In the side position setting, we assumed that the knot pusher would continue to push beside theknot. However, in the even weight conditions, the knot pusher kept pushing the knot itself because
the point of intersection was shifted to the center to balance both side weights. In the uneven weight
conditions, the knot pusher kept pushing down beside the knot like in the central position (Fig. 5B).
The pushing force resulted from the side position setting is shown in Figure 6B. In even weight
conditions, the pushing force was 109±1 gf in Group (100-100), 257±8 gf in Group (200-200), and 482

Figure 5. A, Central position setting. In the even weight setting (X＝Y), the knot was located just beneath the knot
pusher tip. In the uneven weight setting (X＞Y), the knot was displaced to the heavier left side (arrow). B, Side position
setting. In the even weight setting (X＝Y), the knot was located just under the knot pusher tip (arrow). In the unevenweight setting (X＞Y), the knot pusher pushed down the side of the knot the same way as in the central position.

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Study of the Ligation Process with Knot Pushers

Figure 6. The bar graph shows the average pushing force at a depth of 75 mm for each weight setting with Suture-A.
A, Results of tests in the central position setting. There were significant differences between Group (200-100) and theother groups (p＜0.0001). B, Results of tests in the side position setting. There were significant differences between
Group (200-100) and all other groups except Group (300-100). NS, not significant; §p＜0.001 vs Group(200-100), ¶p＜0.0001 vs Group (200-100).

Table 2. Pushing force of central position and side position with Suture A
Weight condition

Pushing force (gf)Side position

114±1
328±6

109±1

＜0.0001

Group (200-200)257±7＜0.0001

Group (300-300)

478±2

482±5

0.0692

Group (200-100)

109±1
100±1

101±1

0.0003

Group (300-100)

99±1

0.795

Group (300-200)

231±3

225±4

0.0045

Group (100-100)
Equal weight

Unequal weightp value

Central position(mean±standard deviation)±5 gf in Group (300-300). In uneven weight settings, the pushing force was 101±1 gf in Group (200-100), 99±1 gf in Group (300-100), and 225±4 gf in Group (300-200). In the side position setting,there were significant differences between Group (200-100) and the other groups except Group (300100), Group (200-100) vs Group (300-100): p＝0.99, Group (200-100) vs Group (100-100): p＝0.0086,
Group (200-100) vs the other groups: p＜0.0001.
Comparing the pushing forces measured in the central position setting and side position setting inthe same weight group, they were not significantly different for Group (300-300) and Group (300-100),and in the other groups, the pushing forces of the side position setting were significantly smaller(Table 2).

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Nishimura et al

Experiment 3
The pushing force was 104 ±1 gf with Suture-A, 112 ±2 gf with Suture-B, and 97 ±1 gf with
Suture-C (Figs. 7A and 7B). There were significant differences in pushing force among all the sutures(Suture-A vs Suture-B: p＜0.0001, Suture-A vs Suture-C: p＜0.0001, Suture-B vs Suture-C: p＜0.0001)(Fig. 7B). The ﬂuctuation of the line graph seemed to be larger with Suture-B than the other two
sutures (Fig. 7A).
Experiment 4
The pushing force of Suture-A was 104 ±1 gf in the dry condition and 104 ±1 gf in the wet
condition (Fig. 8A). The pushing force of Suture-B was 112±2 gf in the dry condition and 122±1 gf in
the wet condition (Fig. 8B). The pushing force of Suture-C was 97±1 gf in the dry condition and 96±
2 gf in the wet condition (Fig. 8C). There were no significant differences between the dry and wet
conditions with Suture-A and Suture-C. The pushing force was significantly larger in the wet
condition with Suture-B (p ＜0.0001) (Fig. 8D). Judging from the waveform of the graph, theﬂuctuation of the pushing force with Suture-B was much larger than those of the other sutures (Fig.
8B).

Figure 7. A, Typical line graphs of the relationship between the pushing force and pushing depth for Suture-A,-B, and -C. The amplitude of the ﬂuctuation of the line in Suture-B was larger than those of the other sutures. B,
Average pushing force for Suture-A, -B, and -C. There were significant differences between all sutures. ¶p＜0.0001.

Discussion
In this study, we examined the ligation processes using a knot pusher with a ligation model. We
assessed the ligation process experimentally because surgeons frequently perform ligations
sensuously or empirically during operations.
It was quantitatively shown that a smaller traction force on the loop side of the suture decreased
the pushing force of the knot pusher. Pushing the suture beside the knot with a knot pusher led to asmaller pushing force than when the knot pusher pushed the knot itself. Finally, the addition of- 138 -

Study of the Ligation Process with Knot Pushers

Figure 8. The typical relationship between the pushing force and pushing depth when water was added to eachsuture. A, Suture-A; B, Suture-B; and C, Suture-C. D, Average pushing force for each suture in dry and wet
conditions. In Suture-A and -C, the lines were similar between dry and wet conditions. In Suture-B, the ﬂuctuation of
the line in the wet condition was larger than in the dry condition. The pushing force of Suture-B in the wet condition
was significantly larger than in the dry condition. NS, not significant; ¶p＜0.0001.

water, which is conventionally performed in the ligation process, had no significant effect on thepushing force when we used hydrophobic sutures with knot pushers.
Experimental apparatus
Because the endoscopic surgery and robotic surgery have been developed, there are some reports
about the mechanical strength of some knots, like Roeder Knot and Weston Knot13-16)． However, there
have been no reports about the assessment of ligation processes with a knot pusher. Although we
needed to simulate the ligation process, no ready-made apparatus existed. Therefore we establishedan original examination apparatus to investigate the pushing force with a knot pusher. In the clinicalsetting, surgeons can control the direction in which the knot pusher is advanced. Our experimental
apparatus simulated only vertical movement of the knot pusher, thus this apparatus was not able tofully simulate the ligation procedure as performed by a surgeon. However, we thought this model
would be appropriate for simulating the knot pusher ligation in cardiovascular surgery because theknot pushers can only be pushed in limited directions during deep site surgeries such as mitral valve
surgery.
Experiment 1
We first evaluated the pushing force and checked the movement of the sutures with all weight
settings in the central position setting. We assumed that the knot pusher would continue pushing
the knot to the seating point, and this was true in the even weight conditions. However, in the- 139 -

Nishimura et al

uneven weight conditions, the knot was displaced to the side of the axis suture with the heavier
weight to remain balanced. This caused the knot pusher to continue pushing the suture beside theknot, and not the knot itself (Fig. 5A).
The pushing force of Group (200-100) was significantly smaller than that of Group (100-100) (p＜0.0001), and the pushing force of Group (300-200) was much smaller than that of Group (200-200).
Therefore it was suggested that the total amount of weight was not the only condition that affected
the pushing force. The pushing force of Group (300-100) was significantly smaller than that of Group(200-100) (p ＜0.0001), which indicated that as the left side weight increased, the pushing force
decreased to keep the axis suture tight. The pushing force of Group (300-100) was much smaller thanthat of Group (300-200), as shown in Figure 6A. This suggests that as the weight of the loop sidesuture increased, the pushing force of the knot pusher increased as well.
From the findings of the experiment 1, it was shown that the pushing force in the uneven weight
condition was smaller than that in the even weight condition, and the traction force on both sides ofthe suture affected the pushing force. Increasing the weight on the axis suture made the pushingforce smaller and increasing the weight on the loop side of the suture made the pushing force larger.
Experiment 2
Comparing the pushing forces of the central position setting and side position setting using thesame weight groups, the pushing forces of the side position setting were smaller than those of thecentral position setting except for Group (300-100) (Table 2). From the findings of experiment 2, it
was found that pushing beside the knot decreased the pushing force.
There was no significant difference between the pushing force of Group (200-100) and Group (300100) in the side position setting (p＝0.99), though there was a significant difference in the central
position setting. It was shown that pushing beside the knot reduced the inﬂuence of the axis sideweight. Since the traction force of the axis suture has a deep relation to the traction force of thetissue at the seating point in the surgery, a smaller traction force of the axis suture helps prevent
injuries to the tissue.
To perform a safer ligation with the knot pusher, it is important to keep in mind which suture is
the axis suture and not to tug the loop side suture too much.
Based on the results of experiments 1 and 2, we performed experiments 3 and 4 in the side
position setting with the weight condition Group (200-100), because this setting provided a stablecondition for pushing down the knot.
Experiment 3
Each suture applied in the experiment 3 has different characteristics (Table 1). The pushing forceof Suture-C was the smallest and that of Suture-B was largest. There were significant differencesamong each suture (Fig. 7B). Suture-C is size 4-0 in USP, so the diameter is different from the othertwo. The diameter of Suture-C possibly affected the pushing force. The amplitude of the pushingforce fluctuation from 30-120 mm pushing depth with Suture-B seemed to be larger, as shown in
Figure 7A.
Experiment 4
In clinical situations, we often add water to the hands when we perform manual ligation to reduce
the friction force between the suture and the rubber gloves. We made a system using a syringe pumpto ensure that the tip of the knot pusher was always kept wet with distilled water (Fig. 4).
There was no significant difference in the pushing force between the dry and wet conditions with- 140 -

Study of the Ligation Process with Knot Pushers

Suture-A and Suture-C (Fig. 8D). The water addition may have had no effect on the pushing force of
these sutures because they are made of hydrophobic materials.
In Suture-B, which is hydrophilic, the pushing force in the wet condition was significantly larger
and the amplitude of the pushing force ﬂuctuation was also noticeably larger than that in the dry
condition (Fig. 8B). Although we could not detect the friction force directly with our experimental
apparatus, it was inferred that the friction force increased when water was added to the hydrophilic
suture.
Addition of water had no effect on the pushing force when we used a smooth head knot pusher andhydrophobic sutures like Suture-A and Suture-C. The purpose of this experiment was to reveal theeffect of water addition on the relationship between the knot pusher and sutures. Therefore, we donot mention the effect of water addition on the relationship between the surgeon s hands with rubber
gloves and the sutures during the manual ligation.
Limitations of this study
In this study, the knot pusher pushed down the loop side suture toward the seating point. The
usage of the knot pusher depends on the operator, and some knot pushers are used differently, likethe knot pusher shown in Figure 1B. Other settings are available with this experimental apparatus;
for example, the knot pusher can be pushed down to the seating point along the axis suture bychanging the settings. However, this effect was not studied in the current work. Additionally, it wasdifficult to evaluate the amplitude of the ﬂuctuations numerically, so we evaluated them visually on
the figures. This calculation can be made more precisely in future studies.
References
1. Goldstone AB, Atluri P, Szeto WY, Trubelja A, Howard JL, MacArthur JW Jr, et al. Minimally invasive
approach provides at least equivalent results for surgical correction of mitral regurgitation: a propensitymatched comparison. J Thorac Cardiovasc Surg 2013;145:748-756.
2. Cosgrove DM 3rd, Sabik JF. Minimally invasive approach for aortic valve operations. Ann Thorac Surg
1996;62:596-597.
3. Gillinov AM, Banbury MK, Cosgrove DM. Hemisternotomy approach for aortic and mitral valve surgery. J
Card Surg 2000;15:15-20.
4. Kim BS, Soltesz EG, Cohn LH. Minimally invasive approaches to aortic valve surgery: Brigham experience.
Semin Thorac Cardiovasc Surg 2006;18:148-153.
5. Shibata T. Loop technique for mitral valve repair. Gen Thorac Cardiovasc Surg 2014;62:71-77.
6. Taylor FW. Surgical knots. Ann Surg 1938;107:458-468.
7. Bo W, Fusheng J, Tianyou W. A novel ligation technique facilitating minithoracotomy. Ann Thorac Surg
2009;88:1989-1992.
8. Haxton H. The inﬂuence of suture materials and methods on the healing of abdominal wounds. BR J Surg
1965;52:372-375.
9. Trimbos JB. Security of various knots commonly used in surgical practice. Obstet Gynecol 1984;64:274-280.
10. Batra EK, Taylor PT, Franz DA, Towler MA, Edlich RF. A portable tensiometer for assessing surgeon s knot
tying technique. Gynecol Oncol 1993;48:114-118.
11. Dinsmore RC. Understanding surgical knot security: a proposal to standardize the literature. J Am Coll Surg
1995;180:689-699.
12. Gunderson PE. The half-hitch knot: a rational alternative to the square knot. Am J Surg 1987;154:538-540.
13. Moreno M, Magos FJ, Arcovedo R, Olachea P, Palacios JA, Salazar A, et al. Comparison of the performance of
the Gea extracorporeal knot with the Roeder extracorporeal knot and the classical knot. Surg Endosc 2004;18:
157-160.
14. Milla MJ, Peindl RD, Connor PM. Arthroscopic knot tying: the role of instrumentation in achieving knot
security. Arthroscopy 2005;21:69-76.
15. Baums MH, Sachs C, Kostuj T, Schmidt-Horlohé K, Schultz W, Klinger HM. Mechanical testing of different
knot types using high-performance suture material. Knee Surgery Sports Traumatology Arthroscopy 2015;23:- 141 -

Nishimura et al1351-1358.
16. Dorsey JH, Sharp HT, Chovan JD, Holtz PM. Laparoscopic knot strength: a comparison with conventionalknots. Obstet Gynecol 1995;86:536-540.
17. Sharp HT, Dorsey JH, Chovan JD, Holtz PM. The effect of knot geometry on the strength of laparoscopic slip
knots. Obstet Gynecol 1996;88:408-411.
18. Grapow MT, Mytsyk M, Fassl J, Etter P, Matt P, Eckstein FS, et al. Automated fastener versus manually tiedknots in minimally invasive mitral valve repair: impact on operation time and short- term results. J
Cardiothorac Surg 2015;10:146.
19. Shibata T, Hattori K, Kato Y, Bito Y. Thimble type knot pusher: bioprosthesis stents no longer interfere withtying. Interact Cardiovasc Thorac Surg 2010;11:131-132.

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Osaka City Med. J. Vol. 64, 143-151, 2018

Experimental Methanol Poisoning: Electron Microscopic Findings
Obtained between 2 and 14 Days after Administration
NOBUHIKO UEDA, and KUNIHIKO SHIRAKI
Department of Ophthalmology and Visual Science,
Osaka City University Graduate School of Medicine

Abstract
BackgroundWe observed changes in retinal ganglion cells and the optic nerve using electron microscopy
between 2 and 14 days after experimental methanol poisoning.
Methods
Rats in the poisoning group received an intraperitoneal injection of methanol (3.5 g/kg) after 5
weeks on a folate-deficient diet. Rats in the control group received an intraperitoneal injection ofsaline after 5 weeks on a normal diet. In both groups, electron microscopic analysis was performedon eyeballs enucleated at 2, 7, and 14 days post-injection.
Results
In the poisoning group, retinal ganglion cells showed swelling and a decrease in organelle number
at 2 days post-injection, and aggregation of organelles at 7 and 14 days post-injection. Axons in the
optic nerve head exhibited swelling and a marked decrease in organelle number at 2 days postinjection. These findings were less marked at 7 and 14 days post-injection. Degeneration of axons
and myelin in the intraorbital optic nerve was observed at 2 days post-injection. These findings wereless marked at 7 and 14 days post-injection.
Conclusions
These findings suggest that significant retinal ganglion cell degeneration occurs between 2 and 14
days post-injection, while degeneration of the optic nerve head is most marked at 2 days postinjection.
Key Words: ‌Methanol; Poisoning; Retina; Optic nerve; Electron microscopy

Introduction
Acute methanol poisoning can lead to severe visual impairment. Onset of symptoms occurs 18 to48 hours following methanol ingestion. Systemic metabolic acidosis from acute methanol poisoning
can cause headaches, abdominal pain, coma, and in some cases even death. With respect to the
Received April 2, 2018; accepted November 27, 2018.
Correspondence to: Nobuhiko Ueda, MD.
Department of Ophthalmology and Visual Sciences, Osaka City University Graduate School of Medicine,
1-4-3 Asahimachi, Abeno-ku, Osaka 545-8585, Japan
Tel: +81-6-6645-3867; Fax: +81-6-6634-3867
E-mail: bwz12269@nifty.com- 143 -

Ueda et aleye, symptoms include decreased visual acuity, mydriasis, attenuation of the pupillary light reﬂex,
hyperemia and swelling of the optic nerve head, and peripapillary retinal edema. Visual acuity
usually recovers within six days of onset of symptoms. However, unless full recovery occurs, further
declines in visual acuity are expected, resulting in optic nerve atrophy and a poor prognosis1).
Methanol is metabolized in the liver into formaldehyde and then formic acid2). Formic acidinhibits cytochrome c oxidase, an enzyme of the mitochondrial electron transport chain3). It isthought that this inhibition reduces adenosine triphosphate (ATP) production and increases reactive
oxygen species in the mitochondria4,5), thereby resulting in damage to retinal ganglion cells (RGC).
It has been thought that animal models of acute methanol poisoning can be useful for developing
therapies. Past research has employed the rhesus monkey6) and the rat7-9) as animal models. Bothmodels have been examined in detail within a span of three days following methanol administration.
However, to the best of our knowledge, no studies using animal models have explored the subacutephase of poisoning, extending to 14 days after administration, and such research would be ofsignificant value for analyzing the pathology of acute methanol poisoning in the acute phase andbeyond. Thus, we performed a qualitative analysis of acute methanol poisoning in the rat model byusing light microscopy (LM) and electron microscopy (EM) to observe changes in the optic nerve and
RGC between 2 and 14 days after methanol administration.

Methods (Fig. 1)
The present study was carried out under the control guidance of a committee in accordance withThe Guidelines on Animal Experiments at Osaka City University.
The experiment used 24 four-week-old male Wistar rats, which were divided into two groups basedon the following criteria.
1. A poisoning group of 12 rats were fed a folate-deficient diet for five weeks ad libitum and thenreceived an intraperitoneal injection of methanol (3.5 g/kg).
2. A control group of 12 rats were fed a normal diet for five weeks and then received an
intraperitoneal injection of saline (11.7 mL/kg).
The folate-deficient diet was obtained from Dyets Inc., USA (#517777). A 30% (w/v) mixture ofmethanol and saline was prepared for intraperitoneal injection.

Figure 1. An overview of the experimental protocol.

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Experimental Methanol Poisoning

At 2, 7, and 14 days post-injection (dpi), eyeballs from four rats in each group were enucleatedfollowing perfusion fixation with a solution of 2.5% glutaraldehyde and 2% paraformaldehyde in a 0.1
M phosphate buffer under inhalation anesthesia using isoﬂurane.
The intraorbital optic nerve as well as the optic nerve head and surrounding retina were
harvested after resecting the optic nerve at a length of 1 mm from the eyeball. The harvested tissue
was pre-fixed with the same fixative solution described above, post-fixed with osmium tetroxide andthen embedded in resin. An ultramicrotome was used to cut samples into 1 μm slices, which werethen stained with toluidine blue then examined with a light microscope. The retina, the horizontal
longitudinal section of the optic nerve head and the cross-section of the intraorbital optic nerve
at a position of 1 mm from the eyeball were examined. Ultra-thin sections prepared at the sametime were double-stained with uranyl acetate and lead citrate and then examined with an electron
microscope (Hitachi H-7500).

Results (Table 1)
LM findings of the inner retina (Fig. 2)
Compared to the control group (Fig. 2A), at 2 dpi the poisoning group exhibited vacuolar
degeneration in the nerve fiber layer, ganglion cell layer and inner plexiform layers (Fig. 2B).
Although this finding diminished at 7 dpi, enlargement of some RGC somas was observed (Fig. 2C).

Table 1. Summary of Results
Inner retina
LM

EM

2 dpi

vacuolar degeneration

7 dpi

enlargement of some RGC somas

14 dpieccentric locations of nuclei

numerous vacuoles in RGC
vacuoles decreased,organelle aggregation in RGC
organelle aggregation was
more pronounced in RGC

Optic nerve head

2 dpi
7 dpi
14 dpiLM

EM

No remarkable change
No remarkable change
No remarkable change

Swollen axons
No remarkable change
No remarkable change

Intraorbital optic nerve
LM
2 dpi

No remarkable change

7 dpi

No remarkable change

14 dpiNo remarkable change

EM
Deformation and size disparity of axons
Gaps between axons and myelin sheaths
Changes in axons &myelin sheaths diminishedNo remarkable change

dpi, days post-injetion; LM, Light microscopy; EM, Electron microscopy; and RGC, retinal ganglion cells.

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Ueda et al

Figure 2. Light micrographs of the inner retina. A, Control group specimen at 2 days post-injection (dpi). Nochanges were observed in the control group at 2, 7, and 14 dpi. B, Poisoning group specimen at 2 dpi. Numerous
vacuoles were observed in the nerve fiber and inner plexiform layers (arrow). C, Poisoning group specimen at 7 dpi.
Retinal ganglion cell (RGC) soma enlargement was observed (＊). D, Poisoning group specimen at 14 dpi. RGC soma
enlargement and eccentric locations of nuclei at the periphery of the soma were observed (＊). Bar＝25 μm.

At 14 dpi, many of the RGC somas were swollen and a portion displayed eccentric locations of nuclei
at the periphery of somas (Fig. 2D).
EM findings of the inner retina (Fig. 3)
Compared to the control group (Fig. 3A), the RGC cytoplasm in the poisoning group exhibited
numerous vacuoles at 2 dpi (Fig. 3B), likely induced by the swelling of intracellular organelles.
Although these vacuoles decreased in number at 7 dpi, organelle aggregation was observed in the
RGC cytoplasm (Fig. 3C). At 14 dpi, RGC nuclei were eccentrically located at the periphery of somas
and organelle aggregation was more pronounced in the cytoplasm (Fig. 3D).
LM findings of the optic nerve headNo remarkable change was detected between the control group and the poisoning group for alltime points.

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Experimental Methanol Poisoning

Figure 3. Electron micrographs of the inner retina. A, Control group specimen at 2 dpi. No changes were observed in
the control group at 2, 7, and 14 dpi. B, Poisoning group specimen at 2 dpi. Marked vacuole formation was observedin the nerve fiber layer (＊), and numerous vacuoles appeared in the RGC cytoplasm (arrow). C, Poisoning groupspecimen at 7 dpi. Aggregation of intracellular organelles was observed in the RGC cytoplasm (＊). D, Poisoning
group specimen at 14 dpi. RGC nuclei eccentric locations at the periphery of cell somas (arrow) and aggregation of
intracellular organelles with high electron density were observed in the cytoplasm (＊). Bar＝5 μm.

EM findings of the optic nerve head (Fig. 4)
Compared to the control group (Fig. 4A), the poisoning group exhibited swollen axons in the optic
nerve head and a marked reduction in intracellular organelles at 2 dpi (Fig. 4B). These findings
disappeared at 7 dpi (Fig. 4C) and 14 dpi (Fig. 4D).
LM findings of the intraorbital optic nerve
No remarkable change was detected between the control group and the poisoning group for alltime points.
EM findings of the intraorbital optic nerve (Fig. 5)
Compared to the control group (Fig. 5A), axons in the intraorbital optic nerve of the poisoning
group exhibited deformation and size disparity. Gaps were also detected between axons and myelin
sheaths at 2 dpi (Fig. 5B). These findings diminished at 7 dpi (Fig. 5C) and were undetectable at 14
dpi (Fig. 5D).

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Ueda et al

Figure 4. Electron micrographs of the optic nerve head. A, Control group specimen at 2 dpi. No changes wereobserved in the control group at 2, 7, and 14 dpi. B, Poisoning group specimen at 2 dpi. Swollen axons and a marked
decrease in intracellular organelles were observed (＊). C, Poisoning group specimen at 7 dpi. D, Poisoning groupspecimen at 14 dpi. Improvements were observed in axon swelling and intracellular organelle reduction. Bar＝2 μm.

Discussion
The present study employed EM of the retina and optic nerve to investigate a rat model of acutemethanol poisoning. As a result, at 2 dpi we identified vacuolar degeneration in the inner retina,
swollen axons in the optic nerve head and axon deformation in the intraorbital optic nerve. RGC
soma enlargement in the inner retina was observed at 7 dpi and beyond. In contrast, changes in the
optic nerve head and intraorbital optic nerve were found to have improved at 7 dpi and 14 dpi.
Accumulation of formic acid following methanol administration is less likely in rats compared toprimates10). As such, rat models of acute methanol poisoning have used nitrous oxide 7) and folatedeficient feed10) to inhibit the metabolism of formic acid. In the nitrous oxide model, rats must be kept
in containers infused with a gaseous mixture of nitrous oxide and oxygen. Nitrous oxide poses safety
risks because it can be either combustible or readily support combustion. On the other hand, thefolate-deficient model requires feeding rats an expensive folate-deficient diet from five weeks before
the initial methanol administration until the conclusion of the experiment. We decided, however, toadopt this model because, unlike nitrous oxide, no safety issues needed to be addressed.

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Experimental Methanol Poisoning

Figure 5. Electron micrographs of the intraorbital optic nerve. A, Control group specimen at 2 dpi. No changes wereobserved in the control group at 2, 7, and 14 dpi. B, Poisoning group specimen at 2 dpi. Axon deformation (＊) andgaps between axons and myelin sheaths were observed (arrow). C, Poisoning group specimen at 7 dpi. A decrease inchanges in axons and myelin sheaths was observed. D, Poisoning group specimen at 14 dpi. No obvious differenceswith the control group were observed. Bar＝2 μm.

In a previous study, we divided rats into four groups based on the criteria noted below andmeasured the serum formic acid concentration of blood samples collected at 2 dpi. 1) The normal
diet-saline group was fed a normal diet for 5 weeks and then given an intraperitoneal injection ofsaline. 2) The normal diet-methanol group on a was fed a normal diet for 5 weeks and then given
an intraperitoneal injection of methanol (3.5 g/kg). 3) The folate-deficient diet-saline group was
fed a folate-deficient diet for 5 weeks and then given an intraperitoneal injection of saline. 4) The
folate-deficient diet-methanol group was fed a folate-deficient diet for 5 weeks and then given an
intraperitoneal injection of methanol (3.5 g/kg). The results of the serum formic acid concentration
were as follows: 1.00 mM in the normal diet-saline group; 1.18 mM in the normal diet-methanolgroup; 1.37 mM in the folate-deficient diet-saline group; and 12.54 mM in the folate-deficient dietmethanol group. The folate-deficient diet-methanol group had a significantly higher serum formic
acid concentration than the other groups 11). This result is relatively consistent with past research
employing the primate model (11.2-12.9 mM) 6), and rat models using nitrous oxide (14.8 mM) 7)
or a folate-deficient diet (16.1 mM)10). To investigate the effects of increased serum formic acid- 149 -

Ueda et alconcentrations on the retina and optic nerves of rats in methanol poisoning, the normal diet-salinegroup and the folate-deficient diet-methanol group were used as the control group and the poisoning
group, respectively.
We identified vacuolar degeneration in RGC somas at 2 dpi, a finding that is consistent withprevious studies in rats 7,9). As with past research, we also observed swollen axons in the optic nerve
head2). These findings could be considered equivalent to retinal edema and papillary swelling inhuman cases of acute methanol poisoning1). However, our observations differed from those of aprevious study using the rhesus monkey model, in which retinal changes were not detected, but theaggregation of intracellular organelles within the axons of the intraorbital optic nerve was observed6).
This study in rhesus monkeys noted a blood formic acid concentration between 11.2 and 13.1 mEq/L6),
which is comparable to a report of 12.54 mM in the rat model11) that we employed. Therefore, thesedifferences can be considered to be specific to the animal model, but require further investigation.
Vacuolar degeneration is generally thought to be caused by an increase in the water permeabilityof the cell membrane. The liver metabolizes methanol into formic acid 2). Formic acid inhibits
cytochrome c oxidase3), an enzyme in the mitochondrial electron transport chain, which in turnleads to reduced ATP production in the retina12). Therefore, it can be inferred that the vacuolar
degeneration of RGC somas and swelling of optic nerve head axons observed in this study are theconsequences of enhanced membrane permeability, caused by ion pump impairment that occurs when
the formic acid metabolized from methanol suppresses ATP production and triggers a shortage ofintracellular energy.
In the present study, vacuolar degeneration in RGC somas and swelling of optic nerve headaxons subsided from days 7 to 14 after methanol administration. We propose that this finding iscomparable to improvements in retinal edema and papillary swelling seen in clinical cases1). To thebest of our knowledge, such observations have not been made in animal models of acute methanol
poisoning. We propose the following mechanism to explain this result. Sadun et al report thatblood formic acid concentration returns to normal 72 hours after methanol administration in theirstudy of an animal model of chronic methanol poisoning13). Considering that formic acid inhibition ofcytochrome c oxidase due to formic acid and the ensuing decrease in ATP production are transient,
it can be inferred that vacuolar degeneration in RGC somas as well as swelling of optic nerve headaxons are also temporary.
The present study identified RGC soma enlargement and intracellular organelle aggregation
between days 7 and 14 after methanol administration. To the best of our knowledge, suchobservations have not been made in past studies using animal models of acute methanol poisoning.
We submit that our findings are related to the progressive reduction in visual acuity that occurs after
temporary vision improvement in clinical cases1).
We believe that the results of the present study may be useful for understanding the pathologyof the acute to subacute phases of acute methanol poisoning and developing appropriate therapies.
However, the development and evaluation of therapies will require quantitative assessment ofdamage to RGC somas and axons.
Using the rat model of acute methanol poisoning, we qualitatively established that although RGC
soma impairment persists two to 14 days after methanol administration, damage to the optic nerveaxons is temporary. Our findings suggest that the present model is useful for analyzing the pathologyof and developing therapies for acute methanol poisoning in the acute and subacute phases.

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Experimental Methanol Poisoning

References
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320 persons. Am J Ophthalmol 1953;36:1677-1685.
2. Eells JT, Henry MM, Lewandowski MF, Seme MT, Murray TG. Development and characterization of a rodent
model of methanol-induced retinal and optic nerve toxicity. Neurotoxicology 2000;21:321-330.
3. Nicholls P. Formate as an inhibitor of cytochrome c oxidase. Biochem Biophys Res Commun 1975;67:610-616.
4. Rajamani R, Muthuvel A, Manikandan S, Srikumar R, Sheeladevi R. Efficacy of DL-alpha-lipoic acid on
methanol induced free radical changes, protein oxidative damages and hsp70 expression in folate deficient rat
nervous tissue. Chem Biol Interact 2007;167:161-167.
5. Rajamani R, Muthuvel A, Senthilvelan M, Sheeladevi R. Oxidative stress induced by methotrexate alone andin the presence of methanol in discrete regions of the rodent brain, retina and optic nerve. Toxicol Lett 2006;
165:265-273.
6. Baumbach GL, Cancilla PA, Martin-Amat G, Tephly TR, McMartin KE, Makar AB, et al. Methyl alcohol
poisoning. IV. Alterations of the morphological findings of the retina and optic nerve. Arch Ophthalmol 1977;
95:1859-1865.
7. Murray TG, Burton TC, Rajani C, Lewandowski MF, Burke JM, Eells JT. Methanol poisoning. A rodent modelwith structural and functional evidence for retinal involvement. Arch Ophthalmol 1991;109:1012-1016.
8. Sahin A, Kaya S, Türkcü G, Cingü AK, Yüksel H, Türkcü FM, et al. The effects of caffeic acid phenethyl esterin acute methanol toxicity on rat retina and optic nerve. Cutan Ocul Toxicol 2013;32:263-267.
9. El-Bakary AA, El-Dakrory SA, Attalla SM, Hasanein NA, Malek HA. Ranitidine as an alcohol dehydrogenase
inhibitor in acute methanol toxicity in rats. Hum Exp Toxicol 2010;29:93-101.
10. Lee EW, Garner CD, Terzo TS. Animal model for the study of methanol toxicity: comparison of folate-reduced
rat responses with published monkey data. J Toxicol Environ Health 1994;41:71-82.
11. Ueda N, Shiraki K. Electron Microscopy Findings for Experimental Methanol Poisoning. Journal of the Eye
2014;31:1555-1561. (in japanese)
12. Seme MT, Summerfelt P, Neitz J, Eells JT, Henry MM. Differential recovery of retinal function after
mitochondrial inhibition by methanol intoxication. Invest Ophthalmol Vis Sci 2001;42:834-841.
13. Sadun A. Acquired mitochondrial impairment as a cause of optic nerve disease. Trans Am Ophthalmol Soc
1998;96:881-923.

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Examples of reference style

1. Priori SG, Schwartz PJ, Napolitano C, et al. Risk stratification in the long-QT syndrome. N Engl J Med
2003;348:1866-1874.
2. Schwartz PJ, Priori SG, Napolitano C. The long-QT syndrome. In: Zipes DP, Jalife J, editors. Cardiac
electrophysiology: from cell to bedside. 3rd ed. Philadelphia: W.B. Saunders; 2000. pp. 597-615.

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Studies of human subjects. It is the responsibility of the authors to ensure that any clinicalinvestigation they did and report in manuscripts submitted to the Osaka City Medical Journal are inaccordance with the Declaration of Helsinki (http://www.wma.net).
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[Reviced: January 2018]

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Editorial Committee

Masaaki Inaba, MD (Chief Editor)
Yasuhiro Fujiwara, MD

Wakaba Fukushima, MD

Kazuo Ikeda, MD

Motoharu Imanaka, MD

Koki Inoue, MD

Norifumi Kawada, MD

Shoji Kubo, MD

Yukio Miki, MD

Yukio Nishiguchi, MD

Masahiko Ohsawa, MD

Toshiyuki Sumi, MD

Masahiro Tanaka, MD

Daisuke Tsuruta, MD

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