Ann Nucl Med (2008) 22:115–122
DOI 10.1007/s12149-007-0091-2

ORIGINAL ARTICLE

Assessment of diastolic function using 16-frame 201Tl gated myocardial
perfusion SPECT: a comparative study of QGS2 and pFAST2
Shigeki Nagamachi · Hideyuki Wakamatsu
Seigo Fujita · Ryuichi Nishii · Kiyohisa Kamimura
Shogo Kiyohara · Shigemi Futami · Hisamitsu Onitsuka
Yasuko Nagoshi · Shozo Tamura · Keiichi Kawai
Hideo Arita
Received: 6 April 2007 / Accepted: 28 September 2007
© The Japanese Society of Nuclear Medicine 2008

Abstract
Objective The objective of the present study is to investigate the correlations across various types of interface
software for 201Tl gated myocardial perfusion SPECT(MPS) in calculating two common diastolic function
parameters (DFx), peak-filling rates (PFR), and time-topeak filling (TTPF).
Methods A total of 109 patients (66 men and 43 women;age 35–78 years) were studied. All patients were classified into three groups (i.e., ND, no-defect group; SD,
small-defect group; LD, large-defect group) to clarify
the influence of perfusion defects possibly affecting theanalysis. Two kinds of available software, namely,
quantitative gated SPECT (QGS2) and perfusion andfunctional analysis for gated SPECT (pFAST2) withcardioGRAF were used to obtain PFR and TTPF.
Finally, we analyzed the correlation between DFx
obtained with the two different kinds of software.
Results The values of LVEF, PFR, and TTPF wereassessed in all patients. In both the ND (correlation coef-

ficients were 0.92, 0.79, and 0.99, respectively) and SD
groups (correlation coefficients were 0.74, 0.88, and 0.98,
respectively), a strong correlation was observed. In contrast, PFR did not show a significant correlation in the
LD group.
Conclusions With the two different kinds of software,
QGS2 and pFAST2, the calculated PFR was almost
equal and showed good correlations in both ND and SD
groups. In contrast, the numerical value varied between
the two methods, and its correlation was poor in the LD
group. However, TTPF showed a good correlation
regardless of the presence of perfusion defects, and thevalues were equal. TTPF was confirmed to be a stable
diastolic index across the two kinds of software, QGS2
and pFAST2, in 201Tl gated MPS.
Keywords Left ventricular diastolic function · 201Tl
gated myocardial perfusion SPECT · QGS2 · pFAST2Introduction
S. Nagamachi (*) · H. Wakamatsu · S. Fujita · R. Nishii ·S. Kiyohara · S. Futami · S. Tamura · H. Arita
Department of Radiology, Miyazaki Medical College, 5200
Kihara, Kiyotake, Miyazaki 889-1692, Japane-mail: snagama@med.miyazaki-u.ac.jp
K. Kamimura
Department of Radiology, Fujimoto Hayasuzu Hospital,
Miyazaki, Japan
H. Onitsuka · Y. Nagoshi
Department of First Internal Medicine, Miyazaki Medical
College, Miyazaki, JapanK. Kawai
School of Health Sciences, Faculty of Medicine, Kanazawa
University, Kanazawa, Japan

Abnormality of left ventricular (LV) diastolic function(DFx) is frequently the earliest indicator of LV dysfunction in many diseases, including coronary artery disease(CAD) [1], congestive heart failure (CHF), cardiomyopathy [2], valvular heart disease [3], and diabetes
mellitus [4]. In particular within heart failure, isolated
diastolic dysfunction in which systolic function is normal
as diastolic function is disturbed, is really present in
40%–50% of cases [5]. It is, therefore, extremely important to diagnose cardiac diastolic dysfunction.
In addition to myocardial perfusion, gated myocardial perfusion SPECT (MPS) is widely used for theassessment of systolic function (SFx) by the measure-

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ment of LV ejection fraction (LVEF) and LV volumes
using a variety of commercially available software programs [6–8]. For the evaluation of DFx, Doppler echocardiography and, although the versatility is limited,first-pass and gated blood pool scintigraphy (GBPS) are
the established procedures [9–11]. The assessment of
DFx has also been shown to be feasible with gated MPS[12–15]. The stability of DFx variables estimated by
99m
Tc-MIBI gated MPS has been reported recently [16].
However, the stability of DFx variables is unclear, andnormal values for DFx parameters using 201Tl gated
MPS have not yet been described. Furthermore, there isno agreement as to which DFx variables are likely to be
most effectively measured with 201Tl gated MPS.
Although 201Tl is inferior to 99mTc in image quality [17],we can diagnose multivessel disease by the washout rateof 201Tl [18]. On the basis of the uptake mechanism, it iseffective in the estimation of myocardial viability [19,20]. It is, therefore, still used routinely for practical
purposes.
Several kinds of gated SPECT software are available
for clinical use, and diastolic parameters can be calculated by software such as quantitative gated SPECT(QGS2, Cedars-Sinai Medical Center, Los Angeles, CA,
USA) [6] and perfusion and functional analysis for gated
SPECT (pFAST2; Sapporo Medical University, Sapporo,
Japan) [8]. This software, pFAST2, is released to generalinstitutions freely, and installation is possible with a PC.
The software, therefore, is used for clinical purposes atmany hospitals. These programs have correlated wellwith conventional methods for calculating EF [6, 8, 21,22]. With regard to systolic indices, a correlation between
different software is reported [23]. However, only a few
clinical studies have been conducted regarding the
cardiac diastolic function parameters estimated by gated
MPS [12, 16, 24].
The objective of the present study is to evaluate correlations between the two software programs (QGS2 andp-FAST2) in computing gated SPECT diastolic function
parameters in both patients with and without perfusion
defects. We also discuss whether we might compare diastolic function parameters calculated by different software in the follow-up of the same patient.

Materials and methods
Patient population
The study population comprised 109 patients referred
for stress/rest gated MPS who met the following criteria:
technically acceptable normal rest and gated MPS,
achieving 85% of maximum predicted heart rate during

13

Ann Nucl Med (2008) 22:115–122

symptom-limited treadmill exercise (Bruce protocol).
The diagnoses for these patients consisted of old myocardial infarction (n = 31), old myocardial infarction
with angina pectoris (n = 25), angina pectoris (n = 43),
and finally diagnosed as normal (n = 10). No patients
had valvular regurgitation. The so-called small heart
patients were excluded from the present study. Namely,such cases, in which the lumen of left ventricle could not
be visualized separately owing to its low volume evenafter the enlargement procedure, were excluded from thestudy. All patients signed informed consent forms prior
to the study, and the study protocol was approved by
the research council of our institution.
According to Nakajima et al. [23], all the patientswere classified into three groups on the basis of the myocardial SPECT findings. The no-defect (ND) group comprised 35 patients in whom resting perfusion SPECT
found no perfusion defect. The small perfusion defect(SD) group comprised 54 patients with a small perfusion
defect. The large perfusion defect (LD) group comprised
20 patients with a large perfusion defect. The criteria
were visually assessed by two nuclear medicine physicians, who reached a consensus on the polar map images.
On the polar map image, which consisted of 20 segments(six basal portion, six mid-portion, six apical portion,and two apex), four-point scoring analysis was done.
The defect score was defined as follows: 3, perfusion
defect; 2, severe low perfusion; 1, moderate low perfusion; and 0, normal perfusion. On the basis of the total
number of segments with severe low perfusion or perfusion defect (score 2 or 3), we classified the patients into
three subgroups such as the LD group that included
more than seven segments whose defect score was 2 or
3; the ND group that consisted of all segments withdefect score 0, and we defined the other patients as theSD group.

Image acquisition/reconstruction
All patients underwent 201Tl MPS following 111 MBq
201
Tl injection at peak exercise. Images were acquiredwith a two-detector camera (e-CAM, Siemens Medical
Systems, USA) using elliptic 360° acquisition with 92
projections at 15 s per projection and 16 frames per
R–R interval. The projection data were reconstructed
into tomographic transaxial images using the filtered
back projection (FBP) method and automatic reorientation. Tomographic short-axis images were reconstructedwith a Butterworth filter that had a cutoff frequencyof 0.4 cycles per centimeter (order 8). No attenuationor scatter correction was used. The pixel size was
5.32 mm.

Ann Nucl Med (2008) 22:115–122

117

Assessment of DFx and SFx by the two different kindsof software
For this study, a new version of QGS2 software was used
(QGS Companion; Cedars-Sinai Medical Center), whichquantifies DFx parameters using the bicubic spline interpolation of the LV volume/time curve. The algorithm fordetermining edges and calculating volume has been
described and validated by Germano et al. [6, 21]. At thesame time, we used version 2 of the pFAST2 software[8], which is designed to operate on Windows for personal computers and transfers data online from a SPECT
system. After the myocardium was automaticallyextracted, a region of interest was set using spine interpolation. When the myocardial perfusion defect waslarge and the fitting deemed inappropriate, the shapewould then be adjusted manually. The radial profile
curves were generated from the center. The distancefrom the myocardial maximum point to the epicardial
border was defined as 50% of the maximum count. The
endocardial border was calculated as the distance fromthe center to the myocardial peak count plus k times wall
thickness, where k was empirically determined to be
0.35.
Automatic processing was initially used for both software programs. When the wall tracing was visuallyjudged inappropriate in using pFAST2, the operator
modified the ventricular border surrounding the ventricle and reprocessed the edge.
The LV-filling rate/time curve was composed from thefirst derivative of the volume/time curve. The peak-fillingrate (PFR) was defined as the maximum dV/dt value
divided by end-diastolic volume (per second) [16], and aunit of PFR was expressed in EDV/S. The time-to-peakfilling (TTPF), expressed in milliseconds, is the interval
between end-systole (ES) and PFR. For SFx, LVEF (%)
was calculated from the LV volume/time curves as commonly used [6, 16]. Recent QGS2 software computes the
DFx parameters in their corresponding units, rather
than providing raw frame numbers in brackets, which

Table 1 Patients’characteristics
AP angina pectoris, MI
myocardial infarction, NS notsignificant, HR heart rateduring gated, MPS
acquisition, EDV end
diastolic volume, ESV end
systolic volume, M male,
F femaleaBoth EDV and ESV were
measured by QGS2

Age (years)
M:F
Diagnosis
NormalAP
AP + old MI
Old MI
HR (bpm)
EDV (ml)
ESV (ml)needed further calculations to find the final unit values
like in the previous version.
We also analyzed the differences in percentage (%difference), correlation, and Bland Altman plot in two
kinds of DFx parameters and LVEF between QGS2 andpFAST in each group.
Statistical analysis
The results are expressed as mean ± standard deviation.
The comparisons between groups were made with theMann–Whitney U test. The comparisons of proportions
were made using Fisher’s exact test. The correlations
between diastolic function parameters calculated by
QGS2 and those calculated by pFAST2 were determinedusing Pearson’s correlation coefficient. At the same time,% differences of all the data were calculated, and themean value of each of the three groups was compared.
Finally, the Bland Altman Plot analysis was performed
to evaluate the bias [25] and to establish 2SD values
between the two studies. Statistical analysis was performed using the GraphPad Prism 4 for Windows statistical application program. In all assessments, P < 0.05
was considered to be statistically significant.

Results
There were no significant differences in clinical parameters among the three subgroups. Regarding mean ventricular volumes, both values of EDV and ESV in the
LD group were statistically significantly higher thanthose in the other subgroups (Table 1). We examined theinter-observer and intra-observer reproducibility of thedata from 16 R-R interval gated SPECT in using
pFAST2. The inter-observer analysis was performed by
two independent observers. The intra-observer analysis
was done twice by the same observer. The reproducibility was good in respect to all the LV systolic and diastolic
functional variables (Table 2). The values of LVEF,

ND group

SD group

LD group

67.3 ± 13.1
21 : 1465.7 ± 10.2
31 : 2365.6 ± 8.6
15 : 5

NS
NS

10
25
0
0
74.8 ± 9.5
58.3 ± 19.2
19.0 ± 14.1

0
18
12
24
69.9 ± 11.7
59.5 ± 19.5
26.8 ± 17.9

0
0
13
7
67.6 ± 4.6
102.1 ± 50.2a56.5 ± 43.8a

NS
<0.05
<0.05

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Ann Nucl Med (2008) 22:115–122

ND group

SD group

LD group

2.33 ± 0.74
2.58 ± 0.78
14.3 ± 14.3

2.55 ± 1.05
2.61 ± 0.86
15.8 ± 20.9

1.77 ± 0.61
1.95 ± 0.52
40.2 ± 44.3

ment for LVEF were −11.2 to 8.7, −28.2 to 19.5, and−26.5 to 14.5 between the ND, SD, and LD groups,
respectively (Fig. 2a).
In both the ND and SD groups, the value of PFR
showed an excellent correlation (r = 0.79 in the ND
group and r = 0.88 in the SD group). In contrast, there
was no correlation in the LD group (Fig. 1b). The limitsof agreement for PFR were −0.61 to 0.58, −1.0 to 0.89,
and −1.59 to 1.23 between the ND, SD, and LD groups,
respectively (Fig. 2b).
Regarding TTPF, they also showed good correlations(r = 0.99 in the ND group, r = 0.98 in the SD group, andr = 0.91 in the LD group, Fig. 1c). The limits of agreement for TTPF were −20.3 to 20.8, −40.1 to 32.5, and−107.9 to 128.3, respectively (Fig. 2c).

195.8 ± 97.6
195.6 ± 100.6
5.1 ± 3.7

231.8 ± 90.5
236.1 ± 98.5
6.5 ± 4.8

264.7 ± 144.7
254.5 ± 122.3
23.6 ± 48.0

Discussion

73.6 ± 13.0
74.8 ± 12.6
5.9 ± 4.2

63.1 ± 13.1
66.6 ± 14.0
10.0 ± 7.3

44.8 ± 11.8
51.3 ± 11.1
25.7 ± 24.7

Table 2 Reproducibility of various parameters in using pFAST2

LVEF
PFR
TTPF

Inter-observer, %CV

Intra-observer, %CV

1.32 ± 0.52
1.29 ± 0.86
1.17 ± 0.62

1.12 ± 0.51
1.23 ± 0.71
1.12 ± 0.42

Data are expressed as mean ± SD

Table 3 Differences in percentage of parameters

PFR (EDV/s)
QGS2pFAST2Difference (%)
TTPF (ms)QGS2pFAST2Difference (%)
LVEF (%)
QGS2
PFAST2Difference (%)

ND no-defect group, SD small-defect group, LD large-defectgroup, PFR peak-filling rates, QGS2 quantitative gated SPECT,pFAST2 perfusion and functional analysis for gated SPECT,TTPF time-to-peak filling, LVEF left ventricular ejection
fraction

Table 4 Differences in percentage of left ventricular volume

EDV (ml)QGS2pFAST2Difference (%)
ESV (ml)QGS2pFAST2Difference (%)

ND group

SD group

LD group

58.3 ± 19.2
76.2 ± 25.1
31.4 ± 13.6

59.5 ± 19.5
79.1 ± 29.7
35.7 ± 3.7

102.1 ± 50.2
169.7 ± 97.3
44.4 ± 7.7

19.0 ± 14.1
22.0 ± 18.7
20.8 ± 19.1

26.8 ± 17.9
29.5 ± 22.6
17.5 ± 15.7

56.5 ± 43.8
78.9 ± 72.0
30.1 ± 17.4

PFR, and TTPF in the three groups of patients are summarized in Table 3. Similarly, both the values of ESV
and EDV are summarized in Table 4. Both EDV and
ESV estimated by QGS2 were apparently lower thanthose with pFAST2. The tendency was prominently
noted in the LD group.
Correlations of LV systolic and diastolic functionalparameters measured by the two different methods
Regarding LVEF, the correlation was good in all groups(r = 0.92 in the ND group, r = 0.74 in the SD group, andr = 0.65 in the LD group, Fig. 1a). The limits of agree-13

The present study demonstrated a good correlation
between diastolic function indexes obtained from two
different software packages (QGS2 and pFAST2) using
different algorithms. Conventionally, 201Tl has been usedroutinely for the following three reasons. The first is that201
Tl is the agent of choice in identifying myocardial
viability on the basis of the assessment of sarcolemma
integrity [26, 27]. The second is that 201Tl offers the possibility of assessing LV function at rest and immediately
after stress [28]. The third is that it offers indirect signsof LV dysfunction, which are associated with multivesselor severe coronary disease and a poor prognosis [29]. An
earlier report confirmed the reliability of 201Tl gated
SPECT as a tool for the assessment of LVEF andregional wall motion abnormality (WMA) [30].
However, 201Tl became useless because of its low
energy with a lack of feasibility. In particular, plenty oftime is needed to acquire counts in gated myocardial
SPECT. Recently, a myocardial collimator (Siemens)has been developed and has become widely used. Becauseof its higher sensitivity, the time necessary to acquire
data has been shortened. This instrument will help overcome the drawbacks of 201Tl.
Although the reliability of DFx has been establishedin gated blood-pool studies [31, 32], it has not been confirmed in gated myocardial SPECT using 201Tl. The mostcommonly used parameters for assessing DFx are the
PFR and the TTPF. Using a new algorithm in QGS2
and pFAST2 software, we evaluated the correlation
between these parameters obtained with two kinds ofsoftware in patients with suspected ischemia under rest
conditions. The TTPF showed good correlations inevery group. In contrast, PFR showed poor correlationsin the group with large perfusion defects. In an earlier

Ann Nucl Med (2008) 22:115–122
Fig. 1 Correlation of left
ventricular ejection fraction(LVEF) obtained fromquantitative gated SPECT(QGS2) and perfusion andfunctional analysis for gated
SPECT (pFAST2). Although
positive correlations are notedin every condition, thecorrelation coefficient in thelarge-defect (LD) group islower than that in the othertwo conditions (a).
Correlation of peak-fillingrates (PFR) obtained from
QGS2 and pFAST2.
Although positive
correlations are noted in boththe no-defect (ND) and smalldefect (SD) groups, there isno significant correlation in
the LD group (b). Correlationof time-to-peak filling (TTPF)
obtained from QGS2 andpFAST2. Significant positive
correlations are noted in all
three conditions (c)119apFAST2
100

100

Y=0.96X-0.64
R =0.74

Y=0.9X+8.6
R =0.92

50

50

0

50

ND groupbpFAST2pFAST2
100

50

100
QGS2

SD group

pFAST2

0

100
QGS2

pFAST2

Y=1.1X+0.26
R =0.88

7.5

50

LD group

pFAST2

Y=0.63X+0.82
R =0.79

4.0

50

0

100
QGS2

Y=0.58X+14.8
R =0.65

3.0

5.0

2.0

2.5

1.0

2.0

0

2.0

4.0
QGS2

0

2.5

ND group
c

5.0

7.5
QGS2

pFAST2500

500
Y=1.03X-5.27
R =0.99

Y=1.1X+9.8
R =0.91

Y=1.07X-12.2
R =0.98

250

250

250

500
QGS2

ND group

report, QGS analysis could not be performed correctlyin cases in which the perfusion defect involved more than
50% of the myocardium [33]. Poor correlations of PFR
in the group with large defects seemed to be related tothese limitations. It seems that the influence of different
exhaustion methods of cardiac contour is strong on the

0

3.0
QGS2

LD group

pFAST2

500

2.0

1.0

SD group

pFAST2

0

0

250

250

SD group

500
QGS2

0

250

500
QGS2

LD group

analysis of cases having a large defect. As anticipated,both EDV and ESV estimated by QGS2 were apparently
lower than those with pFAST2. Because PFR is an inclination of the LV volume curve, prominent differences insuch ventricle volumes are likely to have an important
influence. Moreover, PFR is normalized to EDV, and so

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120

Ann Nucl Med (2008) 22:115–122aQGS-pFAST

QGS-pFAST

ND group

QGS-pFAST

SD group

15

20

30

+2SD
+8.7

20

Mean
-1.3

-10

5

-5

+2SD
+19.5

10
0

Mean
-6.8

-20

-2SD
-11.2

-15
50

60

80

70

90

100

+2SD
+14.5

10
0

Mean
-7.6

-10
-20

-2SD
-26.5

-30

-40
25

110

75

50

10

100

QGS-pFAST

ND group

30

20

40

50

60

70

80

Average of QGS and pFAST

Average of QGS and pFASTb
QGS-pFAST

-2SD
-28.2

-30

Average of QGS and pFAST

LD group30

40

SD group

QGS-pFAST

2

LD group

2

1.0

+2SD
+0.58

0.5
0.0

Mean
-0.43

-0.5

-2SD
-0.61

-1.0

1

+2SD
0.89

0

Mean
-0.6
-2SD
-1.0

-1

2

3

4

Mean
-0.18

0
-1

-2SD
-1.59

-2

-2

1

+2SD
1.23

1

5

2.5

5.0

1

7.5

Average of QGS and pFAST

Average of QGS and pFAST2c

QGS-pFAST

QGS-pFAST

ND group

QGS-pFAST
50

40

+2SD
20.8

25

0

Mean
0.3

0

-20

-2SD
-20.3

-25

20

-40
100

200

300

400

500

Average of QGS and pFAST

600

-50

3

4

5

Average of QGS and pFAST

SD group

LD group

200

+2SD
32.5
Mean
-4.3

+2SD
128.3

100

Mean
10.2

0

-100

-2SD
-41.0
100

200

300

400

500

Average of QGS and pFAST

600

-2SD
-107.9

-200
100

200

300

400

500

600

700

Average of QGS and pFAST

Fig. 2 Comparison of left ventricular function indexes by Bland–
Altman plots analysis. Dotted line indicates two-SD threshold.
Regarding LVEF, the limits of agreement of difference in each of
the three conditions are small (a). In the LD group, limits of agree-

ment of difference between PFR obtained from QGS2 and pFAST2
are relatively wide (b). Regarding TTPF, limits of agreement ofdifference in each of the three conditions are small (c)the difference in calculated EDV also seemed to be an
influential factor.
As TTPF is a timing of volume change, it seemed that
there was little influence of different exhaustion methodsof contour. As Akincioglu reported, TTPF appears to
be a stable and more useful parameter than PFR [16].
Temporal undersampling can adversely affect functional measurements [6]. In general, it has long been
considered that an accurate assessment of DFx requires
a greater number of frames per cardiac cycle than anassessment of SFx [12, 13, 15], with 32 frames recommended [12, 34]. It is well known that temporal resolution equal to or less than 40 ms/frame is required toestimate diastolic dysfunction using gated pool scintig-

raphy. This fact indicates that the 16-frame gated MPS
will not achieve the basis. However, obtaining adequate
counts for evaluation of DFx in a 32-frame gated MPS
would require longer acquisitions than gated pool
imaging because of the lower counting rates, potentiallyexceeding 30 min with conventional methods. A recent
study has suggested that the impact of fewer frames onthese measurements may be less than previously thoughtof [16]. As the values that we observed in our population
were similar to the earlier reported values from GBPS
studies with higher frame rates or MPS using 99mTcMIBI [16, 35], we consider it likely that 16-frame data
will suffice in providing adequate temporal resolution toassess DFx even in 201Tl-SPECT.

13

Ann Nucl Med (2008) 22:115–122

Although earlier studies have indicated that PFR
varies when linked with other parameters, such as HR,
EDV, ESV, LVEF, and age, TTPF seems to demonstrate less variability [16, 35]. Akincioglu et al. [16]recently reported that TTPF varies slightly with HR anddoes not significantly correlate with age, but PFR shows
significant correlations with both of these parameters. In
contrast, Muntinga et al. [36] observed an intermediate
correlation between TTPF and age. As most subjects inthe present study had ischemia, we could not obtain sufficient numbers for the analysis. In the future, we should
perform a study with adjustment for SFx, HR, and age,even when acquired with 16-frame protocols.
Finally, the correlation of diastolic function parameters was relatively poor in the LD group. Particularly,
the measurements of PFR cannot be used interchangeably in the large perfusion defect group by two different
software packages (QGS2 or pFAST2). The clinicalimplication of this is that diastolic indices should be usedwith caution, when follow-up examinations of DFx are
performed in conditions such as severe CADs or ischemic heart failure. In contrast, a follow-up study withtwo different software packages would be possible indiseases not characterized by large perfusion defects
such as DCM. However, in the same patient, sequential
studies should ideally be done using the same software
package. Determination of the degree to which standard
16-frame gated MPS acquisitions can be useful clinicallywould require further study of patients with both normal
and abnormal DFx.

Conclusions
With two different kinds of software, QGS2 andpFAST2, the value of PFR was almost equal and showed
a good correlation in both ND and SD groups. However,in the LD group, numerical values varied between thetwo methods. In contrast, TTPF showed a good correlation regardless of the presence of perfusion defects, andthe values were equal. TTPF was likely to be stable
across the two kinds of software, QGS2 and pFAST2,
in 201Tl gated MPS.

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