Prospective Trial of Arthroscopic Meniscectomy for Degenerative Meniscus Tears
Phase: NA
Conditions: Meniscus Tear
Sponsor: VA Office of Research and Development

Prospective Trial of Arthroscopic Meniscectomy for Degenerative Meniscus Tears   
NCT01931735 
 
Study Protocol and Statistical Analysis Plan 
Document Date: October 1, 2013 

02a. Research Plan 
Background and Significance 
Guiding treatment of degenerative meniscus tears 
    Arthroscopic meniscectomy of the knee is among the most commonly performed orthopedic 
procedures in the United States and in the VA system.  In 1999, it was estimated by the 
American Academy of Orthopedic Surgeons that 636,000 arthroscopic meniscectomies were 
performed annually in the United States (Praemer et al., 1999).  Each procedure has been 
estimated to cost approximately $5000 (Moseley et al., 2002) leading to an estimated annual 
cost to the healthcare system of over three billion dollars. 
Meniscus tears occur in a variety of settings and in patients with varied demographics, and 
various meniscus tear types have been described.  Though there are certain tear types such as 
bucket-handle tears which are amenable to surgical repair, a large percentage of meniscus 
tears are not amenable to repair and, if treated surgically, are removed or debrided 
arthroscopically, a procedure known as arthroscopic partial meniscectomy.   
One type of tear that is not repairable is the degenerative meniscus tear.  This tear type 
usually has a horizontal component, or has a so-called “complex” pattern.  It has been reported 
in multiple large studies that about 60% of meniscus tears treated arthroscopically are 
degenerative tears (Christoforakis et al, 2005, Metcalf et al., 2004).  This tear type is associated 
with an older age group when compared with other tear types (Chirtoforakis et al., 2005).  These 
findings closely reflect our practice at the Palo Alto VA hospital, and are likely to represent the 
general VA experience. 
Degenerative meniscus tears are also associated with incipient osteoarthritis.  A review of 
articular cartilage findings at the time of arthroscopy has revealed that complex and horizontal 
cleavage meniscal tears are highly associated with an increased incidence and severity of 
cartilage degeneration compared with other types of meniscal tears (Christoforakis et al, 2005).  
Long term follow-up of patients with degenerative meniscus tears who undergo partial 
meniscectomy reveals that they develop radiographic osteoarthritis at a higher rate than 
patients who have other tear types (Englund et al., 2003), likely because their knees already 
had some degree of arthritis at the time of surgery. 
It is thus likely that about 60% of arthroscopic meniscectomy cases performed in this country, 
or roughly 380,000 cases annually, are performed on patients with degenerative meniscus tears 
and some degree of osteoarthritis.  This is important because it has been clearly shown in a 
recent prospective, randomized, placebo controlled clinical trial in a VA patient population that 
arthroscopic debridement of the knee for the diagnosis of osteoarthritis is no better than placebo 
surgery (Moseley et al., 2002).  Since nearly all patients undergoing arthroscopy and 
meniscectomy for degenerative meniscus tears also have some degree of chondromalacia or 
osteoarthritis, an important question that must be asked is:  Does arthroscopic meniscectomy 
for a degenerative meniscus tear provide a benefit beyond the placebo effect? 
Beyond the immediate effects that a patient undergoing meniscectomy for a degenerative 
tear may experience, another important concern regarding meniscectomy is the influence that 
meniscectomy has on the progression of osteoarthritis.  Meniscectomy is known to have a 
number of biomechanical effects on the knee that can result in osteoarthritis.  Meniscectomy 
dramatically alters patterns of stress in articular cartilage (Haemer et al., 2011, Baratz et al., 
1986) and alters the position of the femur in relation to the tibia (Netravali et al., 2010). 
Meniscectomy is used in multiple animal models to generate osteoarthritis (Appleyard et al., 
2003, Hashizume et al., 2010)  Patients undergoing meniscectomy, and even partial 
meniscectomy, for meniscus tears are at elevated risk for developing knee osteoarthritis 
compared to matched controls (Englund et al., 2003).  Yet in patients who have meniscus tears 
and end up having a meniscectomy it is unknown whether the meniscus tear itself was the 
reason for the elevated rate of late osteoarthritis, or whether the surgical procedure was the 

cause.  Given this information, another important question to be asked is:  Does arthroscopic 
meniscectomy for a degenerative meniscus tear alter the kinematics of the knee and accelerate 
osteoarthritis development? 
Answering these two questions, which correspond to the aims of the proposed work, would 
have an important effect on the treatment and rehabilitation of a very large group of veteran 
patients with degenerative meniscus tears and knee pain.    Optimizing rehabilitation of these 
patients with treatments that are proven to be efficacious, and eliminating costly, ineffective, or 
harmful treatments is an important goal of this study.  Answering these two questions can either 
justify the large expenditures of health care dollars presently used to surgically treat 
degenerative meniscus tears, or if the surgery is found to be ineffective or damaging, can 
identify a very important area for cost savings. 
 
Understanding mechanisms of osteoarthritis progression 
    Osteoarthritis is the fourth most common health condition served by the Department of 
Veterans Affairs (Kazis et al., 1998), and is the leading cause of disability in the United States 
(CDC 2001).  Across the general population, the prevalence of symptomatic knee arthritis in 
adults over age 45 was been estimated to be 17% (Jordan et al., 2007).  Twenty three percent 
of Veterans over age 50 are diagnosed with osteoarthritis (Kazis et al., 1998).  Clearly, there is 
an important need to understand the development and progression of osteoarthritis and to 
identify predictors of osteoarthritis progression.  Such and understanding would help to guide 
innovative early therapies for osteoarthritis of the knee and to monitor the effectiveness of such 
treatments. 
As a part of our effort to understand and monitor the progression of early osteoarthritis from a 
functional/biomechanical standpoint, and to understand the functional/biomechanical effects of 
meniscectomy that may lead to osteoarthritis, we ask in this study whether resection of an 
already damaged meniscal fragment leads to a kinematic change in the knee that has been 
associated with osteoarthritis progression in a number of different clinical settings - 
meniscectomy and ACL deficiency (Netravali et al., 2010, Andriacchi et al., 2006).   
It may be that the degenerative meniscus is, by objective mechanical and functional 
measures, biomechanically incompetent to the point where it no longer serves any protective 
role to the articular cartilage or any stabilizing role to the joint.  If this is the case, the kinematic 
changes that we have observed following arthroscopic meniscectomy (namely external rotation 
of the tibia in relation to the femur during the stance phase of gait) should be present prior to 
surgical removal of the torn meniscal fragment.  If this is the case, it may be that partial 
meniscectomy itself (the removal of the torn fragment of meniscus) does not change the 
kinematic positioning of the tibia in relation to the femur, and is not actually the cause of post-
meniscectomy osteoarthritis as has been implied in previous work (Englund et al., 2003).  In this 
situation, the higher rate of osteoarthritis seen years after knee arthroscopy and partial 
meniscectomy may simply be due to the damage to the joint that led to the damaged meniscus.  
This is the issue we are trying to address with Aim 2 of our study.  Assessing the biomechanical 
competence and function of the degenerative meniscus is central to the decision to remove the 
torn, but stable fragment. 
Similarly, it has been suggested that the knee with a degenerative meniscus tear already has 
incipient osteoarthritis (Englund et al., 2003), even if osteoarthritis is not evident on plan 
radiographs.  Recent work in the laboratory of Dr. Robinson (Wang et al., 2011) has revealed 
that there is an elevated level of activity in the complement cascade in the synovium of patients 
with early and end-stage osteoarthritis of the knee, with the most dramatic activation of the 
complement system observed in early knee OA.  Using a mouse model of medial meniscal 
transection (Kamekura et al., 2005) work in Dr. Robinson’s laboratory has been shown in this 
animal model of surgically-induced osteoarthritis that progression of osteoarthritis is dramatically 
slowed in genetic knockout mice that are missing enzymes involved in certain steps of the 

complement cascade.  Blocking of these critical steps in the complement cascade with 
antibodies has a similar effect. 
Whether intervening on the complement system would slow the progression of 
mechanically/surgically induced osteoarthritis is not yet known in humans.  In humans with 
advanced osteoarthritis undergoing total knee arthroplasty, elevated activity of the complement 
system has been established .  Although the Robinson lab has demonstrated increase 
activation of the complement system in early OA (Fig. below; Wang et al., 2011), whether 
meniscal tears are associated with activation of the complement system and alteration of gene 
expression in the synovial lining has not been previously investigated.  Establishing whether this 
is the case with joint fluid aspiration and a synovial biopsy of patients undergoing arthroscopic 
meniscectomy for a degenerative meniscus tear, since they are believed to be patients with 
early osteoarthritis, will be a major step in further understanding the role of complement in the 
progression of osteoarthritis and potentially developing pharmacologic intervention strategies to 
slow osteoarthritis progression.  This the focus of an exploratory aim of the proposed work. 
 
Preliminary Studies and Current Status of the Field 
Prospective Study on Arthroscopic Meniscectomy outcomes at the VA Palo Alto 
     We have performed a preliminary study on patients at the Palo Alto VA hospital undergoing 
arthroscopic meniscectomy (Mirza et al., 2011).  In this study, we prospectively followed 
patients presenting to the orthopedic clinic with meniscus tears and who underwent arthroscopic 
meniscectomy.  78 subjects with a mean age of 51 years scheduled for knee arthroscopy for 
meniscal tears were enrolled. 45 subjects were available for final review at one year. History of 
acute injury within 6 months of surgery, Kellgren-Lawrence arthritis grade, and MRI appearance 
of meniscus tear (degenerative or not) was recorded for each patient.  Pre- and one year 
postoperative WOMAC and WOMET were used to evaluate surgical outcome with statistical 
analysis done by ANOVA. 
     The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) (Bellamy et 
al., 1988) and the more recent Western Ontario Meniscal Evaluation Tool (WOMET) (Kirkley et 
al., 2007) are self-administered validated outcome tools for osteoarthritis of the knee and 
meniscal tears of the knee. 
The psychometric properties of the WOMAC have been extensively studied in a number of 
publications. The original publication by Bellemy (Bellemy et al., 1988) found a high level of 
responsiveness, Chronbach’s alpha greater than 0.85, acceptable validity testing against 
multiple other scales including the Lequesne, Bradburn, and Doyle, and superior efficiency over 
other measures. 
The psychometric properties of the WOMET in a population of patients with degenerative 
meniscal tears were recently published (Sihvonen et al., 2012).  Test-retest reliability 95% limits 
of agreement were 20.1 and -20.11 as a percentage of normal score.  Cronbach alpha score for 
total WOMAC was 0.91 and was greater than 0.7 for all domains.  Floor and ceiling effects were 
less than 30%.  The WOMET was significantly correlated to the Lysholm knee score (r=0.558, 
p<0.001) and the 15-D scale (r=0.311, p=0.002).  Construct validity and responsiveness were 
also established.  
Preoperative baseline WOMET and WOMAC scores were compared to postoperative values 
at one year. Subjects were also defined according to age (greater than 50 or younger), BMI, OA 
grade (K-L classification), meniscal tear type (complex or simple), smoking history (yes/no), 
psychiatric diagnosis (yes/no), and PTSD diagnosis (yes/no). Two orthopaedic surgeons 
evaluated the xrays and MRI films independently with discrepancy resolved through consensus. 
Other variables were identified through detailed chart review of diagnoses and parameters. 
Forty-five subjects completed one-year followup and were available for analysis.   WOMAC and 
WOMET scores improved significantly in the entire cohort at one year (p<0.0001).  Patients with 

OA grade 0-1 had greater improvements than those with grade 2-3. Mean differences in 
WOMET and WOMAC scores overall (95% CI, p-value) in 45 subjects at 1 year were 354 (224-
483; p<0.0001) and 561 (407-714, p<0.0001); respectively. Subgroup analysis based on lower 
OA grade (0 and 1) revealed mean differences in WOMET and WOMAC scores of 456 (290-
621, p<0.0001) and 656 (466-845, p<0.0001) at 1 year; respectively. Chronicity of symptoms 
and tear type had no effect on outcomes.  Other variables such as age, BMI, type of meniscus 
tear, smoking history, and psychiatric diagnosis had no significant impact on the results. 
     This preliminary study gave us experience recruiting and following arthroscopic 
meniscectomy patients and experience with the WOMAC and WOMET, the primary outcome 
measures for the current study.  We defined mean and standard deviation scores in our 
meniscectomy patient population that allow us to perform a power analysis for our proposed 
study.  Furthermore, we defined a covariate, radiographic severity of osteoarthritis, that appears 
to have an effect on outcomes.  This study lays a good foundation for the current study that is 
being proposed.  It strongly suggests the need for a prospective study on arthroscopic 
meniscectomy for degenerative tears that has a control group, as the improvement in the 
arthroscopic meniscectomy patient population we observed in our pilot study is comparable in 
magnitude to the improvements seen after placebo surgery (Moseley et al., 2002) and physical 
therapy (Kirkley et al., 2008) interventions for knee osteoarthritis.  
 
Effects of Meniscectomy on Gait and Functional Measures 
     We have recently completed a study with gait analysis on patients who have had 
arthroscopic medial meniscectomy (Netravali et al., 2010).  The menisci are known to influence 
the transverse plane movements (anterior-posterior (AP) translation and internal-external (IE) 
rotation of the knee during walking.  In that study we sought to determine the influence of partial 
medial meniscectomy on the kinematics and kinetics of the knee during the stance phase of gait 
by testing the differences in AP translation and IE rotation, knee flexion range of movement, 
peak flexion and extension moments, and adduction moments between the meniscectomized 
knees and the healthy contralateral knees in ten patient ranging from 45 to 79 years of age. 
 
 
Figures 1 and 2:  Kinematic and kinetic differences between knees with and without posterior 
medial meniscectomy (PMM)  (Figures from Netravali et al., J Biomechanics 2010) 
 
     We found that the primary kinematic difference was a significantly greater external rotation of 
the tibia through the stance phase of gait with eight of ten subjects demonstrating this pattern.  
Limbs that had undergone posterior medial meniscectomy also had lower peak flexion and 
extension moments compared to the normal limbs.  We interpreted this result as resulting in 
changes of tibio-femoral contact during walking, which could be a mechanism for initiating the 
process of post-meniscectomy osteoarthritis. 

     This study shows that we have the ability to identify changes in knee kinematics and kinetics 
after meniscectomy using our current gait analysis techniques.  A key piece of information that 
is missing, however, is the kinematics of the knee with the meniscus tear that has not been 
debrided.  Though we have seen these kinematic changes in knees during gait after 
meniscectomy, it is not clear whether these changes were actually caused by the meniscectomy 
or by the injury/meniscus tear itself.  This is an important distinction as it begins to probe the 
etiology of post meniscectomy osteoarthritis.  If we find that these kinematic changes in knees 
during gait are present only after meniscectomy, we would have reason to believe that post-
meniscectomy osteoarthritis is a result of the surgical intervention itself (partial meniscectomy) 
rather than just due to the meniscus tear. 
 
Relation between knee walking kinematics and spatial cartilage thickness distribution in the 
knee 
     We have done previous work relating the kinematics of walking on the spatial distribution of 
articular cartilage thickness in the knee (Koo et al., 2011).  Gait data and knee MR images were 
obtained from 17 healthy volunteers (age 33.2 ± 9.8 years). Cartilage thickness maps were 
created for the femoral and tibial cartilage. Locations of thickest cartilage in the medial and 
lateral compartments in the femur and tibia were identified using a numerical method. The 
flexion-extension (FE) angle associated with the cartilage contact regions on the femur, and the 
anterior-posterior (AP) translation and internal-external (IE) rotation associated with the cartilage 
contact regions on the tibia at the heel strike of walking were tested for correlation with the 
locations of thickest cartilage. The locations of the thickest cartilage had relatively large variation 
(SD, 8.9°) and was significantly associated with the FE angle at heel strike only in the medial 
femoral condyle (R(2)=0.41, p<0.01).  
 
 
 

 (Figs 3-5 from Koo et al., 2011) 
 
     The natural knee kinematics and contact surface shapes seem to affect the functional 
adaptation of knee articular cartilage morphology. The sensitivity of cartilage morphology to 
kinematics at the knee during walking suggests that regional cartilage thickness variations are 
influenced by both loading and the number of loading cycles. Thus walking is an important 
consideration in the analysis of the morphological variations of articular cartilage, since it is the 
dominant cyclic activity of daily living. The sensitivity of cartilage morphology to gait kinematics 
is also important in understanding the etiology and pathomechanics of osteoarthritis. 
 
Gait mechanics influence healthy cartilage morphology and osteoarthritis of the knee 
     In another study, the response of healthy and diseased cartilage of the knee to the 
mechanics of walking was examined, with the goal of providing insight into the relationship 
between the kinematics and kinetics of the knee during walking and the maintenance of 
cartilage health Andriacchi et al. 2009). The combination of information from three-dimensional 
thickness models of cartilage derived from magnetic resonance imaging and the analysis of the 
interaction between load at the knee and kinematic changes during walking associated with loss 
of the anterior cruciate ligament demonstrated the importance of considering walking mechanics 
as an important factor in the initiation and progression of osteoarthritis. In particular, this 
material suggested that knee cartilage becomes conditioned to loading and to the large number 
of repetitive cycles of loading that occur during walking and that healthy cartilage homeostasis is 
maintained as long as there are no changes to the normal patterns of locomotion, the structure 
of the knee joint, or cartilage biology. Thus, there is the potential for a degenerative pathway to 
be initiated when a condition such as anterior cruciate ligament injury causes the repetitive 
loading during walking to shift to a new location.  
 

 
(From Andriacchi et al., 2009) 
 
     The sensitivity of cartilage to the kinematic changes is illustrated with the anterior cruciate 
ligament-deficient knee and the regional variations in cartilage morphology (Figure 6). The 
material presented here supports the conclusion that individual variations in the range of loading 
and kinematics at the knee during walking can have a profound influence on the initiation and 
progression of osteoarthritis of the knee.  In this study, we will perform a similar analysis, but 
one that looks at the kinematic shifts associated with meniscus tearing or debridement.  Figure 
7 shows the conceptual model of osteoarthritis that forms the basis for this investigation. 
 
 
(From Andriacchi et al., 2009) 
Biomechanical benefit of retaining meniscal tissue in a horizontal meniscus tear 
  We performed and published a study looking at the horizontal meniscus tear pattern, which is 
the most common pattern of meniscus tear in the degenerative meniscus (Haemer et al., 2007).  
In this cadaveric study, we evaluated the contact stresses on the tibial articular surface when 
the meniscus is cut horizontally, simulating a horizontal meniscus tear.  We found that a cut in 
the meniscus itself does not change the contact area or contact stress substantially on the tibial 
articular surface.  Sparing one leaf was beneficial compared to resecting both leaves because 
resection of the second leaf reduced contact area an additional 15%. Similarly, mean pressure 
was increased 24% for single-leaf resection and an additional 27% for double-leaf resection. 
Peak pressure showed no differences with single- and double-leaf resections.  
 

Table 1:  Effects of tear and partial removal on tibial contact area and pressures 
(From Haemer et al., CORR 2007)  
 
  This study shows us that retention of all meniscal tissue in the setting of a stable horizontal 
meniscus tear may be beneficial to the articular cartilage of the joint from the perspective of 
contact area and contact stress.  If we find that, from a short term clinical standpoint, there is no 
symptomatic benefit to resecting any part of a stable horizontal meniscus tear, there is reason to 
believe from this study that the retained tissue will protect cartilage from reduced contact area 
and excessive contact stress. 
 
Proteomic survey of OA synovial fluid.  The Robinson lab subjected OA synovial fluid 
samples to 2-dimensional gel electrophoresis followed by mass spectrometric analysis (the 
Robinson Laboratory runs a mass spectrometry core for the VA Palo Alto).  183 distinct proteins 
were identified, and the DAVID bioinformatic algorithm (http://david.abcc.ncifcrf.gov/) was used 
to determine the pathways represented by the identified proteins along with the Bonferroni-
corrected P value for each pathway (Fig. 8 below).    
 
 
    
     OA-1                OA-2               OA-3        
Mass spectrometry:  193 proteins identified 
    Pathways identified                 # proteins      P value  
“Complement & coagulation”           24            3.8 X 10-21  
“ECM-receptor interaction”               17             4 x 10-10 
“Focal adhesion”                                24             4 x 10-10 
“Toll-like receptor signaling”            11               0.002 
“Cytokine-cytokine receptor”            16               0.01 
Fig.  8.  Proteomic survey of high abundance proteins in OA synovial fluid. Ten OA synovial fluids 
were separated by 2-dimensional gel electrophoresis (representative gel images presented), and protein 
spots and other gel regions were isolated, in-gel trypsin digestion performed, and an Agilent XCT ion 
trap mass spectrometer used to identify proteins. 193 distinct proteins were identified, and the DAVID 
website version 6.7 applied to identify the pathways represented.  The pathways identified, number of 
distinct proteins per pathway identified, and the Bonferroni-corrected P value are listed. 
 
 
 
Complement components are aberrantly expressed and activated in OA joints. 
Complement proteins identified in our proteomic survey of OA synovial fluid are listed in Figure 
9 below. Components of the classical (C1s & C4a) and alternative (factor B) pathways, the C3 
and C5 convertases, and the C5, C7, and C9 components of MAC were aberrantly expressed in 
OA (Wang et al, 2011).   
 
 
 
 
 
 
 

 
 
 
Fig.  9.  Complement components are aberrantly expressed and activated in OA joints. 
Complement proteins identified by 2-dimensional gel electrophoresis and mass spectrometric analysis 
as expressed in OA (n = 10) compared to healthy (n = 10) synovial fluids.In the schematic of the 
complement cascade, blue-filled circles denote the complement effectors and inhibitors identified as 
expressed in OA. 
 
Increased complement proteins in OA synovial fluid.  We used ELISA to verify the presence 
of complement in synovial fluid in OA, and found that C3a and MAC (C5b-9) levels are 
increased in OA compared to healthy synovial fluid, early in the course of OA (Fig. 10 below; 
Wang et al, 2011).  Elevated levels of MAC in OA synovial fluids have been reported previously. 
   
 
Fig.  10.  Complement is aberrantly 
hyperactivated in human OA.  ELISA 
quantification of C3a and of the soluble 
form of MAC in synovial fluids from 
asymptomatic healthy individuals (n 
=14) and from patients with early-stage 
OA (n = 52) or end-stage OA (n = 69). 
**P ≤ 0.01 by one-way ANOVA and 
Dunnett’s post-hoc test. 
 
MAC deposition in OA cartilage and synovium.   We performed immunohistochemistry on 
cartilage and synovium from patients with end-stage OA by using an antibody specific for MAC 
(C5b-9).  Staining with anti-C5b-9 demonstrates the presence of MAC on and around 
chondrocytes in the OA cartilage, and on and around synoviocytes in the OA synovium (Fig. 11 
below).  Our results are consistent with previous reports demonstrating C3 on articular surfaces 
and MAC on and around chondrocytes19 in OA cartilage (Wang et al, 2011).  
 
Fig.  11.  Immunohistochemistry demonstrates 
deposition of membrane attack complexes (MAC, 
C5b-9) on and around chondrocytes in OA cartilage 
and synoviocytes in OA synovium.  OA cartilage and 
synovium collected by the Stanford Arthritis Center at 
the time of arthroplasty was obtained and stained with 
an anti-MAC (C5b-9) antibody.  Samples were fixed, 
paraffin-embedded, and stained with antibody specific 
for C5b-9 or an isotype-matched antibody, and HRP-
conjugated secondary antibodies were used to detect 
primary antibody reactivity. Similar staining patterns 
were observed in 4 independent samples; 
representative images are presented.     

 
Activation of the complement system by OA cartilage.  In vitro complement assays were 
performed as described22.  Pulverized OA cartilage was added to human serum, and ELISAs 
were performed to quantify MAC production as a measure of complement activation.  Human 
OA cartilage activated MAC production over that observed with OA synovium or PBS (Fig. 12 
below).   We further demonstrate that the cartilage component fibromodulin is increased in OA 
synovial fluid and can directly activate the complement system to result in the formation of C5b-
9 (Fig. 13). 
 
 
 
Fig.  12.  OA cartilage induces production of 
MAC (C5b-9).  Pulverized OA cartilage (OA 
cart), OA synovium (OA syn), PBS (negative 
control), or sepharose (positive control) was 
added to normal human serum (NHS), and 
production of MAC quantified by ELISA at 
various time points.  OA cartilage, but not OA 
synovium, activated the complement system, 
resulting in production of MAC. 
 
 
Increased complement-effector, and decreased complement-inhibitor, gene expression in 
OA synovium.  To determine whether the increase in levels of complement effector proteins in 
OA synovial fluid (Fig. 13 below) is due to aberrant production of these factors by joint tissues, 
we performed hierarchical clustering of publicly available gene-expression datasets. Our 
analysis revealed two major clusters, one containing the expression profiles from OA patients 
and another containing the profiles from healthy individuals (Fig. 14 below; Wang et al, 2011).  
Surprisingly, we found a striking induction of transcripts encoding complement components of 
the alternative pathway (C3, C7, C4A, factor I, factor B, C9, C5) and a concomitant suppression 
of inhibitors of the alternative pathway (factor H, C1 inhibitor, C4-Acidic) in OA synovial tissue in 
both early  and end-stage OA synovial linings.  The converse was observed in healthy 
synovium.  These results suggest that complement-encoding genes are dysregulated in early 
and end-stage OA synovium.  
 
 
 
 
                        OA                    Healthy 
Fig.  13.  Fibromodulin activates the complement system to produce MAC (C5b-9) and is elevated 
in OA synovial fluid.  (a) Fibromodulin was added to 10% human serum and production of MAC (C5b-
9) was measured by ELISA.  P ≤ 0.01 by one-way ANOVA with Dunnett’s post-hoc test comparing PBS 
with fibromodulin, matrilin-3, aggrecan, or type II collagen.  Zymosan was used as a positive control.  (b) 
ELISA quantification of fibromodulin levels in synovial fluids from OA patients (n = 50) and healthy 
individuals (n = 9). **P ≤ 0.01 by Student’s t-test. 
 

Fig. 14.  Synovial lining of early and end-stage OA patients exhibits increased expression of 
genes encoding complement-effector proteins, and decreased expression of genes encoding 
complement-inhibitory proteins.  Cluster analysis of gene-expression profilings in microarray datasets 
from synovial membrane derived from early and end-stage OA patients were experimentally determined 
using Affymetrix Human U133 Plus 2.0 chipsand healthy controls (accession # GSE12021) were 
downloaded from the NCBI’s Gene Expression Omnibus (GEO).  For transcriptional profiling, end-stage 
knee OA synovial membranes were obtained from patients undergoing knee joint replacement and 
early-stage knee OA synovial membranes were obtained from patients undergoing arthroscopy for 
meniscal tears with cartilage degeneration but no full-thickness cartilage loss.  The results for the 
complement-related proteins identified by mass spectrometry (Fig. above) were extracted, subjected to 
hierarchical clustering, and displayed as a heatmap. Red = increased RNA expression; black = no 
difference; green = decreased RNA expression.   
 
Increased cytokines in OA sera and synovial fluids.  To follow up on our mass-spectrometry 
results, which included identification of proteins that characterize “Immunologic disorder(s)” (Fig. 
15 below), the Robinson lab used optimized protocols (Hueber et al, 2008) to perform Luminex 
analysis of the cytokines present in synovial fluid and serum samples derived from patients with 
OA or rheumatoid arthritis (RA) or from healthy individuals.  We show that, though low, levels of 
cytokines are significantly higher in sera from OA patients compared to healthy individuals (false 
discovery rate (FDR) < 0.05)(Fig.13 below, right panel). We also profiled cytokine levels in 
healthy sera, OA sera, OA synovial fluids, RA sera, and RA synovial fluids (FDR < 0.01) (Fig.15 
below, left panel).  Cytokine levels are slightly increased in OA sera compared to healthy sera, 
significantly increased in OA synovial fluids compared to healthy synovial fluids, and highest in 
RA sera and synovial fluids (Fig. 15 below, left panel).   
  
 
Fig. 15.   Increased cytokines in OA serum and synovial fluid.  The Luminex System was used for 
profiling of cytokines in sera and synovial fluid samples provided by the Stanford Arthritis Center, 
according to protocols optimized by the Robinson lab (Hueber et al, 2007).  SAM was used to identify 

statistical differences between levels of cytokines in healthy (normal) sera, OA sera, OA synovial fluid, RA 
sera, and RA synovial fluid, and statistically significant results are presented in the heatmap on the left 
(FDR < 0.01).  In the right panel, SAM identified cytokines increased in OA sera as compared to healthy 
sera (FDR < 0.05), the results subject to unsupervised clustering, and the output displayed as a heatmap. 
 
 
Imaging Background 
Joint Morphology in OA with MRI.  Magnetic resonance imaging offers excellent assessment 
of joint structure in OA {Conaghan, 2006}.  Although three-dimensional MRI can provide 
accurate quantification of cartilage thickness and volume, these change slowly in OA {Eckstein, 
2008}. Recent studies have shown focal cartilage thinning in a group of OA subjects in the 
weight-bearing regions in as little as one year {Wirth, 2010}. 
Other important joint structures 
such as the ligaments, menisci, synovium, and bone marrow that are active in the OA process 
have received far less attention than cartilage {Conaghan, 2006;Conaghan, 2004}.  
Conventional MRI of these structures is able to show internal derangements such as meniscal 
tears, which is a late finding and irreversible. However, early degenerative changes in 
fibrocartilage tissue such as ligaments and menisci are not routinely measured with 
conventional MRI due to the short T2 relaxation times of these tissues.  Short echo time or uTE 
imaging improves imaging in these tissues {Gatehouse, 2004} but requires specialized software 
and hardware.   
 
Structural information from conventional intermediate-weighted 2D fast-spin-echo {Boileau, 
2008} and 3D double-echo steady state (DESS) MRI can be summarized using semi-
quantitative scoring systems such as BLOKS or WORMS {Hunter, 2008;Peterfy, 2004;Felson, 
2010}.  The changes seen in OA pathology detected on routine MRI include joint effusion, 
synovitis, bone marrow lesions, and cartilage matrix.  These are useful to document the slow 
progression of OA but are insensitive to short-term changes in cartilage that may be reversible.  
Long-term assessment of regional cartilage thickness, as well as additional assessment of 
cartilage, menisci, and ligaments can be performed using DESS imaging {Eckstein, 
2006;Guermazi, 2009}, the current method used in the OAI. Joint changes such as cartilage 
volume and regional thickness are assessed using post-processing segmentation. Regional 
cartilage thickness has been shown to change a measureable amount using MRI in 18 months 
from the OAI data {Wirth, 2010}. 
 
 
Joint Physiology in OA with MRI.  Recent advances in MRI contrast mechanisms have the 
potential to probe the extracellular matrix of cartilage.  Several promising techniques that show 
early matrix change in OA include T2 mapping, T1p mapping, dGEMRIC, and sodium imaging 
{Burstein, 2006}.  An exciting new method of detection of glycosaminoglycan (GAG) by 
chemical exchange saturation transfer (gagCEST) has only recently been described {Ling, 
2008}. All of these methods can be difficult to use in multi-center trials, which has limited their 
application in studies of interventions in OA. Comparisons between these methods have also 
been difficult, owing to a lack of compatible software and hardware at any one institution. 
 
Measurement of the T2 relaxation time has been shown to be a reflection of the organization 
of the collagen network within the cartilage {Mosher, 2004}.  Increased T2 relaxation time is a 
marker for matrix breakdown, which may occur before cartilage volume or thickness loss 
occurs. T2 mapping is sensitive to magic angle effects and the hydration state of the cartilage.  
This makes T2 mapping less specific for collagen content and more of a reflection of overall 
cartilage structure. T2 mapping is usually done with a two-dimensional fast spin-echo approach 
that can take at least 10 minutes to cover an entire knee.  Two-dimensional imaging in this case 
is a significant limitation that results in errors in quantification due to slice gaps and partial 
volume effects.  
Several promising methods have been developed to assess cartilage GAG.  
Measurement of the relaxation of the spins in cartilage in the presence of a radio-frequency field 

or T1p imaging has been shown to be 
useful in detecting changes to the 
extracellular 
cartilage 
matrix 
{Borthakur, 2006}. Although T1p is 
sensitive to matrix changes in OA, 
there is some controversy as to the 
specificity of T1p for changes to 
glycosaminoglycans {Menezes, 2004}.  
Delayed gadolinium enhanced 
MRI of cartilage (dGEMRIC) is a well-
established MRI method to measure 
GAG content in cartilage {Burstein, 
2000}.  dGEMRIC has shown high 
accuracy and promise in the research 
setting, 
but 
requires 
intravenous 
injection of double-dose gadolinium 
contrast and a significant delay before 
image acquisition. dGEMRIC has 
been used to demonstrate that GAG 
loss in cartilage is reversible with an 
exercise intervention {Roos, 2005}. 
Use of dGEMRIC is also limited by 
concerns 
about 
high-dose 
administration 
of 
gadolinium 
and 
nephrogenic sclerosing fibrosis, a rare 
but serious connective tissue disorder {Weinreb, 2009}. 
Direct imaging of sodium with MRI provides a non-invasive assessment of cartilage GAG 
content.  Sodium is the positive ion associated with the negatively charged GAG side chains in 
cartilage, so sodium provides a direct measure of GAG in cartilage {Borthakur, 2006}.  MR 
imaging of sodium has traditionally been limited by low concentration, low gyromagnetic ratio, 
and short T2 relaxation times.  However, recent advances in MR imaging using non-Cartesian 
acquisition strategies have enabled acquisition of volumetric sodium data in cartilage at clinical 
field strengths in vivo {Staroswiecki, 2010}. 
Diffusion MRI may also be sensitive to cartilage GAG content.  A recent study showed 
excellent correlation between ADC and GAG content in artificially depleted cartilage specimens 
{Raya, 2011}. Diffusion-weighted MRI of cartilage has been attempted in vivo with limited 
success {Azuma, 2009;Miller, 2004}.   
DESS is a rapid 3D method that produces two images:  one with high signal and one with more 
T2 contrast.  {Hardy, 1996}. Normally these images are simply added, giving sufficient contrast 
for cartilage segmentation {Eckstein, 2006}, as has been used extensively in the OAI. More 
recently, it was described that the signal ratio in DESS may be used to provide an 
approximation to a T2 map, with much higher spatial resolution and shorter scan times than 
conventional T2 mapping {Welsch, 2009}.  We have extended this further by incorporating fat 
suppression and varying the flip angle and spoiler gradient, to modulate the diffusion sensitivity 
{Buxton, 1993}. This is based on our pervious work in cartilage diffusion imaging.  Overall, this 
new approach offers an efficient, high-resolution single-acquisition of 3D images for 
segmentation, T2 maps, and ADC measurement.   
Figure 16 summarizes our validation of both T2 and ADC measurement using quantitative DESS 
(qDESS) {Staroswiecki, in press}.  In 5 healthy subjects, we acquired qDESS images with 
different diffusion weighting, and fit a signal model to generate T2 and ADC maps.  Both were 
compared with spin-echo measurements of T2 and ADC, with excellent agreement.  Additionally, 
 
 
Figure 16:  Using qDESS acquisitions in 8 minutes, sum 
images (top) from acquisitions with low and high diffusion 
weighting can be used for segmentation.  Further 
processing provides Apparent Diffusion Coefficient (ADC) 
and T2 maps (middle).  Controlled tests in phantoms 
show high accuracy of qDESS T2 and ADC values 
compared with spin echo (SE) methods (bottom).  

we validated accuracy of qDESS in phantoms of varying T2 and diffusivity.  The agreement with 
standard spin-echo methods is excellent.  Although the validation of diffusion measurement is 
preliminary, substantial work has already been performed to validate DESS for segmentation 
{Wirth, 2009} and semi-quantitative scoring {Roemer, 2009}.  qDESS is particularly promising 
for cartilage assessment, as it avoids the blurring and signal loss of spin echo methods as well 
as the image distortion in most diffusion-weighted imaging sequences.  
 
Imaging of muscle cross sectional area:  Muscle cross sectional area measurement can 
provide additional information regarding the functional consequences of meniscectomy.  We will 
image the thigh of patients at enrollment, and at two-year follow up to determine if patients 
undergoing meniscectomy vs. lavage have greater changes in muscle cross sectional area.  
Images will be obtained using a rapid axial thigh scan with IDEAL fat/water separation using a 
3D spoiled gradient echo sequence.  The data will have 1 mm in-plane resolution and 5 mm 
slice thickness.  Acquisition time will be approximately 2 minutes.  Muscle cross sectional area 
will then be determined as previously described {Walton 1997}. 
 
Research Design and Methods  
In this study we propose a prospective, randomized, blinded, and controlled clinical trial of 
arthroscopic meniscectomy in patients between the ages of 45 and 70 with degenerative 
meniscus tears.   
 
Patient Selection: 
Subjects will be recruited from the orthopedic clinic at the VA Palo Alto Healthcare System. 
Eligible subjects will meet the following inclusion criteria: 
 
1.  Age between 45 and 70 years 
2.  Degenerative meniscus tear as seen by a standard clinical MRI scan 
3.  A complaint of “mechanical symptoms” which would include popping, catching, or locking of 
the knee 
4.  Persistent symptoms for a minimum of three months despite conservative management 
including anti-inflammatory medications and physical therapy 
5.  Patient is enrolled for arthroscopic meniscectomy 
6.  The subject agrees to study follow-up schedule and signs informed consent. 
 
The following exclusion criteria will be enforced: 
 
1.  Radiographic osteoarthritis of the knee in any compartment that is greater than KL grade 2   
2.  Prior knee arthroscopy within two years of study enrollment 
3.  Unable to have an MRI scan 
4.  Does not agree to participate 
 
General Study Plan: 
 
Patients who satisfy the inclusion and exclusion criteria and are scheduled for arthroscopic 
meniscectomy will be approached during their preoperative visit to participate in the study.  
They will be enrolled when they give informed consent.   
 
Preoperative study related evaluation: 
 
Prior to undergoing surgery, the patient will have the following evaluations: 

1.  The patient will fill out the WOMET (Kirkley et al., 2007) and WOMAC (Bellamy et al., 1988) 
surveys. 
2.  The patient will undergo a gait analysis 
3.  The patient will have MRI of the knee and thigh. 
4.  The patient will have standing radiographs of the affected knee. 
 
Evaluation at the time of surgery: 
 
At the time of surgery, the patient will be randomized to treatment with either an arthroscopic 
partial meniscectomy or arthroscopic lavage.  Randomization will be done by opening a sealed 
envelope in the operating room prior to the procedure. To ensure balanced numbers in the two 
surgical conditions, especially at the time of the interim look, randomization will be done by 
permuted blocks of size 10, thereby ensuring 5 patients in each group at every increment of 10 
enrollees. 
 
Upon initiation of the surgery, a sample of synovial tissue and synovial fluid will be obtained for 
biochemical analysis.  During the operation, the status of the knee joint will be documented.  
This will include classifying the degree of chondromalacia according to the Outerbridge 
classification in all three compartments of the knee, and documenting the geometry and pattern 
of meniscus tear type.  Video and photographs will be taken to assist with this documentation 
and will be stored in a secure manner. 
 
During the operation, the meniscus will be carefully probed.  If a large unstable flap of tissue can 
be displaced into the articulation (such as a bucket handle tear) this torn fragment will be 
debrided regardless of the result of randomization.  This will be done as it is widely believed that 
it is inappropriate to leave such an unstable tear untreated.  Any other tear types that do not 
result in an unstable flap that can be displaced into the articulation will be either retained or 
debrided, depending on the result of randomization. 
 
All postoperative contact from this point forward will be made by study personnel who were not 
involved in the surgery and who do not have knowledge of the randomization result.   
 
At 2 weeks and 6 weeks: 
 
The patient will have regularly scheduled clinic visits at 2 and 6 weeks that are not a part of the 
study but are just a part of the routine postoperative care of knee arthroscopy patients.  
Postoperative care as deemed necessary by the treating physician will be provided and could 
include pain and/or anti-inflammatory medications.  Physical therapy is rarely needed.  All 
provided treatments will be recorded in the chart. 
 
Evaluation at 3 months: 
 
1.  The patient will fill out WOMET and WOMAC surveys. 
2.  The patient will undergo gait analysis. 
3.  The patient will have an MRI of the knee 
 
Evaluation at 6 months: 
 
The patient will be contacted to fill out WOMAC and WOMET surveys. 
 
Evaluation at 12 months: (Primary outcome time point) 

 
1.  The patient will fill out WOMAC and WOMET surveys 
2.  The patient will undergo gait analysis 
 
Beyond this time point, patients will be followed for an additional year to address the exploratory 
aims of the study, particularly those having to do with cartilage thinning and radiographic 
progression of osteoarthritis.  We acknowledge that the information gathered from this point 
forward may be underpowered, but it will serve as preliminary data for future grant applications.   
 
Evaluation at 18 months: 
 
The patient will be contacted to fill out WOMAC and WOMET surveys. 
 
Evaluation at 24 months: 
 
1.  The patient will fill out WOMAC and WOMET surveys. 
2.  The patient will have standing plain radiographs to assess for progression of osteoarthirtis 
3.  The patient will have MRI of the knee and thigh 
Subjects will remain blinded with regards to treatment until the conclusion of the study.  At 24 
months will ask them if they learned of their treatment and if so, how.   
 
The subjects will be compensated $100 for study-related travel each time they visit the 
laboratory. 
 
Detailed Description of Study Techniques: 
MRI timing – patient experience and control of activity prior to scan: 
Subjects will not have performed any strenuous activity for two hours prior to the MRI.  
Subjects will always undergo MRI testing following gait testing.  Thus, all subjects will 
have similar mechanical conditions prior to their MRI.  This will reduce the potential for 
confounding short-term effects that could influence articular cartilage thickness 
measurements. 
 
MRI Sequences to be used in this study 
 
The imaging protocol at 3.0T (Table 2) in these subjects will last one hour, and including qDESS 
imaging with T2, diffusion, and cartilage and joint morphology, T1p mapping as described above, 
and sodium MRI. To assess morphology as well as bone marrow edema, we will use 
intermediate-weighted (IW) 2D-FSE with fat suppression {Boileau, 2008}. Long-term 
assessment of regional cartilage thickness, as well as additional assessment of cartilage, 
menisci, and ligaments will be performed using DESS imaging {Eckstein, 2006;Guermazi, 
2009}, the current method used in the Osteoarthritis Initiative. This baseline morphologic 

imaging capability gives us the same capacity to follow joint changes using post-processing for 
cartilage volume, regional cartilage thickness changes, and internal derangement scored by 
BLOKS {Hunter, 2008;Peterfy, 2004;Felson, 2010}.  
 
 
 
 
We will compare and correlate the results of multiple standard imaging markers of OA with 
our new methods. All (established and novel) sequences in this protocol will have varying 
degrees of change in the post-menisctomy population (Figure 17). We will directly compare in 
vivo sodium, diffusion, and T1p imaging for sensitivity to GAG changes in cartilage in a moderate 
number of OA patients. We will analyze the T2 maps obtained from qDESS to assess regional 
variations of the collagen matrix.  Diffusion weighted MRI is anticipated to show greater 
sensitivity to changes in the GAG matrix, so this may be a leading indicator of matrix change.  
The data from these comparisons will be rich, allowing us to correlate changes in cartilage GAG 
with bone marrow edema, meniscal pathology, and changes seen in in T2 and ADC using 
qDESS. 
 
MR Image Segmentation : 
The first step of creating surface models from MR images is delineating boundaries of 
objects in two-dimensional slices. The boundary detection of an object in image has 
been one of important subjects in computer vision field. Our approach to this open and 
extensively studied problem is a semi-automatic method, similar to techniques described 
in the literature [Falcão, 1998, Stammberger, 1999, Steines, 2000]. We use a B-Spline 
Snake method with manual initialization to detect the cartilage boundary on a single MR 
image. In order to fit the B-spline snake to the image data, an energy minimization 
algorithm is employed. The cost function is composed of internal energy, image energy 
and constraint energy.   Accuracy and precision of this cartilage thickness measurement 
technique has been studied and reported (Koo et al., 2009).  Ability to see changes in 
cartilage thickness at the two-year time point has been demonstrated previously (Wirth 
et al., 2009). 
 
Gait Analysis  
Gait analysis in this study will be performed with a point cluster technique (Dyrby and 
Andriacchi, 2004; Alexander and Andriacchi 2001).  The point cluster technique was 
developed to better account for skin movement during gait analysis. Skin movement 
relative to the underlying bone is a primary factor limiting the resolution of detailed joint 
movement using skin-based system. In most cases only large motions such as flexion 
extension have acceptable error limits with skin-based marker systems. Skeletal 

movement can be measured using alternative approaches to a skin-based marker 
system.  These approaches include electrogoniometers, bone pins external fixation 
devices and single plane fluoroscopic techniques. All of these methods are invasive or 
expose the test subject to radiation. Therefore, the widespread applicability of these 
methods is limited. A method described as a point cluster technique (PCT) permits direct 
in vivo measurement of the six-degree of freedom motion of the femur on the tibia while 
performing activities of daily living. A key feature of PCT method relative to fluoroscope 
or other imaging methods is the ability to acquire unencumbered motion measurements. 
Artifacts associated with the laboratory environment causing the subject to walk in an 
unnatural manner are a major potential source of error in the interpretation of human 
movement. The method proposed in this study avoids placing fixtures tightly strapped to 
the limb segments or requiring the subject to move in a limited fixed field of view 
required by fluoroscopic, radiographic or magnetic resonance imaging techniques. 
 
Gait Analysis Protocol: Each subject will be tested standing in an anatomical position, 
during level walking and finally during stair ascent and descent. The level walking 
measurements include six stride cycles for each side over a range of walking speeds. 
The subject is instructed to walk at a comfortable speed (normal), slower than normal 
and faster than normal. Typically, this protocol produces gait measurements over a 
range of walking speeds.  The stair climbing protocol consists of walking up a set of 
steps with a rise of 21cm and run of 23cm. The first step of the staircase is placed on the 
forceplate in order to record the forces during the lifting motion of stairclimbing. Again, 
three trials for each leg will be captured for ascent and descent. 
 
The instrumentation to capture the skin-based marker data includes an eight camera 
opto-electronic system for 3-D motion analysis, a multi-component force plate for 
measurement of foot-ground reaction force and a computer system for acquisition, 
processing and analysis. Multiple video cameras acquire data with the subject during 
activities of interest. The over-abundance of markers (Figure 18) on each limb segment 
is used to define a cluster coordinate system (Figure 19), which is tied to an anatomically 
relevant coordinate system calculated with the subject at rest. 
 

 
Nine markers are placed directly over bony landmarks and fifteen others evenly 
distributed on the anterior and lateral portions of the thigh and shank (Figure 18). 
Techniques described in the literature are used to locate these bony landmarks. The 
femoral medial-lateral axis runs through the trans-epicondylar line (a line drawn between 
the medial-lateral femoral epicondyles).  The midpoint of this axis is the origin.  The 
inferior-superior axis runs parallel to the long axis of the femur, passing through the 
midpoint of the trans-epicondylar line.  The anterior-posterior axis is the cross product of 
the medial-lateral and inferior-superior axes.  The final position of the inferior-superior 
axis is made orthogonal to the anterior-posterior and medial-lateral axis.  For the shank 
segment, the tibial coordinate system begins with the medial-lateral axis running through 
the most medial and lateral edges of the plateau.  The inferior-superior axis is 
perpendicular to the medial-lateral axis passing through the tibial eminence.  The 
anterior-posterior axis is the cross product of the medial-lateral and inferior-superior 
axes. 
 
Kinetic and kinematic data is acquired through an eight camera motion analysis system 
with Qualisys MCU 240 cameras controlled by Qualisys Track manager software.  A 
Computer Boards DAS-1602 analog to digital converter card provides synchronized 
force data from a Bertek 4060-10 force plate.  The software and hardware are housed 
on a Pentium based personal computer, with 2 GB RAM and 60 GB hard disk space.  
The eight cameras are positioned in an arc approximately 1.5 meters from the center of 
the measurement volume on one side of a 10 meter walkway.  
Gait analysis will be carried out at three months after meniscectomy, and again at 12 
months after meniscectomy.  The three month gait analysis data on peak adduction 
moment and positioning of the tibia with respect to the femur will give us an idea of how 
quickly changes are manifest, but will not be the primary outcome time point. 
 

Sensitivity of MRI to detect articular cartilage thickness changes 
We have investigated whether MRI can detect articular cartilage changes in a 1-4 year time 
window following soft tissue injury to the knee.  In this particular study, ACL injury was the 
model, and the purpose of this study was to test the feasibility that cartilage thinning (relative to 
the healthy contralateral knee) could be detected in period of approximately 4 years or less past 
ACL injury in reconstructed knees.  
Twelve subjects with unilateral ACL reconstructions and no other history of serious lower limb 
injury (avg 38 yrs, 1.7 m, 68 kg, 4 male, 3.0 mo injury to reconstruction, 9-48 mo past 
reconstruction) were recruited for the study. All subjects were reconstructed within 6 months 
after injury.  Subjects underwent bilateral, non-weightbearing 1.5T MR imaging. Tibial articular 
cartilage were segmented from knee MR images and reconstructed into three-dimensional (3D) 
cartilage thickness maps and the cartilage models from the right knee were mirrored and 
registered to the cartilage models from the left knee using surface matching techniques. The 
thickness maps were compared point-by-point and made into difference maps. The thinning 
volume in the weight-bearing region of the medial tibial plateau, normalized by its surface area, 
was calculated for the ACL reconstructed knees.   
The results (Figure 20) suggest that articular cartilage thinning can be detected relatively early 
(15 months) after soft tissue injury to the knee.  These preliminary data show that our MR-based 
measurement of cartilage thinning has adequate sensitivity to detect early patterns of 
morphological changes after ACL injury.  These methods will be applied in this study towards 
investigating articular cartilage thickness changes after meniscal injury and meniscectomy. 
 
 
Figure 20.  Medial tibial cartilage thinning with time after ACL injury in ACL reconstructed patients.  The vertical 
red line is at 15 months after injury. 
 
Biomarker analysis of synovial and serum samples 
 
We will test the hypothesis that increased complement activation, levels of inflammatory 
cytokines and/or levels of cartilage metabolism biomarkers are associated with accelerated 
cartilage loss.  Biomarkers of cartilage metabolism (Table 3 below) as well as inflammatory 
cytokines (Table 4 below) will be measured as indicated.  The rationale for characterizing 
inflammatory cytokines, including IL-
-6 and TNF, is based on the putative role of these 
cytokines in driving low-grade inflammation that might contribute to the pathogenesis of 
OA.  Studies on human samples and in mouse models have suggested a role for IL-
and 
other cytokines in OA pathogenesis.  Further, IL-
signals arising from painful stimuli and may thereby exacerbate gait dysfunction in OA.   The 
rationale for analyzing complement components is based on data from our laboratory (Wang et 
al, 2011) demonstrating elevations of complement components in OA synovial fluid and tissue, 
and on our data demonstrating that C5-deficient mice are protected against OA (Wang et al, 
2011).  The cartilage degradation product COMP have been shown by Dr. Andriacchi’s 

laboratory to be elevated following exercise, and certain markers of cartilage degradation or 
synthesis are thought to reflect cartilage turnover, disease severity, or disease progression in 
OA.  The metalloproteinases (MMP) 3 and 13 mediate the proteolytic digestion and subsequent 
breakdown of cartilage in OA.  For certain markers, such as certain collagen degradation 
products, there are findings suggesting that urine provides a more reliable sample source as 
compared to serum.   We will use the sample source previously demonstrated to be most robust 
for detection of the biomarker.  We will use commercially available ELISA/EIAs (Tables below) 
to measure the levels of select complement components, cytokines, and cartilage metabolism 
biomarkers in serum and synovial fluid samples.      
    
Table 3.  Markers of cartilage metabolism to be measured in serum and/or synovial fluid (SF).   
Description 
Biological 
fluid to be 
tested 
Symbol 
Units 
Average (Standard 
deviation) 
Kit source 
Cartilage oligomeric matrix protein 
serum 
COMP 
U/L 
12.62(4.2) 
Pacific Biomarkers 
Hyaluronic acid 
serum 
HA 
ng/ml 
11.4(4.5) 
Corgenix 
Chondroitin sulfate 846 
serum 
CS-846 
ng/ml 
 
Ibex 
Matrix metalloproteinase-3 
serum, SF 
MMP-3 
ng/ml 
64(199) 
RnD Systems 
Matrix metalloproteinase-13 
serum, SF 
MMP-13 
ng/ml 
54(18) 
RnD 
Type II collagen neoepitope 
Serum  
C2C 
ng/ml 
 
Systems 
Keratan sulfate  
serum 
KS-5D4 
ng/ml 
27(19) 
Ibex 
  
 
 
Table 4. Markers of complement activation and inflammation. 
Description 
Biological 
fluid to 
betested 
Symbol 
Units 
Average 
(Standard 
deviation) 
Kit source 
High-
sensitivity C-
reactive 
protein 
serum 
hsCRP 
mg/L 
2.5(1.7) 
Hemagen Diagnostics 
Tumor 
necrosis 
factor-alpha 
serum, SF 
TNF 
pg/ml 
12.97(23.52) 
Bio-Rad 
Interleukin-
1 
serum, SF 
IL-1 
pg/ml 
2.74 (2.77) 
Bio-Rad 
Interleukin-6 
serum, SF 
IL-6 
pg/ml 
0.09 (0.8) 
Bio-Rad 
Complement 
C3a 
Serum, SF 
C3a 
ng/ml 
103.3 (19.7) 
BD, OptEIA 
Complement 
C5b-9 
SF 
MAC 
ng/ml 
 
BD, OptEIA 
 
 
Multiplex cytokine analysis.  The rationale for multiplex cytokine profiling stems from the putative 
role of cytokines in driving low-grade inflammation, which might contribute to the pathogenesis 
of OA.  Studies on human samples and in mouse models have suggested a role for IL-
other cytokines in OA pathogenesis.  Further, IL-
signals arising from painful stimuli and may thereby exacerbate gait dysfunction in OA.  We 
identified a panel of cytokines that are elevated in severe OA (KL=4) compared to less severe 
OA (KL<4) (Fig. 3.5).  Using protocols optimized by the Robinson Laboratory (Hueber et al, 
2007), we will use a 50-cytokine BioPlex bead array (Table 5 below) and the Luminex System 
(the Robinson Lab possesses a Luminex200 system and a Bio-Rad automated magnetic bead 
washing system) to measure the levels of 50 cytokines in all synovial fluid and serum samples 
collected.    
 
 

 
Table 5. The 50-cytokine panel to be measured by BioPlex bead array. 
IL-1  
IL-6   
IL-12  
IL-16  
MIP-1b  
IL-1  
Eotaxin   
CTACK  
LIF  
-NGF  
IL-1ra   
IL-7   
IL-13   
IL-18  
PDGF-bb  
IL-2Ra  
FGF basic   GROa  
MCP-3  
SCF  
IL-2   
IL-8   
IL-15   
IP-10  
RANTES  
IL-3  
G-CSF   
HGF  
M-CSF  
SCGF-  
IL-4   
IL-9  
IL-17  
MCP-1 
TNF-  
TRAIL 
GM-CSF   
ICAM-1  
MIF  
SDF-1  
IL-5 
IL-10   
IL-12p40  
MIP-1  
VEGF  
VCAM-1  
IFN-   
IFN-2  
MIG  
TNF-  
 
 
Power calculations & bioinformatic analysis.  We will test the hypothesis that increased 
complement activation, cartilage metabolism and/or inflammatory biomarkers are associated 
with accelerated cartilage loss.  We will explore use of (i) predefined indexes of markers of 
cartilage metabolism (Table 3 above) and markers of inflammation (Table 4 above), and (ii) a 
combined multivariate test.  For the predefined indexes of markers, we will standardize each 
marker to have standard deviation 1, so an average of 8 independent markers would have a 
variance 1/8, and an average of 6 a variance of 1/6.  For the combined multivariate testing for 
the cartilage metabolism and the inflammatory markers, we will use 8 and 6 degrees of 
freedom, respectively, in conjunction with a multivariate Hotelling's T-test.   Power calculation:  
So to achieve an effect (difference in mean index score) of .25 standardized units using a two-
sample-test at (0.05 two-sided, power 0.8) would require 29 samples in each group for the 8-
marker index, and 43 per group for the 6-marker index. 
 
 
Statistical Analysis 
 
Randomization: 
We will explicitly test if randomization achieved balance between the experimental groups on 
potentially confounding variables such as age, gender, and body weight. However, confounding 
may still operate even if the differences between the groups are not statistically significant. 
Therefore, we will conduct two secondary analyses in which imbalances in important potential 
confounding variables (duration of symptoms, grade of chondromalacia found on arthroscopic 
evaluation of the joint, radiographic severity of arthritis (Kellgren-Lawrence), and diagnosis of 
depression) will be addressed. First, we will simply add these covariates to the primary 
regression model. However, estimating so many more parameters will inherently reduce the 
statistical power of the test of the intervention effect. Our second approach solves this problem 
by first calculating a propensity score (the probability of being in the meniscectomy group based 
on pre-treatment variables) for each patient, and then using the propensity scores as regression 
weights in the main regression analysis. This is a state of the art approach for estimating 
treatment effects in the presence of potential confounding. 
 
Aim 1:  To test the clinical benefit of arthroscopic meniscectomy in the setting of a stable 
degenerative meniscus tear. 
     Hypothesis 1a:  The 12 month WOMAC score will be our primary outcome measure for this 
aim and the endpoint for this power analysis.  The WOMAC is a validated osteoarthritis outcome 
tool that is widely used to assess the severity of pain, stiffness, and function due to 
osteoarthritis.  A 20% improvement in the total WOMAC score is considered to be clinically 
important (Kirkley et al., 2008).  In a preliminary study, we evaluated a cohort of 45 patients 
undergoing arthroscopy and meniscectomy at our institution (Mirza et al., 2010).  We found a 
mean preoperative WOMAC score of 1296 with a standard deviation of 392.  Twenty percent of 
the mean baseline score of 1296 is 260.   
 
To ensure patient safety, we are incorporating in our analysis an interim look at the results by 
the DSMB to ensure that one group does not have dramatically superior results to another 
group.  In addition, the DSMB will assess subject attrition rates by group and adverse events.  

This will take place after 25% of the total planned number of subjects complete the study.  This 
analysis will include assessment of drop-out rates and adverse events as well. 
 
Setting the experiment-wide alpha at 0.05 and power at 80%, sample sizes of 37 and 37 
achieve 81% power to detect a difference of 260 between the group means with standard 
deviations of 392 and 392 at a significance level (alpha) of 0.05 using a two-sided independent 
sample t-test. These results assume that 2 sequential tests are made using the O'Brien-Fleming 
spending function to determine the test boundaries.  The interim look will thus take place when 
the first 20 subjects (25% of the total 74) complete the 12 month assessment. The analysis 
assumes that we will stop the trial if either condition is superior. The critical t-value will at the 
interim look will be +/- 4.3326.  If the trial continues, the final analysis will use a critical t-value of 
1.96. Sensitivity analyses will be conducted with t-tests on the baseline-to-12-month change 
scores.  
 
74 subjects will thus be needed to complete the trial.  Over a one year period we will expect to 
have a 10% lost to follow-up rate.  We will thus plan to enroll 82 subjects into the study. With a 
70% recruitment rate we will need to have 117 candidate patients for this study.  In calendar 
year 2011, we performed 66 arthroscopic meniscectomies at our facility.  Assuming that 70% of 
these cases involved stable degenerative tears, we would have 46 candidate patients per year.    
It would thus take us approximately 2.5 years to recruit enough patients for the study if we were 
to operate at last year’s rate.  We presently have approximately 100 patients for knee 
arthroscopy on our waiting list for surgery, which makes it likely that we could accomplish this 
goal more rapidly. 
 
Hypothesis 1b:  Should we fail to find a difference in 12 month WOMAC scores, we will test the 
hypothesis that the WOMAC scores in the arthroscopy and lavage condition are at least as 
good as (non-inferiority) the menisecomy by setting "d" the largest difference in WOMAC scores 
which we consider to be clinically meaningless to 15% of baseline, or 194 points.  We will then 
calculate 90% confidence limits for the difference in means for the two groups and determine 
whether these confidence limits lie within the -194 to 194point interval. Since there is no danger 
to patients if this hypothesis is found to be true, this hypothesis will not be subject to an interim 
analysis.  We will assume that the standard deviation of the means is 392.  With these numbers, 
the sample size of 74 and alpha = .10 and yields power = .80. 
 
Aim 2:  To test the functional effect of arthroscopic meniscectomy in the setting of a 
degenerative meniscus tear. 
 
Hypothesis 2:  Subjects randomized to arthroscopy and meniscectomy will have greater 
changes in tibio-femoral rotation, knee adduction moment, and knee flexion moment at 12 
months following surgery when compared to subjects randomized to arthroscopy and lavage. 
 
Calculations were performed to estimate the necessary sample size for the endpoints of Aim 2 
of changes in tibio-femoral rotation, knee adduction moment, and knee flexion moment. In order 
to keep the family-wise error rate at .05, each comparison will be made with an independent 
sample t-test with alpha = 0.0167. To reject the null hypothesis that changes in tibio-femoral 
rotation will not differ between the intervention (meniscectomized) knees and control (non-
meniscectomized knees), data from a similar study performed in our laboratory evaluating tibial 
rotation using the same techniques between meniscectomized knees and intact knees was 
used (Netravali et al., 2010). In that study, we found a 3.2 degree difference in tibio-femoral 
rotation in meniscectomized knees when compared to intact contralateral knees using a t-test. 
The standard deviation of the measurements in the meniscectomized knees was 3.8 degrees.  
Thus, to detect a difference of 3.2 degrees tibio-femoral rotation in the meniscectomized group 

versus no change in the intact group, with an alpha of 0.0167 and 74 total patients, power of 
87% will be achieved.  
 
In addition, we would be interested to detect a change in peak adduction moment of about 10% 
of baseline value. This corresponds to a change of 0.35%BW*ht (Netravali et al., 2010).  Prior 
work looking at changes in knee adduction moment with intervention find a standard deviation of 
the difference in peak adduction moment with the intervention to be 0.35%BW*ht.  With an 
alpha of 0.0167 and 74 total patients, power of 94% will be achieved. 
 
Finally, we are interested in detecting a change in peak flexion moment of about 10% baseline 
value.  This corresponds to a change of 0.3%BW*ht (Netravali et al., 2010).  Assuming a 
standard deviation of the flexion moment of approximately 0.35%BW*ht.  With an alpha of 
0.0167 and 74 total patients, power of 89% will be achieved. 
 
Missing Data: 
All analyses will be on the intent-to-treat sample. To address missing data at 1 year (and other 
time points), we will use a multiple imputation strategy that minimizes potential attrition bias.  
Ten datasets will be imputed with draws from the theoretical complete data distribution using the 
Multivariate Imputation by Chained Equations (MICE) program implemented in the R statistical 
language.  All analyses with these data will be conducted on the imputed datasets and 
combined to yield the final parameter estimates and inferences. 
 
 
 
 
Timeline and Targeted/Planned Enrollment Table: 
 
                                         
 
Note:  we will assess the success of our recruitment at the end of 10 months and double our rate of 
surgery (and thus our opportunities for recruitment at the preoperative evaluation) if we find ourselves 
behind in recruitment efforts.