Driban, J.B.

Lo, G.H.

McAlindon, T.E.

Price, L.

Zhang, M.

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A magnetic resonance imaging based rapid knee cartilage quantification method for the lateral tibiofemoral compartment: Data from the osteoarthritis initiative 

Figure 1(a), (c) Lateral Femur and Tibia denuded projection and 18
informative locations on the coordinate system, (b), (d) Corresponding
denuded peak on the cartilage map. Note: cartilage maps were rotated to
better display informative locations.
Abstracts / Osteoarthritis and Cartilage 23 (2015) A82eA416 A209mechanics, particularly mechanical stress in the cartilage, is largely
responsible for disease pathology. Since stress in the cartilage is highly
dependent upon the geometry of the joint, among other biomechanical
and physiological factors, it is not surprising that imaging biomarkers
based on high ﬁdelity bone shape descriptors are signiﬁcantly different
in individuals who are at risk of developing radiographic knee OA
(RKOA) and those who are not, and that baseline subchondral bone
shape is a signiﬁcant predictor of the onset of RKOA 12-months prior to
onset. We tested the hypothesis that high ﬁdelity descriptors of distal
femur subchondral bone shape are signiﬁcant predictors of future RKOA
and that these shape descriptors are different in males compared to
females.
Methods: The Osteoarthritis Initiative (OAI) is a multi-center, longi-
tudinal, observational cohort study focused on identifying biomarkers
for the development or progression of knee OA. From an ongoing case-
control longitudinal OAI study, we identiﬁed a group of subjects within
the OAI Incidence subcohort that presented with no signs of knee OA
per the OAI deﬁnition (KL¼0 in both knees) at baseline and at the 36- or
48-month visit (control group; n¼32). We also identiﬁed age- and sex-
matched subjects from the OAI Incidence subcohort who presented
with no signs of knee OA at baseline (KL¼0 in both knees) who then
went on to develop knee OA (KL>¼2 in any knee) by the 36- or 48
month visit (case group; n¼32). Baseline axial MRI image data sets were
processed to extract the distal femur bone surface and a statistical
shape model (SSM)of the distal femur representing the entire cohort
(n¼64). We tested for differences in mean SSM shape mode weighting
factors (WFs) between the case and control groups, and between males
and females (JMP Pro, v.10, SAS Institute, Cary, NC). Using stepwise
logistic regression (JMP Pro, v.10, SAS Institute, Cary, NC) we tested the
ability of baseline SSM WFs to predict the future onset of RKOA at least
three years post baseline imaging for the whole cohort and for males
and females separately. Sensitivity and speciﬁcity of the resulting pre-
dictions of future RKOA were quantiﬁed using the area under the
receiver operating characteristic curve (ROC AUC).
Results: A total of six distal femur SSMWFs were signiﬁcantly different
between case and control knees for males. Three SSM WFs were sig-
niﬁcantly different between case and control knees for females. Using
stepwise logistic regression with case or control status as the outcome
variable, three SSM WFs were selected for males and six WFs were
selected for females. The resulting area under the ROC curve for the
logistic model using the three selected SSM WFs for males was 1.0 and
the AUC for the model constructed form the six SSM WFs for females
was 0.975.
Conclusions: Subchondral knee bone shape differs signiﬁcantly
between knees that later developed RKOA and those that did not. This
difference is detectable at least three years prior to the onset of RKOA.
Predictions of the future onset of RKOA can be made with high specif-
icity and sensitivity using independent, high ﬁdelity, shape descriptors
of the distal femur. In addition the high ﬁdelity SSM parameters
describing these differences are not the same for men compared to
women. Distal femur subchondral bone shape variability associated
with future onset of RKOA appears to be more complex in females
compared to males since the number of shape variables (6) used to
construct an accurate predictive model for females was larger than the
number of shape models required to construct an accurate predictive
model for males (3). While, on average, the incident knees generally had
higher condylar curvature and greater varus orientation, knee shape
differences between cases and controls are much more complex and
cannot be easily described using gross discrete measures (Fig. 1). These
results warrant further investigation to determine how the identiﬁed
subchondral bone shape variations affect knee mechanics, particularly
the stresses encountered within the knee cartilage and subchondral
bone.335
A MAGNETIC RESONANCE IMAGING BASED RAPID KNEE CARTILAGE
QUANTIFICATION METHOD FOR THE LATERAL TIBIOFEMORAL
COMPARTMENT: DATA FROM THE OSTEOARTHRITIS INITIATIVE
M. Zhang y, J.B. Driban y, L. Price y, G.H. Lo z, T.E. McAlindon y. y Tufts
Med. Ctr., Boston, MA, USA; zMichael E. DeBakey VA Med. Ctr./Baylor
Coll. of Med., Houston, TX, USA
Purpose: Cartilagemorphometry onmagnetic resonance images (MRIs)
is becoming an acceptable outcome measure for clinical trials among
individuals with knee osteoarthritis (OA). However, obtaining accurate
and reproducible cartilage data is burdensome. In previous work, we
designed and validated a rapid knee cartilage quantiﬁcation method_-
cartilage damage index (CDI) e for the medial tibiofemoral compart-
ment. The purpose of this study was to expand and validate the CDI to
detect cartilage damage in the lateral tibiofemoral compartment.
Methods: This was an iterative process where we developed the
measure, conducted preliminary tests of validity, and then tested its
construct validity. For this process, we created 3 datasets: development
(100 knees), testing (83 knees), and validation (100 knees). (1) Devel-
opment: For the development dataset, we chose 100 knees from the
Osteoarthritis Initiative (OAI) baseline that included knees with all
grades of lateral joint space narrowing (JSN, grades 0-3) with and
without medial JSN. The MRIs are 3-dimensional double-echo steady-
state sagittal images that were obtained on four 3-Tesla systems (0.37
mm x 0.37 mm, 0.7 mm slice thickness). To develop the lateral tibio-
femoral CDI we identiﬁed areas commonly affected by denudation by
having one reader manually mark the lateral cartilage denudation on
each knee. We then designed a pair of two dimensional, rectangular,
universal coordinate systems to represent the articular surface of the
distal lateral femur and proximal lateral tibia. Next, we projected the
denudation regions onto a coordinate system and selected 18 infor-
mative locations in and around the region that most frequently con-
tained denudation (Figure 1). The primary outcome is a CDI, which
summates the products of cartilage thickness, cartilage length and voxel
size from each informative location and are adjusted by height. (2)
Testing: On 83 knees with publicly available MRI-based cartilage seg-
mentation (Imorphics LTD) we did preliminary tests to explore face and
construct validity. One reader used customized software to measure the
CDI in the lateral femur and tibia cartilage in the testing and validation
datasets. (3) Validation: We selected 100 knees with baseline and 24-
month MRIs that was enriched to include all levels of lateral JSN and
individuals with and without lateral JSN progression. 20 knees were
selected from this ﬁnal validation dataset to assess intra-tester
Abstracts / Osteoarthritis and Cartilage 23 (2015) A82eA416A210reliability. We validated the lateral CDI by examining the association
between baseline (month 0) lateral CDI, lateral joint space narrowing
(OARSI score 0-1), lateral joint space width (JSW), and static alignment
(hip-knee-ankle [HKA] angle). We calculated standard response mean
(SRM) for lateral CDI change between baseline and 24-months. JSW
data and descriptions of the methods are publicly available on the OAI
website (kxr_qjsw_duryea_00 [version 0.5] and kxr_qjsw_duryea_03
[version 3.4]; http://oai.epi-ucsf.org/). HKA was measured on standing
full-limb radiographs (developed by Derek Cooke, ICC>0.99).
Results: The ﬁnal validation set included 100 knees with a mean age:
64.3 years, 59% females, and with a diverse range of lateral JSN grades (0
to 3, each grade contains 25 subjects) as our ﬁnal validation dataset. The
intra-tester reliability is good (intraclass correlation coefﬁcient ICC [3, 1
model] ¼ 0.86 to 0.98). At baseline, knees with greater medial JSN and
KL had lower mean CDI (i.e. greater cartilage damage, Table 1). Baseline
lateral CDI is associated with both lateral JSW and HKA (see table 2).The
SRM is good (SRM¼-0.76 for lateral femur; SRM¼-0.73 for lateral tibia;
SRM¼-0.87 for lateral tibiofemoral total).Table 1
Baseline lateral cartilage damage index stratiﬁed by baseline lateral JSN and KL grade.
Lateral JSN
Cartilage Measure JSN¼0 (n¼25) mean JSN¼1 (n¼25) mean JSN¼2 (n¼25) mean JSN¼2 (n¼25) mean p-value for trend
Lateral Femur CDI 2969.3 3003.2 2184.4 1542.0 <0.001
Lateral Tibia CDI 1154.9 889.9 663.8 392.7 <0.001
Lateral Tibiofemoral CDI 4124.3 3893.0 2848.2 1934.6 <0.001
KL
KL¼0 (n¼10) mean KL¼1 (n¼6) mean KL¼2 (n¼32) mean KL¼3 (n¼26) mean KL¼4 (n¼26) mean p-value for trend
Lateral Femur CDI 2718.7 2831.5 3061.0 2254.0 1605.3 <0.001
Lateral Tibia CDI 1229.3 994.1 946.3 690.4 424.7 <0.001
Lateral Tibiofemoral CDI 3948.0 3825.5 4007.3 2944.4 2030.0 <0.001
Table 2
Spearman correlation of baseline lateral CDI with baseline lateral JSW and HKA
angle.
Cartilage Measure Lateral JSW HKA
Lateral Femur CDI 0.81* -0.31*
Lateral Tibia CDI 0.81* -0.30*
Lateral Tibiofemoral CDI 0.85* -0.33*
Note: * ¼ p<0.05.Conclusions: Overall, the lateral tibiofemoral CDI quantiﬁcation is
reliable, responsive, and has good construct valid. The CDI has utility for
deployment in large studies.
336
CHANGE IN CARTILAGE T2 RELAXATION TIME IN OSTEOARTHRITIC
KNEES WITH AND WITHOUT STRUCTURAL PROGRESSION e PILOT
DATA FROM THE OSTEOARTHRITIS INITIATIVE
W.Wirth y,z, S. Maschek y,z, P. Beringer y, F. Eckstein y,z. y Paracelsus Med.
Univ. Salzburg & Nuremberg, Salzburg, Austria; zChondrometrics GmbH,
Ainring, GermanyBaseline T2 (ms) and change in T2 in the cartilages of progressors (P) and non-progre
Baseline Change
P NP P vs.NP P
Mean SD Mean SD P-Value Mean
MT Deep Layer 35.8 3.1 35.6 3.5 0.89 1.4
Superﬁcial Layer 44.8 3.0 43.6 2.9 0.12 -0.6
cMF Deep Layer 45.5 5.0 46.4 8.1 0.66 1.9
Superﬁcial Layer 54.0 4.3 51.6 4.7 0.09 0.4
LT Deep Layer 32.9 2.1 32.5 2.5 0.53 0.1
Superﬁcial Layer 43.0 2.9 43.3 3.1 0.74 -0.1
cLF Deep Layer 41.9 3.7 41.7 2.5 0.80 -0.3
Superﬁcial Layer 50.3 4.5 49.4 4.4 0.54 -1.1Purpose: MRI-based measurement of spin-spin (transverse) relaxation
time (T2) of articular cartilage is of interest because of its potential
sensitivity to changes in cartilage composition. However, it is unknown
whether cartilage T2 predicts structural progression (i.e. cartilage loss
in MRI and radiographic joint space width [JSW] loss) in knee osteo-
arthritis (OA), and to what extent T2 changes longitudinally in knees
that exhibit structural progression. The objective of the current study
was therefore to compare baseline cartilage T2 and longitudinal change
in T2 between knees with and without structural progression in the
medial femorotibial compartment.
Methods: OA knees with and without structural progression in the
medial femorotibial compartment (MFTC) were selected from a sub-
cohort of the OAI (n¼625), for which baseline and 1-year follow-up
measurements of MRI-based cartilage thickness and radiographic JSW
were available. 45 knees with Kellgren & Lawrence grade 2/3 showed
structural progression in the MFTC that exceeded the smallest detect-
able change (SDC) thresholds for both MRI-based cartilage thickness
(102mm) and radiographic JSW (328mm) over the same period. Of these,37 could be matched to one of the 202 knees from the same subcohort
without any progression in theMFTC or the lateral compartment (LFTC).
Knees were matched 1:1 by KLG, BMI, sex, and knee pain status.
Thus far, cartilage T2 analyses were completed in 22 of the 37 matched
case-control pairs (17 women/5 men; 13KLG 2/9 KLG3; cases: age:
63.8±9.0 y, BMI: 30.6±5.0 kg/m2; controls: 65.5±10.6 y, 30.8±4.4 kg/
m2). A multi-echo spin-echo MRI sequence was used (resolution:
0.31x0.31x3mm, repetition time: 2700ms, echo time: 10, 20, 30, 40, 50,
60, 70ms, 1st echo excluded from analysis) andmanual segmentation of
the medial and lateral tibial (MT/LT) and medial and lateral weight-
bearing femoral condyles (cMF/cLF) was performed with blinding to the
progressor/non-progressor status and the image acquisition order. T2
was computed in the deep and superﬁcial layer of each cartilage plate
(each 50% of the thickness) using a non-linear curve-ﬁtting. Paired t-
tests were used to compare baseline and follow-up measurements
within progressors and non-progressors, and to compare both groups
cross-sectionally (at baseline) and longitudinally.
Results: The baseline T2 did not differ signiﬁcantly between OA knees
with and without subsequent medial progression (p0.09, Table).
Despite the substantial cartilage thickness loss in the MFTC of the
progressors (Mean±SD: -280 ±160mm, p<0.001), no signiﬁcant change
in T2 was observed in MFTC (p0.10, Table). The T2 tended to increasessors (NP)
NP P vs. NP
SD P-Value (change) Mean SD P-Value (change) P-Value
3.9 0.10 -0.7 1.5 0.05 0.05
2.9 0.31 -0.1 2.1 0.83 0.42
5.4 0.11 -0.1 4.3 0.90 0.06
5.7 0.72 0.3 3.0 0.70 0.89
1.5 0.82 -0.1 1.3 0.60 0.61
1.6 0.86 -0.7 1.6 0.06 0.24
2.2 0.50 -0.5 1.7 0.20 0.74
2.1 0.03 -0.7 2.2 0.17 0.55


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A magnetic resonance imaging based rapid knee cartilage quantification method for the lateral tibiofemoral compartment: Data from the osteoarthritis initiative

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