Bay-Jensen, A-C.

Chen, P.

Karsdal, M.A.

Li, B.

Qvist, P.

Thomsen, G.

Wang, B.

Zheng, Q.

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Poster Presentations – Biomarkers S57
inﬂammation. The following biomarkers were measured for all 5 visits:
Serum: sCOMP, sCTXI, sIntactPINP, sPIIANP, sCPII, sPIIINP.
Plasma: p15HETE, pNPII, pPGE2, pYNO2.
Urine: uAgg, uCTXII, uTINE, uTIINE, uTIIINE, uOsteop.
A simple linear regression model was produced for each biomarker
against JSN after 24 months. Multiple test comparisons were adjusted for
through use of false discovery rate methods, a=0.1. Multivariate linear
regression models examining all biomarkers against change in JSW were
generated using forward and backward stepwise regression algorithms.
These algorithms were used to reduce the number of biomarkers included
in the ﬁnal model by including signiﬁcant or removing non-signiﬁcant
variables from the model. All of the individual biomarkers data showed
skewed distributions; thus a log-transformation of the data was used.
Results: Quality data was generated for 16 individual biomarkers for
160 subjects at 5 time points during 2-year longitudinal OA method
study. Several approaches to analyze these data for the identiﬁcation
of biochemical markers that predict JSN at 24 month were undertaken.
The most straightforward approach was to use the baseline (BL) levels
of each individual biomarker. Another approach was to evaluate changes
in biochemical markers over a short period of time (3−6 months). Finally,
multivariate analysis of all 16 biomarkers at baseline was investigated
since a combination of multiple biomarkers may help explain disease
behaviour better than an individual biomarker. Preliminary data using
all subjects indicated that levels of the urinary biomarker, uTIINE, at
baseline correlate to JSN at 24 month with a p value of 0.0071. A subset
of subjects (KLG3 and KLG2) showing the most signiﬁcant changes
in JSN was evaluated separately. For this rapidly progressing subset,
among all 16 biomarkers, baseline data of uTINE, uTIIINE, and uOsteop
correlated to JSN at 24 month with p values of 0.0340, 0.0297, and
0.0120, respectively.
Conclusions: Based on this longitudinal OA clinical methods study,
biochemical biomarkers show signiﬁcant promise with regard to their
prediction in radiographic JSN at 24 months.
101 EFFICIENCY AND REPRODUCIBILITY OF SEGMENTATION
OF KNEE CARTILAGES ON MR IMAGES FROM
OSTEOARTHRITIS INITIATIVE (OAI) – COMPARISON
OF SEMI-AUTOMATED GRAPH-CUTS AND MANUAL
DELINEATION METHODS
H. Shim, S. Chang, C. Tao, K. Kwoh, R. Boudreau, K.T. Bae. University
of Pittsburgh, Pittsburgh, PA, USA
Purpose: Efﬁcient and reproducible segmentation of knee cartilage is
necessary for quantiﬁcation and analysis of cartilages from large co-
horts of osteoarthritis subjects such as in the OAI database. We have
developed and implemented a semi-automated cartilage segmentation
method using a graph-cuts algorithm. The purpose of this study was
to evaluate and compare, between the semi-automated and manual
delineation methods, the efﬁciency and reproducibility for segmenting
knee cartilages.
Methods: Nine right knee MR image sets of varying severities of OA
[Kellgren-Lawrence (KL) grade] were selected from the sagittal double-
echo steady-state (DESS) MR images in the OAI-0.B.1 Imaging Data
Set (Siemens 3.0T Trio, 160 slices with 0.7mm thickness): one set with
KL 0; 3 with KL 1; 3 with KL 2; and 2 with KL 3. Two radiologist
readers (1 and 2) segmented the knee cartilage on ‘every third’ slice
by manual boundary delineation (M method: M1 and M2). Segmentation
was repeated by both readers using the semi-automated method, which
was based on a graph-cuts algorithm (SA method: SA1 and SA2). The
SA method incorporates the seeds speciﬁed by a reader and intensity
values to compute the optimal segmentation. Seed speciﬁcation and
computation were iterated allowing the reader to edit and improve the
segmentation results. The efﬁciency in segmentation was measured in
terms of segmentation processing time used by readers. The inter-reader
reproducibility in segmentation was determined by superimposing the
segmented cartilages (M1 onto M2 or SA1 onto SA2) and computing
the Dice Similarity Coefﬁcient (DSC: ratio of overlapped volume/mean
volume) as an index of matching between the segmented cartilages.
Perfect match corresponds to 100% DSC. In addition, the inter-method
reproducibility of a reader was measured by computing DSC’s of (SA1
onto M1) and (SA2 onto M2).
Results: The manual segmentation processing time (mean±SD, min)
was (160±45) for M1 and (121±27) for M2. On the other hand, the
SA processing time, which was based on ‘every’ slice, was (54±14)
for SA1 and (33±6) for SA2, indicating that the SA method was sig-
niﬁcantly more efﬁcient than the manual method (p< 0.001). The inter-
reader reproducibility of each method measured by DSC (mean±SD)
was 94.2±1.5% (SA1 onto SA2) and 87.7±1.3% (M1 onto M2), indicating
that the semi-automated method was signiﬁcantly higher in inter-reader
reproducibility than the manual method (p< 0.001). Finally, the inter-
method reproducibility of a reader also measured by DSC was 87.4±1.6%
(SA1 onto M1) for reader 1 and 87.7±1.2% (SA2 onto M2) for reader 2,
which supports the feasibility of the SA method as an alternative to a
manual delineation method.
Conclusions: We have developed and implemented a semi-automated
cartilage segmentation method based on a graph-cuts algorithm which
permitted us to segment the knee cartilages from high-resolution MR
images with signiﬁcantly higher (approximately 10 times) efﬁciency and
reproducibility than a manual boundary delineation segmentation method.
102 SOME AGGRECAN FRAGMENTS CARRYING
AGGRECANASE-MEDIATED NEO-EPITOPES AREONLY
RELEASED INTO THE SUPERNATANT OF BOVINE
CARTILAGE EXPLANTS AFTER PROLONGED EXPOSURE
TO CATABOLIC CYTOKINES
B. Wang1, A-C. Bay-Jensen2, P. Chen1, M.A. Karsdal2, B. Li2,
G. Thomsen2, Q. Zheng1, P. Qvist2. 1Nordic Bioscience, Beijing,
CHINA, 2Nordic Bioscience, Herlev, DENMARK
Purpose: Degradation of the core aggrecan protein is a complicated
process of aggrecanase and MMP activity, resulting in a long range of
identiﬁed degradation products, albeit with less understanding of their
individual biological role and release from the matrix. The aggrecan
molecule is linked via the G1 domain and the LINK protein to hyaluronic
acid. As a consequence of this molecular interaction with the ECM,
some proteolytic fragments of aggrecan may be released from the matrix
whereas others are primarily retained.
The aim of this study was to proﬁle two fragments of aggrecanase medi-
ated aggrecan degradation, i.e. the 374’ARGSV-containing fragments and
the NITEGE’373-containing fragments that are generated in equimolar
amount through the action of aggrecanase, although as a consequence
to different binding motifs to the matrix potentially are released by differ-
ent patterns and amounts. This was compared to the release of other
fragments of aggrecan.
Methods: Aggrecan fragments were measured in the supernatants of
bovine articular cartilage explants stimulated with TNFa/OSM for up to
21 days using a range of immunoassays; (1) 374’ARGSV-containing
fragments (374-G2) were detected using BC3 (ABCAM) and F78 in a
sandwich construction; (2) NITEGE’373-containing fragments were mea-
sured using monoclonal antibody 1H11 recognising the . . .NITEGE′373
neo-epitope in a competition ELISA; (3) 342FFGVG-containing fragments
were measured using AF28 and F78 in a sandwich construction; (4) and
total aggrecan was measured using F78 as both capture and detector
antibody.
Results: As previously reported, aggrecan fragments cleaved by aggre-
canase (374-G2) were released in the early phase of explants culturing,
i.e. peaking at day 7 reaching background levels at day 9, whereas MMP-
related fragments (342-G2) were detected in the late stage, i.e. after
day 15.
Interestingly, aggrecan fragments containing the NITEGE′373 neo-
epitope were released through a different pattern compared to the
other aggrecanase-mediated aggrecan fragments, as a major part of the
NITEGE carrying fragments were detected in the intermediate phase, i.e.
around day 11 after prolonged catabolic stimulation of the explants.
Conclusions: We found that some aggrecan fragments carrying
aggrecanase-mediated neo-epitopes are only released into the super-
natant after prolonged exposure to catabolic cytokines, while others are
released rapidly. Such prolonged exposure will activate MMP-mediated
aggrecan (and type II collagen) degradation, and therefore the data
suggest that these fragments are only released through the action of
both families of proteases. This would be consistent with the G1 domain
participating in the linking to hyaluronic acid in the ECM. This, however,
remains to be investigated further.


102 SOME AGGRECAN FRAGMENTS CARRYING AGGRECANASE-MEDIATED NEO-EPITOPES AREONLY RELEASED INTO THE SUPERNATANT OF BOVINE CARTILAGE EXPLANTS AFTER PROLONGED EXPOSURE TO CATABOLIC CYTOKINES 

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102 SOME AGGRECAN FRAGMENTS CARRYING AGGRECANASE-MEDIATED NEO-EPITOPES AREONLY RELEASED INTO THE SUPERNATANT OF BOVINE CARTILAGE EXPLANTS AFTER PROLONGED EXPOSURE TO CATABOLIC CYTOKINES

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