- Award ID(s):
- Publication Date:
- NSF-PAR ID:
- Journal Name:
- Osteoarthritis and Cartilage
- Page Range or eLocation-ID:
- S331 to S332
- Sponsoring Org:
- National Science Foundation
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Composite quantitative knee structure metrics predict the development of accelerated knee osteoarthritis: data from the osteoarthritis initiativeAbstract Background We aimed to determine if composite structural measures of knee osteoarthritis (KOA) progression on magnetic resonance (MR) imaging can predict the radiographic onset of accelerated knee osteoarthritis. Methods We used data from a nested case-control study among participants from the Osteoarthritis Initiative without radiographic KOA at baseline. Participants were separated into three groups based on radiographic disease progression over 4 years: 1) accelerated (Kellgren-Lawrence grades [KL] 0/1 to 3/4), 2) typical (increase in KL, excluding accelerated osteoarthritis), or 3) no KOA (no change in KL). We assessed tibiofemoral cartilage damage (four regions: medial/lateral tibia/femur), bone marrow lesion (BML) volume (four regions: medial/lateral tibia/femur), and whole knee effusion-synovitis volume on 3 T MR images with semi-automated programs. We calculated two MR-based composite scores. Cumulative damage was the sum of standardized cartilage damage. Disease activity was the sum of standardized volumes of effusion-synovitis and BMLs. We focused on annual images from 2 years before to 2 years after radiographic onset (or a matched time for those without knee osteoarthritis). To determine between group differences in the composite metrics at all time points, we used generalized linear mixed models with group (3 levels) and time (up to 5 levels). For our prognostic analysis,more »
Spatial Gradients of Quantitative
MRIas Biomarkers for Early Detection of Osteoarthritis: Data From Human Explants and the Osteoarthritis Initiative Background
Healthy articular cartilage presents structural gradients defined by distinct zonal patterns through the thickness, which may be disrupted in the pathogenesis of several disorders. Analysis of textural patterns using quantitative MRI data may identify structural gradients of healthy or degenerating tissue that correlate with early osteoarthritis (OA).
To quantify spatial gradients and patterns in MRI data, and to probe new candidate biomarkers for early severity of OA.
Fourteen volunteers receiving total knee replacement surgery (eight males/two females/four unknown, average age ± standard deviation: 68.1 ± 9.6 years) and 10 patients from the OA Initiative (OAI) with radiographic OA onset (two males/eight females, average age ± standard deviation: 57.7 ± 9.4 years; initial Kellgren‐Lawrence [KL] grade: 0; final KL grade: 3 over the 10‐year study).
3.0‐T and 14.1‐T, biomechanics‐based displacement‐encoded imaging, fast spin echo, multi‐slice multi‐echo
We studied structure and strain in cartilage explants from volunteers receiving total knee replacement, or structure in cartilage of OAI patients with progressive OA. We calculated spatial gradients of quantitative MRI measures (eg, T2) normal to the cartilage surface to enhance zonal variations. We compared gradient values against histologically OA severity, conventional relaxometry, and/or KL grades.
Multiparametric linear regression for evaluation of the relationship between residuals of the mixedmore »
Gradients of individual relaxometry and biomechanics measures significantly correlated with OA severity, outperforming conventional relaxometry and strain metrics. In human explants, analysis of spatial gradients provided the strongest relationship to OA severity (
R 2= 0.627). Spatial gradients of T2 from OAI data identified variations in radiographic (KL Grade 2) OA severity in single subjects, while conventional T2 alone did not. Data Conclusion
Spatial gradients of quantitative MRI data may improve the predictive power of noninvasive imaging for early‐stage degeneration.