Analysis of multiple MRI-based quantitative structural measurements of knee osteoarthritis in a case control study - association with pain and structural progression and comparison to semi-quantitative scoring

Stacy E Smith; Lawrence Lo; Meera Sury; Sara M Bahouth; Ming Yin; Lena F Schaefer; Jamie E Collins; Jeffrey Duryea

doi:10.1016/j.ocarto.2025.100638

Analysis of multiple MRI-based quantitative structural measurements of knee osteoarthritis in a case control study - association with pain and structural progression and comparison to semi-quantitative scoring

Osteoarthr Cartil Open. 2025 Jun 5;7(3):100638. doi: 10.1016/j.ocarto.2025.100638. eCollection 2025 Sep.

Authors

Stacy E Smith^{1

2}, Lawrence Lo^{1

3}, Meera Sury¹, Sara M Bahouth¹, Ming Yin¹, Lena F Schaefer¹, Jamie E Collins⁴, Jeffrey Duryea¹

Affiliations

¹ Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital. Harvard Medical School, Boston, MA, USA.
² Neil and Elise STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
³ Department of Radiology, University of Chicago, Chicago, IL, USA.
⁴ Department of Orthopaedic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Abstract

Objective: To use software-based magnetic resonance imaging (MRI) measures of multiple features of knee osteoarthritis (KOA) to predict radiographic and pain progression in persons with KOA, and compare to a study that used primarily semi-quantitative (SQ) scoring.

Design: Data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium (FNIH) nested case-control study (600 subjects divided into case and control groups based on knee pain and/or radiographic progression) were used. The MRI Osteoarthritis Software Scoring (MOSS) was used to quantitatively assess medial femoral cartilage, bone marrow lesions, osteophyte volume, effusion-synovitis volume, and a measure of Hoffa's synovitis at baseline and 24-months using readers with diverse levels of expertise. Association between baseline and baseline to 24-month change with progressor status was examined and discriminative ability assessed using the c-statistic (AUC) computed under 10-fold cross validation.

Results: AUC values ranged from 0.690 to 0.726 to predict combined pain/radiographic progression and from 0.709 to 0.804 to predict radiographic progression alone. Bone marrow lesions and osteophyte volume played a role in all analyses. Medial femoral cartilage was significant for all but the cross-sectional analysis involving pain progression. Comparison to results from a separate publication showed that MOSS offered similar discrimination to a published model that primarily used SQ scoring.

Conclusions: We found a high level of discrimination particularly for radiographic progression analysis. Use of fast automated software and readers with varied prior experience make MOSS a useful tool for enriching future clinical trials and for other large studies of KOA.

Keywords: Knee; Magnetic resonance imaging; Osteoarthritis; Quantitative imaging; Software; Synovitis.