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

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.