Spatial Gradients of Quantitative MRI as Biomarkers for Early Detection of Osteoarthritis: Data From Human Explants and the Osteoarthritis Initiative

Abstract

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).

Purpose: To quantify spatial gradients and patterns in MRI data, and to probe new candidate biomarkers for early severity of OA.

Study type: Retrospective study.

Subjects: 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).

Field strength/sequence: 3.0-T and 14.1-T, biomechanics-based displacement-encoded imaging, fast spin echo, multi-slice multi-echo T2 mapping.

Assessment: 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.

Statistical tests: Multiparametric linear regression for evaluation of the relationship between residuals of the mixed effects models and histologically determined OA severity scoring, with a significance threshold at α = 0.05.

Results: 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 (R² = 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.

Evidence level: 1 TECHNICAL EFFICACY: Stage 1.

Keywords: T1rho; T2; biomechanics; degeneration; multiparametric; pathogenesis.