Model using longitudinal MRI radiomics, biochemical biomarkers, clinical factors improves prediction of progression<\/p>\n<\/h3>\n
By Elana Gotkine HealthDay Reporter<\/b>
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WEDNESDAY, Aug. 27, 2025 (HealthDay News) — Longitudinal magnetic resonance imaging (MRI) radiomics features of load-bearing knee joint tissues can help predict progression of knee osteoarthritis (KOA), according to a study published online Aug. 21 in PLOS Medicine<\/em>.<\/p>\n Ting Wang, from The Third People’s Hospital of Chengdu in China, and colleagues developed and tested the longitudinal Load-Bearing Tissue Radiomic plus Biochemical biomarker and Clinical variable Model (LBTRBC-M) to predict KOA progression. A total of 594 participants with Kellgren-Lawrence grades 1 to 3 and complete biomarker data were selected (mean age, 61.6 \u00b1 8.9 years; 58.8 percent female; 79.3 percent White). A total of 1,753 knee MRIs were included: 594 at baseline, 575 at one-year follow-up, and 584 at two-year follow-up. The model was developed in the total development cohort (877 participants) and tested among 876 participants in the total test cohort.<\/p>\n The researchers found that the area under the receiver operating characteristic curves of LBTRBC-M for predicting joint space narrowing (JSN) and pain progression, JSN progression, pain progression, and nonprogression were 0.880, 0.913, 0.886, and 0.909, respectively. LBTRBC-M had overall accuracy of 70.1 percent. The prognostic accuracy of resident physicians improved from 44.7 to 49.0 percent to 64.4 to 66.5 percent with LBTRBC-M assistance.<\/p>\n “The integrated model using longitudinal MRI radiomics, biochemical biomarkers, and clinical KOA high-risk factors, improved the prediction performance of KOA progression. LBTRBC-M enhances the accuracy of resident physicians to predict KOA progression,” the authors write.<\/p>\n One author disclosed ties to the biopharmaceutical and medical technology industries.<\/p>\n