Keywords: Cartilage, MSK
Motivation: Identifying patients with a backfill progression is crucial for predicting clinical prognosis and adjusting treatment approaches in the disease process.
Goal(s): This study aimed to extract radiomics features for the sacroiliac joint on MRI images in patients with axSpA to predict backfill progression within one year.
Approach: This retrospective study analyzed 257 patients diagnosed with axSpA. The radiomics and clinical models were combined to construct a nomogram model through multivariable logistic regression analysis.
Results: Seven radiomics features were extracted to generate a Rad-score. The AUCs of the radiomics, clinical, and nomogram models in the training cohort were 0.90, 0.78 and 0.93, respectively.
Impact: The built radiomics-based nomogram has good predictive value for structural progression in patients with axial spondyloarthritis.
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