Prediction of Backfill Progression at the Sacroiliac Joint in Patients with Axial Spondyloarthritis using a radiomics method

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.