Nomogram prediction of short-term collapse progression in osteonecrosis of the femoral head: A combination of clinical data and radiomics features from hip magnetic resonance imaging.

Abstract

This study investigates the development of a nomogram for predicting the short-term collapse progression of osteonecrosis of the femoral head by integrating clinical data with radiomics features obtained from hip joint MRI. The study involved 364 patients with osteonecrosis of the femoral head who had not yet severe collapsed(Collapse < 2 mm or no collapse) from two medical centers, selected from a major medical center. MRI images of their hip joints were analyzed to extract radiomics features. A clinical model was developed using criteria such as ARCO classification, CJFH classification, JIC classification, and the modified Kerboul angle. The outcome variable was the occurrence of collapse progression within one year post-examination. Features most significantly associated with collapse progression were identified from both radiomics and clinical data, which were then integrated into separate models. A combined Nomogram model was constructed by merging the clinical and radiomics models. The performance of these models was compared to assess their effectiveness in predicting collapse progression. The Nomogram model demonstrated superior predictive performance compared to both the clinical and radiomics models across all cohorts. In the external validation set, the Nomogram achieved an AUC of 0.919 and an accuracy of 0.879, outperforming the clinical (AUC = 0.809) and radiomics (AUC = 0.875) models. Statistical significance was confirmed between the Nomogram and clinical model in all cohorts. In summary, our study demonstrates that a nomogram combining hip MRI-based radiomics with clinical data shows superior predictive performance compared to clinical-only models for assessing short-term collapse risk in osteonecrosis of the femoral head.