Motivation: Patients with low-energy vertebral fractures are typically at high risk for future fracture. Lumbar MRI-based deep learning (DL) can help improve prediction of fracture risk. Goal(s): To develop and validate a DL model for fracture prediction based on vertebral and paraspinal muscular MR images. Approach: Establish a DL model to predict fracture risk in low bone mass patients, including subgroup analyses for osteopenia and osteoporosis. Data was collected from three hospitals with an external validation set. Results: In osteopenia, the combined vertebral-muscle model achieved an AUC of 0.648, outperforming the vertebral-only model's 0.582 on the external validation set. Impact: The paraspinal muscles, as one of the key structures in maintaining spinal stability, work synergistically with the vertebrae in predicting vertebral fracture risk, especially in osteopenia patients.
Yang et al. (Tue,) studied this question.