Prediction of vertebral fracture risk in patients with osteopenia based on MRI texture analysis

Motivation: Fractures can be highly detrimental for the elderly population. Assessing bone density alone is insufficient in accurately predicting fracture risk in osteopenia patients with and without fragility fracture. MRI can provide additional information on vertebral strength. Goal(s): To develop and validate a three-dimensional texture analysis method based on MRI for quantifying grayscale and distribution information of vertebrae. Approach: We extracted MR texture features of the L4 vertebra and selected the most relevant features. A logistic regression model was established for fracture risk prediction. Results: In a comprehensive model, the training and testing set achieved an AUC of 0.84 and 0.80 respectively. Impact: Detecting subtle texture information that is imperceptible to the naked eye during the osteopenia stage. Analyzing these texture features specifically can help slow down the process of bone loss.