Jun Zhang, Liang Xia, Jiayi Liu, Xiaoying Niu, Jun Tang, Jianguo Xia, Yongkang Liu, Weixiao Zhang, Zhipeng Liang, Xueli Zhang, Guangyu Tang, Lin Zhang
PURPOSE: To develop and validate a deep learning radiomics (DLR) model that uses X-ray images to predict the classification of osteoporotic vertebral fractures (OVFs). MATERIAL AND METHODS: The study encompassed a cohort of 942 patients, involving examinations of 1076 vertebrae through X-ray, CT, and MRI across three distinct hospitals. The OVFs were categorized as class 0, 1, or 2 based on the Assessment System of Thoracolumbar Osteoporotic Fracture. The dataset was divided randomly into four distinct subsets: a training set comprising 712 samples, an internal validation set with 178 samples, an external validation set containing 111 samples, and a prospective validation set consisting of 75 samples...
2024: Frontiers in Endocrinology