A deep-radiomics approach can be used to diagnose osteoporosis from hip radiographs, according to a study published in Radiology: Artificial Intelligence. Sangwook Kim, MD, and colleagues developed and validated deep radiomics models for diagnosis of osteoporosis using 4,924 hip radiographs from 4,308 patients. The model was trained using 10 deep features, 16 texture features, and three clinical features. Seven deep-radiomics models were developed by combining different feature types: clinical (Model-C), texture (Model-T), deep (Model-D), texture and clinical (Model-TC), deep and clinical (Model-DC), deep and texture (Model-DT), and deep, texture, and clinical features (Model-DTC). A total of 444 hip radiographs from a different institution were used as an external test set. An observer performance test was conducted by six radiologists. Model-D demonstrated higher diagnostic performance than Model-T for the external test set. Compared with Model-D, Model-DC and Model-DTC showed improved diagnostic performance.
