In the current issue of JBMR, Kolanu and colleagues evaluate a computer-aided diagnostic (CAD) system designed to identify osteoporotic vertebral fractures (VFs) visualized opportunistically from computed tomography (CT) images.(1) The system, developed by Zebra Medical Vision (Shefayim, Israel; www.zebramed. com), extracts a virtual sagittal section visualizing the spinal midplane and identifies VFs using machine-learning algorithms. It outputs the probability that the volume contains a VF and a heat map indicating the probable locations of VFs in the sagittal image. In a single-site study involving thoracic CT scans from 1696 patients with a VF prevalence of 24%, the system achieved a sensitivity, specificity, and accuracy of 54%, 92%, and 83%, respectively.