Automated opportunistic osteoporotic fracture risk assessment using computed tomography scans to aid in FRAX underutilization

Methods for identifying patients at high risk for osteoporotic fractures, including dual-energy X-ray absorptiometry (DXA).sup.1,2 and risk predictors like the Fracture Risk Assessment Tool (FRAX).sup.3-6, are underutilized. We assessed the feasibility of automatic, opportunistic fracture risk evaluation based on routine abdomen or chest computed tomography (CT) scans. A CT-based predictor was created using three automatically generated bone imaging biomarkers (vertebral compression fractures (VCFs), simulated DXA T-scores and lumbar trabecular density) and CT metadata of age and sex. A cohort of 48,227 individuals (51.8% women) aged 50-90 with available CTs before 2012 (index date) were assessed for 5-year fracture risk using FRAX with no bone mineral density (BMD) input (FRAXnb) and the CT-based predictor. Predictions were compared to outcomes of major osteoporotic fractures and hip fractures during 2012-2017 (follow-up period). Compared with FRAXnb, the major osteoporotic fracture CT-based predictor presented better receiver operating characteristic area under curve (AUC), sensitivity and positive predictive value (PPV) (+1.9%, +2.4% and +0.7%, respectively). The AUC, sensitivity and PPV measures of the hip fracture CT-based predictor were noninferior to FRAXnb at a noninferiority margin of 1%. When FRAXnb inputs are not available, the initial evaluation of fracture risk can be done completely automatically based on a single abdomen or chest CT, which is often available for screening candidates.sup.7,8. A retrospective analysis of existing computed tomography scans shows the feasibility of an automated process for evaluating osteoporotic fracture risk that could be used as an initial screening tool when FRAX inputs are unavailable.
Author(s): Noa Dagan [sup.1] [sup.2] [sup.3] , Eldad Elnekave [sup.4] [sup.5] , Noam Barda [sup.1] [sup.2] [sup.3] , Orna Bregman-Amitai [sup.5] , Amir Bar [sup.5] , Mila Orlovsky [sup.5] , [...]