Diagnostic Accuracy of Dual-Energy CT-Derived Metrics for the Prediction of Osteoporosis-Associated Fractures

Abstract

ObjectivesThis study aimed to compare the diagnostic value of dual-energy CT (DECT)-based volumetric material decomposition with that of Hounsfield units (HU)-based values and cortical thickness ratio for predicting the 2-year risk of osteoporosis-associated fractures. MethodsThe L1 vertebrae of 111 patients (55 men, 56 women; median age, 62 years) who underwent DECT between 01/2016 and 12/2018 were retrospectively analyzed. For phantomless bone mineral density (BMD) assessment, a specialized DECT postprocessing software employing material decomposition was utilized. The digital records of all patients were monitored for two years after the DECT scans to track the incidence of osteoporotic fractures. Diagnostic accuracy parameters were calculated for all metrics using receiver-operating characteristic (ROC) and precision-recall (PR) curves. Logistic regression models were used to determine associations of various predictive metrics with the occurrence of osteoporotic fractures. ResultsPatients who sustained one or more osteoporosis-associated fractures were significantly older (median age 74.5 years [IQR 57-83 years]) compared to patients without fractures (median age 50.5 years [IQR 38.5–69.5 years]). According to logistic regression models, DECT-derived BMD was the sole predictive parameter significantly associated with osteoporotic fracture occurrence across all age groups. ROC and PR curve analyses confirmed the highest diagnostic accuracy for DECT-based BMD, with an area under the curve (AUC) of 0.95 [95% CI: 89.3 - 98.3] for the ROC curve and an AUC of 0.96 [95% CI: 85.4 - 98.7] for the PR curve. ConclusionsThe diagnostic performance of DECT-based BMD in predicting the 2-year risk of osteoporotic fractures is greater than that of HU-based metrics and the cortical thickness ratio. DECT-based BMD values are highly valuable in identifying patients at risk for osteoporotic fractures.