Chest Radiograph-based Artificial Intelligence for Osteoporosis: Accuracy and Associations With Fracture and Mortality.
Authors
Affiliations (1)
Affiliations (1)
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine (J.Y.L., E.J.H.); Division of Clinical Epidemiology, Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea (M-.S.K., J.K.).
Abstract
To evaluate an AI tool for opportunistic osteoporosis screening using chest radiographs (CXRs), focusing on its diagnostic accuracy against dual-energy x-ray absorptiometry (DXA) and associations with long-term risks of fracture and mortality. This retrospective, external validation study included a health checkup cohort with same-day CXR-DXA pairs and a chronic obstructive pulmonary disease (COPD) cohort with available CXRs. We evaluated a commercialized AI tool (InceptionV3 backbone, trained with 55,600 CXR-DXA pairs) designed to identify osteoporosis from a single frontal CXR. Diagnostic performance was assessed against DXA using the area under the receiver operating characteristic curve (AUC). Associations between AI results and subsequent fractures or all-cause mortality were investigated using multivariable Cox proportional-hazard regression, adjusted for sex, age, low body mass index, and COPD stage. Mediation analyses were conducted to examine whether these associations were mediated by a diagnosis of osteoporosis. In total, 8618 (male-to-female ratio, 2882:5736; mean age, 58 y; median follow-up, 2868 d) and 4941 (male-to-female ratio, 4110:831; mean age, 69 y; median follow-up, 2656 d) patients were included in the health checkup and COPD cohorts, respectively. The AI achieved AUCs of 0.94 (95% CI: 0.93-0.95) and 0.81 (95% CI: 0.76-0.87) for osteoporosis identification in the health checkup and COPD cohorts, respectively. Higher AI-predicted osteoporosis probability was associated with subsequent fracture and mortality in both cohorts ( Ps <0.05). Mediation analyses showed that indirect effects of AI scores on fracture or mortality mediated through DXA-defined or clinically diagnosed osteoporosis were not significant ( P s>0.05), suggesting that AI may identify fracture risk in individuals not yet clinically diagnosed with osteoporosis. AI could identify osteoporosis from chest radiographs, and AI results were associated with subsequent fracture and mortality.