ArticleOsteoporosis and sarcopenia2026
Artificial intelligence-assisted screening reveals high prevalence of osteoporosis in Vietnamese adults using pelvic and hip radiographs.
Article in Osteoporosis and sarcopenia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: Osteoporosis is a silent disease with low screening rates in many developing countries. This study aimed to evaluate the feasibility of using an artificial intelligence (AI)-based system to screen osteoporosis from pelvic and hip radiographs in Vietnam. Methods: We conducted a cross-sectional study at a tertiary medical center in Central Vietnam in 2023. A total of 2000 consecutive pelvic and hip radiographs from patients aged ≥ 40 years were collected. After excluding poor-quality images, 1987 radiographs were analyzed using an AI-based software designed to estimate bone mineral density (BMD) from plain radiographs and derive T-scores. Osteoporosis was defined as a T-score ≤ -2.5. Patient characteristics, radiographic findings, and risk factors for osteoporosis were analyzed. Results: Among 1987 patients (mean age 66.4 ± 15.1 years; 41.3% men), osteoporosis was identified in 872 patients (43.9%). The prevalence increased with age and was higher in women than in men (58.7% vs 22.8%, P < 0.001). Osteoporosis was associated with femoral neck (OR = 3.8, 95% CI: 2.7-5.2) and intertrochanteric fractures (OR = 7.0, 95% CI: 4.5-11.0). Patients with lower T-scores had a higher risk of hip fractures, especially those with T-scores ≤ -3.0 (OR = 11.5, 95% CI: 5.5-24.5). Conclusions: AI-based analysis of pelvic and hip radiographs is a feasible and effective tool for osteoporosis screening in Vietnam. The prevalence of osteoporosis in this hospital-based setting was high, particularly among elderly women. AI-assisted screening may offer an accessible strategy for early detection of osteoporosis in resource-limited settings.
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