ArticleSkeletal radiology2026
Combination of artificial intelligence and chest computed tomography to assess bone mineral density.
Article in Skeletal radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence for opportunistic screening of osteoporosis across multiple imaging modalities: a systematic review.Frontiers in medicine · 2026Pooled it
- Artificial intelligence and chest CT: a new frontier for opportunistic bone mineral density assessment.Skeletal radiology · 2026Article
- Artificial Intelligence for Osteoporosis Diagnosis, Risk Prediction and Therapy: Current Advances, Clinical Challenges, and Future Perspectives.Clinical interventions in aging · 2026Review
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
Abstract
objectivesTo evaluate the diagnostic accuracy of artificial intelligence-assisted opportunistic chest CT for osteoporosis/osteopenia screening in a Chinese population.
methodsThis retrospective study included 1306 adults (≥ 55 years) undergoing concurrent chest CT and DXA during physical examinations (Apr 2015 to May 2024). Exclusion criteria comprised vertebral fractures, spinal surgery, or contrast-enhanced CT. DXA T-scores (lumbar spine) defined osteoporosis, osteopenia, and normal BMD. The AI system automatically quantified volumetric BMD (AI-BMD) at vertebrae T10-L1. Diagnostic performance was assessed using ROC curves.
resultsMean age was 63.96 years (36.98% male). Osteoporosis prevalence was 36.45% (n = 476/1306), significantly higher in women (P < 0.01). AI-BMD values decreased significantly from T10 to L1 (P < 0.05). For osteoporosis detection, AI-BMD demonstrated excellent diagnostic accuracy: AUC was 0.84 (95% CI: 0.81-0.87) at T10, 0.83 (95% CI: 0.80-0.86) at T11, 0.81 (95% CI: 0.79-0.84) at T12, and 0.83 (95% CI: 0.80-0.87) at L1. Performance for osteopenia diagnosis was moderate, with AUCs ranging from 0.72 to 0.75.
conclusionThe combination of opportunistic chest CT and AI shows promise for accurate osteoporosis screening (AUCs 0.81-0.84), albeit with moderate performance in detecting osteopenia (AUCs 0.72-0.75). The retrospective, single-center design of this study suggests that future multi-center validation is warranted to confirm the generalizability of these findings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.