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An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...
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Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
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Chest Radiograph-based Artificial Intelligence for Osteoporosis: Accuracy and Associations With Fracture and

Ji Young Lee1, Mi-Sook Kim, Jinhee Kim

  • 1Department 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.).

Investigative Radiology
|July 15, 2026
PubMed
Summary

An artificial intelligence tool can detect osteoporosis from chest X-rays, showing high accuracy. This AI shows potential for identifying fracture and mortality risks, even in patients not yet diagnosed with osteoporosis.

Keywords:
artificial intelligencechest radiographydeep learningfracturemortalityopportunistic screeningosteoporosis

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Area of Science:

  • Artificial Intelligence in Medical Imaging
  • Osteoporosis Screening
  • Radiology

Background:

  • Osteoporosis poses significant fracture and mortality risks.
  • Current screening methods like DXA are not universally accessible.
  • Chest radiographs (CXRs) are widely available and offer an opportunity for opportunistic screening.

Purpose of the Study:

  • To evaluate an AI tool for opportunistic osteoporosis screening using CXRs.
  • To assess the AI's diagnostic accuracy against DXA.
  • To investigate the association between AI-identified osteoporosis and long-term fracture and mortality risks.

Main Methods:

  • Retrospective external validation study using health checkup and COPD cohorts.
  • Evaluation of a commercialized AI tool (InceptionV3 backbone) trained on 55,600 CXR-DXA pairs.
  • Diagnostic performance assessed via AUC against DXA; long-term risks analyzed using Cox regression.

Main Results:

  • AI achieved high AUCs for osteoporosis identification (0.94 in health checkup cohort, 0.81 in COPD cohort).
  • Higher AI-predicted osteoporosis probability correlated with increased subsequent fracture and mortality risk in both cohorts.
  • Mediation analyses indicated AI identifies fracture risk independently of existing osteoporosis diagnoses.

Conclusions:

  • AI can effectively identify osteoporosis from chest radiographs.
  • AI-driven osteoporosis detection from CXRs is associated with future fracture and mortality risks.
  • The AI tool shows promise for early risk identification in individuals not yet diagnosed with osteoporosis.