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Explainable Biological Age from Automated Chest Radiography-based Organ Quantifications: qCXR-bioage.

Yoosoo Chang1,2,3, Suntae Park1, Hyungjin Kim4

  • 1Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.

Radiology. Cardiothoracic Imaging
|April 9, 2026
PubMed
Summary
This summary is machine-generated.

This study developed qCXR-bioage, a novel biologic age model using chest X-rays, which accurately predicts chronological age and surpasses it in forecasting mortality risk.

Keywords:
Conventional RadiographyLungThorax

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Area of Science:

  • Radiology
  • Artificial Intelligence
  • Biomarkers

Background:

  • Assessing biologic age is crucial for predicting health outcomes.
  • Quantitative organ metrics from chest radiographs offer potential biomarkers.
  • Existing methods for biologic age estimation have limitations.

Purpose of the Study:

  • To develop an explainable biologic age model (qCXR-bioage) using quantitative chest radiograph metrics.
  • To evaluate the prognostic value of qCXR-bioage for all-cause and cause-specific mortality.
  • To validate the model's performance in a large, independent cohort.

Main Methods:

  • Developed qCXR-bioage using deep learning to extract biomarkers (lung area, emphysema, aortic diameter, heart area, bone density) from chest radiographs.
  • Integrated automated measurements with clinical variables using the Klemera-Doubal method and multivariable ridge regression.
  • Validated the model in 257,004 individuals and assessed mortality prediction using Cox and Fine-Gray models.

Main Results:

  • qCXR-bioage strongly correlated with chronological age (R² > 0.98).
  • The model outperformed chronological age in predicting all-cause mortality (C-index > 0.76).
  • Accelerated aging (qCXR-bioage > chronological age) was significantly associated with increased all-cause and cardiovascular mortality.

Conclusions:

  • Chest radiograph-derived qCXR-bioage is a reliable and explainable tool for estimating biologic age.
  • qCXR-bioage demonstrates significant prognostic value for predicting mortality, including cardiovascular causes.
  • This approach offers a novel method for risk stratification using conventional radiography.