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Related Experiment Video

Updated: Jul 24, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Deep learning-based age estimation from chest CT scans.

Ghazal Azarfar^1,2, Seok-Bum Ko³, Scott J Adams⁴

¹Department of Medical Imaging, University of Saskatchewan, Saskatoon, SK, Canada. azarfar.g@gmail.com.

International Journal of Computer Assisted Radiology and Surgery

|July 7, 2023

Summary

This summary is machine-generated.

Chest CT scans can estimate biological age, offering insights beyond chronological age. This new method predicts lung cancer risk more accurately than chronological age alone.

Keywords:

Age estimation Cancer risk Computed tomography Lung cancer Machine learning

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Area of Science:

Radiology
Medical Imaging
Artificial Intelligence in Medicine

Background:

Biological age estimation from medical imaging offers complementary clinical insights.
Chronological age is a standard metric, but biological age may provide a more nuanced understanding of health status.

Purpose of the Study:

To develop a method for estimating patient age using chest CT scans.
To evaluate if chest CT-derived estimated age is a superior predictor of lung cancer risk compared to chronological age.

Main Methods:

A deep learning model (Inception-ResNet-v2) was trained on 13,824 chest CT scans from the National Lung Screening Trial.
The model's performance was validated on a local dataset of 1849 CT scans.
Lung cancer risk was assessed by comparing individuals with CT-estimated age older than chronological age versus those with CT-estimated age younger than chronological age.

Main Results:

The age prediction model achieved a mean absolute error of 1.84 years and a Pearson's correlation coefficient of 0.97 on local data.
The model's attention was concentrated on lung-related areas.
Individuals with CT-estimated age older than chronological age had a 1.82 times higher relative risk of lung cancer.

Conclusions:

Chest CT-derived estimated age reflects biological aging processes.
Estimated age from chest CT scans may serve as a more accurate predictor of lung cancer risk than chronological age.
Further validation on larger, diverse populations is needed to generalize findings.