Heart volume on health checkup CT scans inversely correlates with pulse rate: data-driven analysis using
Kanato Masayoshi1, Masahiro Hashimoto2, Naoki Toda1
1Department of Radiology, Keio University School of Medicine, Tokyo, Japan.
Japanese Journal of Radiology
|May 5, 2025
Summary
Pulse rate is the strongest predictor of heart volume on CT scans, more so than blood pressure. This study highlights the effectiveness of AI in analyzing large CT datasets for health insights.
Area of Science:
- Medical Imaging
- Cardiology
- Artificial Intelligence
Background:
- Computed tomography (CT) enables detailed cardiac imaging.
- Analyzing large CT datasets for health correlations is challenging.
- Deep learning offers potential for automated image analysis.
Purpose of the Study:
- To correlate heart volume on CT with general health checkup data.
- To assess the utility of a deep-learning tool for CT data analysis.
- To identify key health indicators related to heart volume.
Main Methods:
- Retrospective analysis of CT images and health data (2013, 2018).
- Heart volume quantified using the TotalSegmentator deep-learning model.
- Statistical analysis included Spearman's correlation and ANOVA, adjusting for covariates.
Main Results:
- Pulse rate showed the strongest inverse correlation with heart volume.
- A 10 bpm increase in pulse rate correlated with a 0.5% decrease in cardiothoracic ratio.
- Hemoglobin, hematocrit, total protein, albumin, and cholinesterase also showed weak inverse correlations.
Conclusions:
- Pulse rate is a significant covariate of heart volume, outweighing other cardiovascular markers.
- AI-assisted, data-driven research on CT big data is feasible and effective.
- Findings support using AI for large-scale medical image analysis.
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