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Updated: May 12, 2026
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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
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Deep learning-based post-hoc noise reduction improves quarter-radiation-dose coronary CT angiography
Tomoro Morikawa1, Tatsuya Nishii2, Yuki Tanabe1
1Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, Japan.
European Journal of Radiology
|June 12, 2025
Summary
Deep learning-based noise reduction significantly enhances quarter-dose coronary CT angiography (CCTA) image quality. This deep learning-based noise reduction improves diagnostic accuracy for coronary artery disease assessment.
Area of Science:
- Radiology
- Artificial Intelligence
- Medical Imaging
Background:
- Coronary CT angiography (CCTA) is crucial for diagnosing coronary artery disease.
- Reducing radiation dose in CCTA is a significant clinical goal.
- Deep learning-based noise reduction (DLNR) offers potential for dose reduction without compromising image quality.
Purpose of the Study:
- To assess the impact of DLNR on image quality, CAD-RADS assessment, and diagnostic performance.
- To compare quarter-dose CCTA with DLNR against full-dose CCTA.
- To validate DLNR on external datasets for CCTA applications.
Main Methods:
- Retrospective review of 221 patients undergoing electrocardiogram-gated CCTA.
- Utilized dose modulation for quarter-dose and full-dose acquisitions.
- Applied a residual dense network for denoising quarter-dose images.
- Assessed image quality, CAD-RADS agreement, and diagnostic performance for stenosis detection.
Main Results:
- DLNR reduced noise in quarter-dose CCTA from 37 HU to 18 HU (P < 0.001).
- DLNR improved CAD-RADS agreement from moderate to excellent (0.82).
- Denoised images showed superior AUC (0.97) for significant stenosis detection compared to original quarter-dose images (0.93, P = 0.032).
Conclusions:
- DLNR significantly enhances image quality in quarter-dose CCTA.
- DLNR improves CAD-RADS assessment and diagnostic performance for significant stenosis.
- DLNR is a promising technique for reducing radiation dose in CCTA while maintaining diagnostic efficacy.
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