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Published on: September 22, 2023
AUTOMATED AGATSTON SCORE COMPUTATION IN A LARGE DATASET OF NON ECG-GATED CHEST COMPUTED TOMOGRAPHY
Germán González1, George R Washko1, Raúl San José Estépar1
1Applied Chest Imaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA.
Insights
An automated method accurately calculates the Agatston score from chest CT scans, a key indicator of coronary artery disease. This technique correlates highly with traditional cardiac CT methods, simplifying disease assessment.
Area of Science:
- Radiology
- Cardiovascular Imaging
- Medical Image Analysis
Background:
- The Agatston score is a standard measure for coronary artery disease (CAD) using ECG-gated cardiac CT.
- Recent studies indicate strong correlation between Agatston scores from non-ECG-gated chest CT and cardiac CT.
Purpose of the Study:
- To develop and validate an automated method for calculating the Agatston score from standard chest CT images.
- To assess the feasibility of using non-ECG-gated chest CT for CAD risk assessment via automated Agatston scoring.
Main Methods:
- Developed an algorithm to detect coronary artery calcifications (CACs) in chest CT scans.
- Defined CACs as voxels ≥ 130 HU within coronary arteries.
- Employed image processing techniques including heart localization, region of interest generation, thresholding, and rule-based discrimination to identify CACs and exclude artifacts.
Main Results:
- The automated method achieved a high correlation with manual Agatston scoring.
- Pearson correlation coefficient (ρ) between manual and automated scores was 0.86 (p < 0.0001) in a cohort of 1500 patients.
Conclusions:
- The automated Agatston score calculation from chest CT is a reliable and accurate method.
- This approach offers a promising tool for non-invasive coronary artery disease assessment using readily available chest CT data.
Abstract:
The Agatston score, computed from ECG-gated computed tomography (CT), is a well established metric of coronary artery disease. It has been recently shown that the Agatston score computed from chest CT (non ECG-gated) studies is highly correlated with the Agatston score computed from cardiac CT scans. In this work we present an automated method to compute the Agatston score from chest CT images. Coronary arteries calcifications (CACs) are defined as voxels contained within the coronary arteries with a value greater or equal to 130 Hounsfield Units (HU). CACs are automatically detected in chest CT studies by locating the heart, generating a region of interest around it, thresholding the image in such region and applying a set of rules to discriminate CACs from calcifications in the main vessels or from metallic implants. We evaluate the methodology in a large cohort of 1500 patients for whom manual reference standard is available. Our results show that the Pearson correlation coefficient between manual and automated Agatston score is ρ = 0.86 (p < 0.0001).
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