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Evidence-Based Investigation of Coronary Calcium Score in Cardiac Computed Tomography.

Authors :
Shim, Jina
Kim, Kyuseok
Lee, Youngjin
Source :
Applied Sciences (2076-3417); Oct2024, Vol. 14 Issue 19, p8906, 13p
Publication Year :
2024

Abstract

This study aimed to verify whether increased body mass index (BMI) increases the noise in computed tomography (CT) images due to heightened effective thickness, impacting calcium scores. Calcium scores were measured in 30 sets of images from normal weight patients. Calcium scores were also measured in 30 sets of images from hypothetical overweight and obese patients, generated by extracting the noise from overweight and obese patients, respectively, and inserting it into the images of normal weight patients. In addition, a phantom study was performed using three calcium phantoms with intensities below the threshold of 130 Hounsfield units and three calcium phantoms with intensities above this threshold. Calcium scores were measured in the absence and presence of a bolus at the heart level to simulate an obese patient. All calcium scores were measured by three radiologists. In the patient study, the total calcium scores of the hypothetical overweight and hypothetical obese groups were 14.93% (p = 0.014) and 22.19% (p = 0.012) higher than those of the normal weight group. In the phantom study, the total calcium score of the six calcium phantoms without a bolus was 1.61% higher at a tube voltage of 120 kV than at 100 kV, and 12.06% higher at a slice thickness of 1 mm than at 3 mm. The total calcium score of the six calcium phantoms with a bolus was 0.13% higher at a tube voltage of 120 kV than at 100 kV, and 14.76% higher at a slice thickness of 1 mm than at 3 mm. These results can be used as a reference to train automated calcium scoring programs on effective thickness through deep learning to reduce calcium score errors caused by increased BMI. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
19
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
180273523
Full Text :
https://doi.org/10.3390/app14198906