Quantification of coronary artery calcium using ultrafast computed tomography
Open accessAbstract
Ultrafast computed tomography was used to detect and quantify coronary artery calcium levels in 584 subjects (mean age 48 +/- 10 years) with (n = 109) and without (n = 475) clinical coronary artery disease. Fifty patients who underwent fluoroscopy and ultrafast computed tomography were also evaluated. Twenty contiguous 3 mm slices were obtained of the proximal coronary arteries. Total calcium scores were calculated based on the number, areas and peak Hounsfield computed tomographic numbers of the calcific lesions detected. In 88 subjects scored by two readers independently, interobserver agreement was excellent with identical total scores obtained in 70. Ultrafast computed tomography was more sensitive than fluoroscopy, detecting coronary calcium in 90% versus 52% of patients. There were significant differences (p less than 0.0001) in mean total calcium scores for those with versus those without clinical coronary artery disease by decade: 5 versus 132, age 30 to 39 years; 27 versus 291, age 40 to 49 years; 83 versus 462, age 50 to 59 years; and 187 versus 786, age 60 to 69 years. Sensitivity, specificity and predictive values for clinical coronary artery disease were calculated for several total calcium scores in each decade. For age groups 40 to 49 and 50 to 59 years, a total score of 50 resulted in a sensitivity of 71% and 74% and a specificity of 91% and 70%, respectively. For age group 60 to 69 years, a total score of 300 gave a sensitivity of 74% and a specificity of 81%. The negative predictive value of a 0 score was 98%, 94% and 100% for age groups 40 to 49, 50 to 59 and 60 to 69 years, respectively. Ultrafast computed tomography is an excellent tool for detecting and quantifying coronary artery calcium.
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The Agatston score is a validated composite metric of CAC density and volume derived from non-contrast CT and is the most widely used method for CAC quantification.
“The Agatston score, a validated composite metric of CAC density and volume derived from non-contrast CT, is the most widely used method for CAC quantification.2”
From Prognostication and clinical opportunities with AI for coronary artery calcium: a scoping review (2026) · cites this paper as [2]
The Abstract describes a CT calcium score based on lesion area and peak Hounsfield number, and reports interobserver agreement and associations with clinical coronary artery disease. It does not specify that the scans were non-contrast or establish that this is the most widely used CAC quantification method. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThe CT coronary calcium score is a measure of the burden of coronary atherosclerosis and one of the most widely accepted measures of cardiovascular risk.
“The CT coronary calcium score is a measure of the burden of coronary atherosclerosis and is one of the most widely accepted measures of cardiovascular risk5,6.”
From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [5]
The Abstract describes a CT calcium score that quantifies coronary calcification and reports higher scores in subjects with clinical coronary artery disease, supporting its relevance to coronary disease. It does not establish that the score measures the full burden of coronary atherosclerosis or that it is one of the most widely accepted measures of cardiovascular risk. (LLM, conf=0.85)
Experimental — accuracy not yet measuredCoronary artery calcium is an accurate predictor of cardiovascular events.
“Coronary artery calcium is an accurate predictor of cardiovascular events.”
From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [5]
The Abstract reports that coronary calcium scores distinguished subjects with and without clinical coronary artery disease and gives predictive values for that diagnosis. It does not report whether calcium predicts subsequent cardiovascular events, which is the outcome claimed. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThe CAC score was measured manually by expert readers using the method by Agatston and Janowitz on dedicated workstations, as reported in the parent FHS, PROMISE, and ROMICAT-II studies.
“The CAC score was measured manually by expert readers using the method by Agatston and Janowitz5,6 on dedicated workstations, as reported in the parent FHS17, PROMISE19, and ROMICAT-II20 studies.”
From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [5]
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- Authors
- Agatston, A. S., Janowitz, W. R., Hildner, F. J., Zusmer, N. R., Viamonte, M., & Detrano, R.
- Affiliations
- Mount Sinai Medical Center (US)
- ORCID
- Agatston, Arthur S.
- Venue
- Journal of the American College of Cardiology
- Publisher
- Elsevier BV
- Published
- 1990-03
- Volume
- 15
- Issue
- 4
- Pages
- 827-832
- ISSN
- 0735-1097 (ISSN-L)
- OpenAlex
- W2153785016
- Cited by
- 7,786
- References
- 0
- Citations by year
- 2026: 280 · 2025: 422 · 2024: 394 · 2023: 447 · 2022: 411 · 2021: 452 · 2020: 435 · 2019: 318 · 2018: 298 · 2017: 339 · 2016: 350 · 2015: 389 · 2014: 298 · 2013: 317 · 2012: 277
- FWCI
- 7.29
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of the American College of Cardiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Coronary Artery Anomalies
- Health Sciences › Medicine › Surgery › Coronary Interventions and Diagnostics
- Keywords
- coronary artery calcium, ultrafast computed tomography, calcium scoring, coronary artery disease, fluoroscopy, interobserver agreement, sensitivity and specificity, coronary artery calcification
- MeSH terms
- Adult, Aged, Calcinosis, Coronary Disease, Female, Fluoroscopy, Humans, Male, Middle Aged, Predictive Value of Tests, Sensitivity and Specificity, Tomography, X-Ray Computed, Observer Variation, Coronary Angiography
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