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Cited by 356Cardiac Imaging and DiagnosticsLung Cancer Diagnosis and TreatmentMedical Imaging and Pathology Studies

Association of Coronary Artery Calcification and Mortality in the National Lung Screening Trial: A Comparison of Three Scoring Methods

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Chiles, Caroline, Duan, Fenghai, Gladish, Gregory W., Ravenel, James G., Baginski, Scott G., Snyder, Bradley S., DeMello, Sarah, Desjardins, Stephanie S. +2 more·2015·Radiology
DOI 10.1148/radiol.15142062PMC PMC5137795
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Abstract

PURPOSE: To evaluate three coronary artery calcification (CAC) scoring methods to assess risk of coronary heart disease (CHD) death and all-cause mortality in National Lung Screening Trial (NLST) participants across levels of CAC scores. MATERIALS AND METHODS: The NLST was approved by the institutional review board at each participating institution, and informed consent was obtained from all participants. Image review was HIPAA compliant. Five cardiothoracic radiologists evaluated 1575 low-dose computed tomographic (CT) scans from three groups: 210 CHD deaths, 315 deaths not from CHD, and 1050 participants who were alive at conclusion of the trial. Radiologists used three scoring methods: overall visual assessment, segmented vessel-specific scoring, and Agatston scoring. Weighted Cox proportional hazards models were fit to evaluate the association between scoring methods and outcomes. RESULTS: In multivariate analysis of time to CHD death, Agatston scores of 1-100, 101-1000, and greater than 1000 (reference category 0) were associated with hazard ratios of 1.27 (95% confidence interval: 0.69, 2.53), 3.57 (95% confidence interval: 2.14, 7.48), and 6.63 (95% confidence interval: 3.57, 14.97), respectively; hazard ratios for summed segmented vessel-specific scores of 1-5, 6-11, and 12-30 (reference category 0) were 1.72 (95% confidence interval: 1.05, 3.34), 5.11 (95% confidence interval: 2.92, 10.94), and 6.10 (95% confidence interval: 3.19, 14.05), respectively; and hazard ratios for overall visual assessment of mild, moderate, or heavy (reference category none) were 2.09 (95% confidence interval: 1.30, 4.16), 3.86 (95% confidence interval: 2.02, 8.20), and 6.95 (95% confidence interval: 3.73, 15.67), respectively. CONCLUSION: By using low-dose CT performed for lung cancer screening in older, heavy smokers, a simple visual assessment of CAC can be generated for risk assessment of CHD death and all-cause mortality, which is comparable to Agatston scoring and strongly associated with outcome.

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  • As our deep learning system does not require human input, this makes it an 'end-to-end' solution for accurate and time-efficient cardiovascular risk assessment in clinical settings.

    “As our deep learning system does not require human input, this makes it an ‘end-to-end’ solution for accurate and time-efficient cardiovascular risk assessment in clinical settings32,33.”

    From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [33]

    The Discussion (page not provided) reports that visual CAC assessment stratified cardiac risk and was faster and simpler than the other methods studied. But the method required radiologists; this paper does not establish that a deep learning system needs no human input or provides an end-to-end clinical solution. (LLM, conf=0.84)

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Authors
Chiles, C., Duan, F., Gladish, G. W., Ravenel, J. G., Baginski, S. G., Snyder, B. S., DeMello, S., Desjardins, S. S., Munden, R. F., & For the NLST Study Team
Affiliations
  • The University of Texas MD Anderson Cancer Center (US)
  • Houston Methodist (US)
  • American College of Radiology (US)
ORCID
Venue
Radiology
Publisher
Radiological Society of North America (RSNA)
Published
2015-07
Volume
276
Issue
1
Pages
82-90
ISSN
  • 0033-8419 (ISSN-L)
  • 1527-1315
DOI
10.1148/radiol.15142062
PMC
PMC5137795
OpenAlex
W2036208966
Cited by
356
References
2
Citations by year
2026: 29 · 2025: 44 · 2024: 34 · 2023: 38 · 2022: 38 · 2021: 45 · 2020: 28 · 2019: 34 · 2018: 27 · 2017: 19 · 2016: 19 · 2015: 1
FWCI
17.83
Type
journal article
Language
en
Open access
Locations
  • Radiology (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health (3u10ca079778-14s1)
  • National Cancer Institute (U01CA079778, U10 CA079778, U10CA180794)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Medical Imaging and Pathology Studies
Keywords
coronary artery calcification, Agatston score, coronary heart disease mortality, all-cause mortality, National Lung Screening Trial, low-dose CT, cardiovascular risk stratification, risk prediction model, coronary artery disease risk assessment, cardiovascular risk prediction models, cardiovascular risk prediction
MeSH terms
Coronary Artery Disease, Female, Humans, Lung Neoplasms, Male, Middle Aged, Retrospective Studies, Tomography, X-Ray Computed, Case-Control Studies, Risk Assessment, Early Detection of Cancer, Vascular Calcification

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