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Cited by 75Cardiac Imaging and DiagnosticsLung Cancer Diagnosis and TreatmentMedical Imaging and Pathology Studies

Quantification of coronary artery calcium in nongated CT to predict cardiovascular events in male lung cancer screening participants: Results of the NELSON study

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Takx, Richard A.P., Išgum, Ivana, Willemink, Martin J., van der Graaf, Yolanda, de Koning, Harry J., Vliegenthart, Rozemarijn, Oudkerk, Matthijs, Leiner, Tim +1 more·2015·Journal of Cardiovascular Computed Tomography
DOI 10.1016/j.jcct.2014.11.006
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Abstract

Objective To evaluate the incremental prognostic value of the number and maximum volume of coronary artery calcifications over modified Agatston score strata, age, pack-years, and smoking status for predicting cardiovascular events. Methods A total of 3559 male current and former smokers received a CT examination for lung cancer screening. Smoking characteristics, patient demographics, and physician-diagnosed cardiovascular events were collected. Images were acquired without electrocardiography gating on 16-slice CT scanners. The association between the presence of both fatal and nonfatal cardiovascular events and the predictors was quantified using Cox proportional hazard analysis. Results Median follow-up period was 2.9 years. Incident cardiovascular events occurred in 186 participants. Adjusted hazard ratios for modified Agatston score strata of 1 to 10, 11 to 100, 101 to 400, and >400 were 3.39 (95% confidence interval [CI], 1.20-9.59), 6.52 (95% CI, 2.73-15.60), 6.58 (95% CI, 2.75-15.78), and 12.58 (95% CI, 5.42-29.16), respectively. Moreover, comparing the models with and without modified Agatston score strata to the model with age, pack-years, and smoking status yielded a significantly better net reclassification improvement (NRI; 27.3%; P < .0001). Adding the number of calcifications to the model with age, pack-years, smoking status, and modified Agatston score strata resulted in a slightly better NRI (1.68%; P = .0490) with a hazard ratio of 1.13 (95% CI, 1.05-1.21) per 10 calcifications. The incremental prognostic information contained in the volume of the largest calcification was not statistically significant (NRI, 0.14%; P = .3458). Conclusion Cardiovascular event rate increased with higher numbers of calcified lesions. The number but not maximum volume of calcifications has independent, although minimal, prognostic value over age, pack-years, smoking status, and modified Agatston score strata in our population.

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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 [32]

    The Conclusions report that CT-derived calcium scores accurately predicted cardiovascular events in male smokers without a CVD history, supporting the risk-assessment rationale. The paper does not establish time efficiency or clinical performance for the citing authors’ deep learning system. Its own automated measurements were visually checked and manually corrected when needed (Imaging predictors, §2.3). (LLM, conf=0.84)

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Authors
Takx, R. A. P., Išgum, I., Willemink, M. J., van der Graaf, Y., de Koning, H. J., Vliegenthart, R., Oudkerk, M., Leiner, T., & de Jong, P. A.
Affiliations
  • University Medical Center Utrecht (NL)
  • University Medical Center Groningen (NL)
Corresponding author
Takx, Richard A.P.
ORCID
Venue
Journal of Cardiovascular Computed Tomography
Publisher
Elsevier BV
Published
2015-01
Volume
9
Issue
1
Pages
50-57
ISSN
  • 1876-861X (ISSN-L)
  • 1934-5925
DOI
10.1016/j.jcct.2014.11.006
OpenAlex
W1991337537
Cited by
75
References
1
Citations by year
2026: 6 · 2025: 7 · 2024: 7 · 2023: 8 · 2022: 9 · 2021: 10 · 2020: 4 · 2019: 4 · 2018: 9 · 2017: 5 · 2016: 5 · 2015: 1
FWCI
2.87
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of cardiovascular computed tomography (publishedVersion)
  • PubMed (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion)
  • Pure Amsterdam UMC (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
  • Utrecht University Repository (Utrecht University) (submittedVersion)
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, cardiovascular events, lung cancer screening, smokers, prognostic value, net reclassification improvement, cardiovascular risk prediction, pack-years, smoking status, age, male patients, 16-slice CT
MeSH terms
Artificial Intelligence, Belgium, Calcinosis, Coronary Artery Disease, Humans, Lung Neoplasms, Male, Middle Aged, Netherlands, Radiographic Image Interpretation, Computer-Assisted, Sensitivity and Specificity, Smoking, Tomography, X-Ray Computed, Reproducibility of Results, Comorbidity, Causality, Incidence, Survival Rate, Coronary Angiography, Age Distribution, Risk Assessment, Early Detection of Cancer

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