Can Artificial Intelligence Help Us in the Evaluation of Coronary Artery Calcification Scores by Acting as a Prognosticator in Patients That Are Operated on Due to Non-Small Cell Lung Cancer? A Pivotal Study
Open accessAbstract
Background: Non-small cell lung cancer (NSCLC) is the leading cause of death from malignancies, and surgical resection is the most effective form of treatment. Coronary artery disease (CAD) is a common comorbidity in patients with NSCLC. A coronary artery calcium (CAC) score correlates with the extent of CAD. We aimed to test whether an automated assessment of CAC scores helps to identify the population of patients with a higher risk of postoperative complications and worse overall survival (OS) after the surgical treatment of NSCLC. Methods: In this retrospective cohort study, the data of the patients who were surgically treated for NSCLC were matched with the reassessed preoperative CT images. The postoperative complication rates and overall survival were analyzed. The CAC score was evaluated automatically using the Syngo.via Siemens Healthcare software. Cardiac age was assessed according to Hoff et al. 2001. The prognosticators of postoperative complications and of OS were tested. Results: The data of 193 patients with complete data, an adherence to the inclusion and exclusion criteria, and that were operated between 2018 and 2019, were included. Cardiac age was a predictor of the cardiovascular and pulmonary complications rate (95%CI −0.007–0.203, p = 0.066, beta coefficient 0.098). In a multivariable stepwise regression analysis, operative access was a predictor of cardiovascular and pulmonary complications (95%CI −0.290–−0.111, p < 0.001, beta coefficient −0.200), cardiovascular complications (95%CI −0.161–−0.022, p = 0.011, beta coefficient −0.036), and the general complication rate (95%CI −0.370–−0.194, p < 0.001, beta coefficient −0.286). Kaplan–Meier curves were separated in the survival analysis of groups of patients with a cardiac age 0–69 years vs. an age of 70+ (92 vs. 92 patients) (in Cox regression analysis, HR = 1.678, 95%CI 0.847–3.292 p = 0.138). Conclusions: An automated CAC score assessment may be a potential and clinically meaningful prognosticator of both postoperative complications and OS in patients that are operated on due to NSCLC. Further studies are required.
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AI-CAC was predictive of haemodynamically significant CAD (CT-FFR ≤0.8), postoperative complications, and cancer therapy-related cardiac dysfunction.
“AI-CAC was predictive of haemodynamically significant CAD (CT-Fractional Flow Reserve ≤0.8),28 postoperative complications,21 and cancer therapy-related cardiac dysfunction.24”
From Prognostication and clinical opportunities with AI for coronary artery calcium: a scoping review (2026) · cites this paper as [21]
Citation 21 is attached to the postoperative-complications finding. The Results (page unavailable) report only a trend for automated cardiac age predicting cardiovascular and pulmonary complications in patients undergoing NSCLC surgery (p = 0.066); the Discussion calls it a potential prognosticator. Saying AI-CAC was predictive overstates that tentative finding. (LLM, conf=0.87)
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Prognostication and clinical opportunities with AI for coronary artery calcium: a scoping review
McDonald, V. J. F., Parsa, S., Mastrodicasa, D., Rodriguez, F., Langlotz, C., Maron, D. J., Sandhu, A. T., Dudum, R., & Jain, S. S. (2026) · BMJ Digital Health & AI · doi:10.1136/bmjdh-2026-000053
Guideline for the Comprehensive Perioperative Management of Older Patients With Lung Cancer (2025)
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- Authors
- Marjanski, T., Chmielecki, M., Klein-Awerjanow, K., Cytawa, W., Ciepialowska, P., Bilyk, A., Peksa, R., & Dudek, M.
- Affiliations
- Department of Thoracic Surgery, Faculty of Medicine, Medical University of Gdansk, 80-214 Gdansk, Poland
- Department of Cardiology, Faculty of Medicine, Medical University of Gdansk, 80-214 Gdansk, Poland
- Gdańsk Medical University (PL)
- Faculty of Medicine, Medical University of Gdansk, 80-214 Gdansk, Poland
- Department of Pathology, Faculty of Medicine, Medical University of Gdansk, 80-214 Gdansk, Poland
- Poznan University of Medical Sciences (PL)
- ORCID
- Venue
- Journal of Clinical Medicine
- Publisher
- MDPI AG
- Published
- 2024-11-01
- Volume
- 13
- Issue
- 21
- Pages
- 6579
- ISSN
- 2077-0383 (ISSN-L)
- PMC
- PMC11546565
- OpenAlex
- W4403968698
- Cited by
- 2
- References
- 21
- Citations by year
- 2026: 2
- FWCI
- 0.58
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Clinical Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac, Anesthesia and Surgical Outcomes
- Keywords
- coronary artery calcium score, non-small cell lung cancer, lung cancer surgery, artificial intelligence, postoperative complications, cardiovascular complications, pulmonary complications, overall survival, prognostic factors, surgical access, cardiac risk stratification
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