Can Routine Imaging for Lung Cancer Radiotherapy Planning Predict Cardiac Mortality?

By: Sarah Campen, PharmD
Posted: Thursday, March 10, 2022

A study published in JCO Clinical Cancer Informatics found that measuring coronary artery calcium from lung cancer radiotherapy planning computed tomography (CT) scans may provide valuable data for determining cardiac risk. Raymond H. Mak, MD, of Dana-Farber Cancer Institute and Brigham and Women’s Hospital, Boston, and colleagues identified an increased risk of all-cause mortality in patients with locally advanced lung cancer and elevated coronary artery calcium—one of the strongest predictors of atherosclerotic disease.

“Our proof-of-concept study strongly suggests that a previously developed [deep learning] system trained on cardiovascular imaging can be repurposed and applied to cancer-specific, radiotherapy planning CT scans to generate a quantitative [coronary artery calcium] score that is associated with the risk of mortality, despite the high competing risk of lung cancer death,” stated the study authors.

In this retrospective analysis, the researchers evaluated non–contrast-enhanced radiotherapy planning CT scans of 428 patients with locally advanced lung cancer using the deep-learning coronary artery calcium (DL-CAC) algorithm. Based on the DL-CAC score—a value determined by the size and volume of coronary calcium plaques—patients were grouped as being at very low risk (DL-CAC = 0) or elevated risk (DL-CAC ≥ 1).

The median follow-up was 18.1 months. In all, 61.4% of patients had a DL-CAC score ≥ 1. The risk of all-cause mortality was increased in patients with a DL-CAC score ≥ 1 compared with 0, with a 2-year estimate of 56.2% versus 45.4%, respectively (P = .04). There was also a trend toward increased risk of major adverse cardiac events with a DL-CAC score ≥ 1 versus 0 (7.3% vs. 1.2%) based on the 2-year estimate (P = .11).

“These observations illustrate a significant potential to apply this approach for automated cardiac risk stratification before the initiation of cancer therapy,” concluded the authors.

Disclosure: For full disclosures of the study authors, visit ascopubs.org.

JCO Clinical Cancer Informatics

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