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JACC CardioOncol
JACC CardioOncol
JACC: CardioOncology
2666-0873
Elsevier

S2666-0873(24)00221-7
10.1016/j.jaccao.2024.07.003
Mini-Focus Issue: Radiation Therapy
Editorial Comment
Optimizing Cardiovascular Risk Prediction From CT Imaging at the Radiation Oncology Point of Care
Atkins Katelyn M. MD, PhD katelyn.atkins@cshs.org
@_katelynatkins
ab∗
Nikolova Andriana P. MD, PhD b
a Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California, USA
b Department of Cardiology, Cedars-Sinai Medical Center, Los Angeles, California, USA
∗ Address for correspondence: Dr Katelyn M. Atkins, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, California 90048, USA. katelyn.atkins@cshs.org@_katelynatkins
20 8 2024
8 2024
20 8 2024
6 4 541543
© 2024 Published by Elsevier on behalf of the American College of Cardiology Foundation.
2024

https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Corresponding Author

Key Words

cardiac events
left atrium
lung cancer
MACE
radiotherapy
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pmcIn a study reported in this issue of JACC: CardioOncology, Walls et al1 evaluated the prognostic utility of select radiotherapy (RT) planning computed tomographic (CT) cardiac volumetric parameters for predicticommng major adverse cardiac events (MACE) after RT. This study is an effort to enhance the gamut of clinical and imaging biomarkers available for up-front cardiovascular (CV) risk stratification in patients with non–small cell lung cancer (NSCLC), who are at substantial risk for CV morbidity because of pre-existing CV risk factors and treatment-associated CV toxicity. Furthermore, as therapeutic advances in the field of lung cancer have led to dramatic improvements in survival (ie, immune checkpoint inhibitor therapy), the competing risk for CV disease has prominently emerged. RT remains a cornerstone of NSCLC treatment, with well-recognized CV toxicities stemming from off-target radiation exposure to vital cardiac and vascular structures. The determination that CV toxicity manifests in patients with lung cancer within 1 to 2 years has catapulted the quest for biomarkers to identify the highest risk patients who would benefit most from close monitoring and aggressive medical optimization.

Walls et al1 conducted a retrospective analysis of 478 patients with locally advanced NSCLC from the NI-HEART (Northern Ireland Cardiovascular Health Events After Radiation Therapy) study to determine whether readily available imaging parameters from RT planning CT (or staging positron emission tomographic/CT) scans were associated with MACE following RT. They defined MACE as grade ≥ 3 atrial arrhythmia, acute heart failure (HF), and acute myocardial infarction (AMI). Notably, this differs from the standard 5-point MACE definition (AMI, stroke, CV death, unstable angina, and HF). The inclusion of arrhythmias among MACE is important, as studies have highlighted the high prevalence of atrial fibrillation and other arrhythmias in recipients of thoracic RT and a relationship of radiation dose exposure to specific cardiac substructures with that risk.2, 3, 4 Among several baseline CT cardiac volumetric parameters analyzed, the investigators identified 2 that were associated with specific adverse events. Baseline left atrial volume (LAV) showed the highest predictive capacity for atrial arrhythmia (C index = 0.70), and LAV was significantly associated with atrial arrhythmia after accounting for left atrial (LA) maximum radiation dose (Dmax). In a similar model predicting HF, left ventricular (LV)/right ventricular (RV) volume ratio showed the highest predictive capacity for HF (C index = 0.71) and was associated with increased risk after accounting for mean LV radiation dose and other prognostic factors. The investigators did not observe a significant association between coronary artery calcium (CAC) and the risk for AMI or overall survival, though events were few (n = 16), and CV event association was limited to myocardial infarction. Although CAC is a powerful atherosclerotic CV disease risk predictor in the general population, preclinical models have demonstrated that ischemia and infarction represent major inciting events for remodeling mechanisms (eg, fibrosis) that play a role in the development of arrhythmias. As such, CAC should be studied in context of diverse cardiac event prediction and not necessarily limited to ischemic events outcomes. Indeed, a recent study by No et al5 linked baseline CAC with grade ≥ 3 cardiac Common Terminology Criteria for Adverse Events, comprising myocardial, constrictive, valvular, and conduction events.

The pathophysiological plausibility for these findings is supported by echocardiographic studies that have demonstrated the prognostic utility of cardiac chamber volumes. LAV index is thought to reflect the chronicity of exposure to elevated cardiac filling pressures, as can be seen with LV systolic and diastolic dysfunction, which can trigger profibrotic remodeling pathways that augment future atrial fibrillation risk. In fact, LAV index can provide prognostic information incremental to clinical data and standard echocardiographic predictors and has been linked to all-cause mortality, HF hospitalizations, and stroke in both the general population and high-risk CV risk cohorts.6 Similarly, changes in LV geometry and function can be seen with various myocardial diseases, and LV end-diastolic and end-systolic dimensions have been found to carry important prognostic implications after AMI, in valvular heart disease, and in HF management. Importantly, however, cardiac dimensional parameters vary by sex, body habitus (height, weight, or both), ethnicity, fitness, and age. Thus, it is standard to index volumes to body habitus (most commonly body surface area), with the addition, preferably, of sex- and age-adjusted normal values. Although studies have been designed to establish reference values for CT chamber dimensions,7 most CT cardiac parameters represent small cohorts of healthy individuals reflective of specific ethnicity or geography and have not been validated in multicenter and ethnically diverse cohorts. Walls et al1 do not report that cardiac volumes were indexed to body habitus or account for sex-specific values. Furthermore, the predictive power of the LA and LV/RV volume parameters in this study was benchmarked according to the median value specific to this cohort from a single institution in Ireland. As such, even though these findings are thought provoking, they require further investigation with standard indexing and validation in larger multicenter cohorts, with the investigation of specific cutoff values that can be meaningfully translated into clinical practice.

The work by Walls et al1 also highlights the complex interplay among factors that influence cardiac events and whether this translates into a discernable impact on survival in this patient population. In the investigators’ atrial arrhythmia model (Table 2), LAV was associated with an increased risk, with an HR of 1.01 per milliliter (P = 0.024), though conversely, in the Cox survival model (Table 4), LAV had the same absolute magnitude of risk (HR: 0.99 per milliliter; P = 0.002), albeit with differing directionality, appearing protective against mortality. The investigators speculate that perhaps the clinical presentation of an atrial arrhythmia might prompt CV optimization, which might in turn improve survival in these patients. Ultimately, findings such as these contribute to the growing body of evidence underscoring the importance of RT-associated cardiac toxicity studies using specific cardiac event endpoints rather than overall survival alone as a surrogate endpoint to assess factors important for CV risk.

Walls et al1 further observed an association between maximum heart radiation dose and survival, though they did not account for other dosimetric parameters that have been linked to mortality, such as the heart base, left anterior descending coronary artery, and LA. Arguably, however, given the multifactorial nature of mortality in these patients, models focusing on fine-mapping radiation dose exposure to cardiac substructures linked to specific cardiac outcomes will better refine the predictive ability of RT dosimetric parameters. Therefore, as Walls et al are proposing putative imaging biomarkers for CV risk prediction following lung cancer RT, it would be important to demonstrate their additive value to other emerging biomarkers. Namely, in the model for atrial fibrillation, the investigators account for LA Dmax but not their recently identified pulmonary vein dose parameters, which outperformed LA Dmax,3 and there did not appear to be any additional explanatory power of LA Dmax when accounting for LAV in this cohort.

Last, consistent with prior studies, Walls et al1 illustrate the high baseline CV risk burden characteristic of patients with NSCLC, with a median QRISK3 score of 18.7%, CAC prevalence of 85%, and established cardiac disease in 55%, though only 59% were on statins. This is a recurrent finding across similar studies, in which patients are notoriously underoptimized from a CV risk prevention perspective. Therefore, as research efforts continue to identify ever more sophisticated CV prognostic biomarkers, the findings of Walls et al1 and others are a cautionary lesson that one should not forget the importance of guideline-based baseline medical optimization and adequate treatment of CV risk factors.

Funding Support and Author Disclosures

Dr Atkins has received honoraria from OncLive, outside the submitted work. Dr Nikolova has reported that she has no relationships relevant to the contents of this paper to disclose.

The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center.
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References

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