Machine Learning Based Analysis of Heart and Cardiac Substructures for Radiation-Induced Cardiac Toxicity From Breast Cancer Radiotherapy

Abstract

Radiation-induced cardiac toxicity is an importantissue of breast RT. Although a relationship between mean heart dose and acute coronary event (ACE) risk was reported in previous study, the specific relationships between doses to cardiac structures or their sub-regions and subsequent toxicity have not been well defined. In this study, we studied the effect of radiation on specific heart segments on subsequent cardiac toxicity.From the 1294 patients with breast cancer where previously demonstrated a relationship between mean heart dose and ACE, 21 patients who developed HF following breast RT and 39 with ACE were identified after an independent review by cardiologists. The study included 21 and 39 controls for respective toxicity who were matched according to age, comorbidities, and physical activity. For each patient who received radiotherapy, substructures were manually drawn, and then dose-distribution parameters of heart and substructures (Mean, Maximum (Max) dose, Relative volume at least given dose from 5-50 Gy in 5 Gy increments) were collected from CT planning data. To specify most critical regions for developing ACE, analysis using High-dimensional Cox regression model (SNet) was performed to reveal the effect of radiation on specific heart segments on subsequent cardiac toxicity.In HF (n = 42) and ACE (n = 78) cohorts, characteristics between case and control were well matched. Mean time to develop heart failure, acute coronary events were 40.0 months and 42.2 months, respectively. In HF cohort, there was no significant difference not only in the mean heart dose (3.7 Gy vs 3.1 Gy, P = 0.652), but also in the mean left ventricle (LV) (5.0 Gy vs 4.1 Gy, P = 0.587), mean right ventricle (RV) (4.8 Gy vs 3.6 Gy, P = 0.473). On the other hand, in ACE cohort, there was significant difference in mean dose of heart (2.9 Gy vs 1.3 Gy, P = 0.015), left atrium (LA) (1.0 Gy vs 0.5 Gy, P = 0.008), LV (3.7 Gy vs 1.5 Gy, P = 0.028), left anterior descending artery (LAD) (6.6 Gy vs 2.4 Gy, P = 0.028) and right atrium (RA) (1.5 Gy vs 0.9 Gy, P = 0.025). In univariate analysis, mean dose of heart, LA, LV, LAD and RA was significant factors for acute coronary event free survival. ((Heart; P = 0.006, Hazard ratio (HR) 1.139, 95% Confidence Interval (CI) 1.035-1.253) (LA; P = 0.002, HR 1.735, 95% CI 1.209-2.490), (LV; P = 0.018, HR 1.079, 95% CI 1.012-1.150), (LAD; P = 0.031, HR 1.032, 95% CI 1.002-1.064), (RA; P = 0.008, HR = 1.307, 95% CI 1.068-1.598)). For predicting ACE risk for breast cancer patients, SNet model suggested nomogram based on mean and max LA dose, LAD V10, 15, 20, mean heart dose, mean RA dose and RV V35 in the order of higher predicted point variation. Based on this risk stratification model, event free survival significantly showed difference (P = 0.013).There was significant difference between cardiac substructure dose parameters in ACE cohort, but not in HF cohort. Further analysis using convolution neural network will be performed to specify most critical region to be spared.