Association of echocardiographic radiomics-based features with cardiotoxicity effect in breast cancer patients from the CARDIOCARE project
Authors: Manikis G , Kalliatakis G , Marias K , Bouratzis V , Lakkas L , Naka A , Karanasiou G , Tsekoura D , Kampouroglou E , Keramida K , Papakonstantinou A , Constantinidou A , Mazzocco K , Cipolla C , Fotiadis D 
Published: January 2025

Abstract

Introduction
Improvements in breast cancer (BC) treatment including chemotherapy have increased significantly the BC survivors. However, higher BC survival rates have been compromised by life-threatening collateral toxic effects. Effects such as cardiomyopathy and heart failure, described as cardiotoxicity, have become main causes of comorbidity and mortality, having a great impact on patients’ quality of life.

Purpose
Leverage radiomics-based analysis to explore innovative, non-invasive echocardiography biomarkers that can associate with cardiotoxicity.

Method
A cohort of 28 prospective patients (above 60 years old, 10 cardiotoxic) of the EU-funded CARDIOCARE project [1] undergoing cardiotoxic antineoplasmatic therapy was utilized to investigate potential association between imaging features calculated from the end diastolic (ED) and end systolic (ES) apical 4- and 2-chamber views and patients’ cardiotoxicity status as defined by the project's cardiologists using imaging data (Left Ventricle Ejection Fraction , Global Longitudinal Strain) and blood test markers (high sensitive Troponin I and Nt-pro-Bnp). Imaging data were collected at baseline visit (start of the treatment) and 3 months after. A pre-trained deep neural network [2] was initially utilized to automatically segment the myocardium (MY) and the left ventricle (LV) from the ED and ES 4- and 2-chamber static views both at baseline (T0) and 3-month follow-up (T1). More than 1500 imaging features were calculated from all images of the MY and LV using radiomics, a state-of-the-art technique to elicit hidden image patterns using histogram, shape and textural features. Apart from radiomics at T0 and T1, time-dependent features (delta-radiomics) were also provided as the relative change in radiomics values between T0 and T1, aiming to reveal potential changes at the MY and LV areas through treatment. Cardiotoxicity status was defined at T1.

Results
A univariate analysis using the Wilcoxon rank-sum test identified a subset of 40 radiomics features (20 delta-radiomics and 20 from T1) to be considered statistically significant (p-value&lt;0.05) in differentiating cardiotoxic from non-cardiotoxic patients. Histogram and shape-based characteristics showed no association with cardiotoxicity status. Additionally, radiomics-based features at T0 were not statistically significant. All significant features corresponded to textural properties of the MY, indicating that the heterogeneity of the MY can be a significant factor for cardiotoxicity. 17 out of 20 T1 features were calculated from the 4-chamber view of the MY (19/20 from the ED). 15 delta-radiomics textural features were extracted from the 2-chamber view of the MY region at the ES.

Conclusion
Heterogeneity of the myocardium quantified by radiomics has potential diagnostic impact in assessing cardiotoxicity response, paving the way for the development of image-based risk stratification models for the early detection of cardiac toxicity.