Cardiac metabolic changes on 18 F-positron emission tomography after thoracic radiotherapy predict for overall survival in esophageal cancer patients

A roadmap for modelling radiation-induced cardiac disease

Cardiac risk mitigation is a major priority in improving outcomes for cancer survivors as advances in cancer screening and treatments continue to decrease cancer mortality. More than half of adult cancer patients will be treated with radiotherapy (RT); therefore it is crucial to develop a framework for how to assess and predict radiation-induced cardiac disease (RICD). Historically, RICD was modelled solely using whole heart metrics such as mean heart dose. However, data over the past decade has identified cardiac substructures which outperform whole heart metrics in predicting for significant cardiac events. Additionally, non-RT factors such as pre-existing cardiovascular risk factors and toxicity from other therapies contribute to risk of future cardiac events. In this review, we aim to discuss the current evidence and knowledge gaps in predicting RICD and provide a roadmap for the development of comprehensive models based on three interrelated components, (1) baseline CV risk assessment, (2) cardiac substructure radiation dosimetry linked with cardiac-specific outcomes and (3) novel biomarker development.

Novel Functional Radiomics for Prediction of Cardiac Positron Emission Tomography Avidity in Lung Cancer Radiotherapy

PURPOSE

Traditional methods of evaluating cardiotoxicity focus on radiation doses to the heart. Functional imaging has the potential to provide improved prediction for cardiotoxicity for patients with lung cancer. Fluorine-18 (18F) fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) imaging is routinely obtained in a standard cancer staging workup. This work aimed to develop a radiomics model predicting clinical cardiac assessment using 18F-FDG PET/CT scans before thoracic radiation therapy.

METHODS

Pretreatment 18F-FDG PET/CT scans from three study populations (N = 100, N = 39, N = 70) were used, comprising two single-institutional protocols and one publicly available data set. A clinician (V.J.) classified the PET/CT scans per clinical cardiac guidelines as no uptake, diffuse uptake, or focal uptake. The heart was delineated, and 210 novel functional radiomics features were selected to classify cardiac FDG uptake patterns. Training data were divided into training (80%)/validation (20%) sets. Feature reduction was performed using the Wilcoxon test, hierarchical clustering, and recursive feature elimination. Ten-fold cross-validation was carried out for training, and the accuracy of the models to predict clinical cardiac assessment was reported.

RESULTS

From 202 of 209 scans, cardiac FDG uptake was scored as no uptake (39.6%), diffuse uptake (25.3%), and focal uptake (35.1%), respectively. Sixty-two independent radiomics features were reduced to nine clinically pertinent features. The best model showed 93% predictive accuracy in the training data set and 80% and 92% predictive accuracy in two external validation data sets.

CONCLUSION

This work used an extensive patient data set to develop a functional cardiac radiomic model from standard-of-care 18F-FDG PET/CT scans, showing good predictive accuracy. The radiomics model has the potential to provide an automated method to predict existing cardiac conditions and provide an early functional biomarker to identify patients at risk of developing cardiac complications after radiotherapy.

Nuclear medicine imaging methods of early radiation-induced cardiotoxicity: a ten-year systematic review

Introduction

Radiotherapy has significantly improved cancer survival rates, but it also comes with certain unavoidable complications. Breast and thoracic irradiation, for instance, can unintentionally expose the heart to radiation, leading to damage at the cellular level within the myocardial structures. Detecting and monitoring radiation-induced heart disease early on is crucial, and several radionuclide imaging techniques have shown promise in this regard.

Method

In this 10-year review, we aimed to identify nuclear medicine imaging modalities that can effectively detect early cardiotoxicity following radiation therapy. Through a systematic search on PubMed, we selected nineteen relevant studies based on predefined criteria.

Results

The data suggest that incidental irradiation of the heart during breast or thoracic radiotherapy can cause early metabolic and perfusion changes. Nuclear imaging plays a prominent role in detecting these subclinical effects, which could potentially serve as predictors of late cardiac complications.

Discussion

However, further studies with larger populations, longer follow-up periods, and specific heart dosimetric data are needed to better understand the relationship between early detection of cardiac abnormalities and radiation-induced heart disease.

Impact of Blood Parameters and Normal Tissue Dose on Treatment Outcome in Esophageal Cancer Patients Undergoing Neoadjuvant Radiochemotherapy

Despite technological advances, normal tissue sparing in photon beam irradiation is still challenging. Since in esophageal cancer this may inflict damage on the lungs, heart and bone marrow, possibly impacting on outcome, the aim of this study was to investigate the association of normal tissue dose and blood parameters on the survival of patients having undergone neoadjuvant radiochemotherapy (RCTx) followed by surgery. This retrospective study included 125 patients irradiated to 40−41.4 Gy with photons or protons combined with concurrent chemotherapy. On initial and restaging 18F-FDG-PET/CT, the lungs and heart were contoured as organs at risk for which standardized uptake values (SUV) were evaluated. The mean radiation dose (Dmean) to the lungs and heart, the volume of the lungs receiving at least 20 Gy (V20Gy_lung) and various pre- and per-treatment blood parameters were included in the Cox regression analyses. Results: The median follow-up time was 19.8 months and median overall survival 37 months (95% confidence interval: 16−58.9 months). In multivariate analysis, higher radiation doses to the lungs and heart were statistically significantly associated with decreased overall survival (Dmean_lung: p < 0.001; V20Gy_lung: p < 0.002; Dmean_heart: p = 0.005). Neither the 18F-FDG-PET nor blood parameters were predictive for overall survival. In patients with locally advanced esophageal cancer treated with RCTx, the radiation dose to the heart and lungs was significantly associated with overall survival.