Topic: CardioOncology in Cardiovascular Health, Medicine and Aging

As global populations age and cancer survival rates continue to rise, cardio-oncology has emerged as a critical field addressing the complex cardiovascular challenges faced by older cancer patients. Cardio-oncology focuses on preventing and managing cardiovascular toxicities resulting from cancer therapies. In parallel, artificial intelligence (AI) offers transformative tools to enhance precision in risk assessment, early detection, and personalized care. This Special Issue of The Journal of Cardiovascular Aging explores the synergistic potential of these disciplines, highlighting research that bridges cancer treatment, aging biology, and cardiovascular medicine to improve outcomes in this increasingly vulnerable population. ​

Focus of This Special Issue​

This collection features original research articles and reviews on cardio-oncology, with a specific lens on aging populations. Older adults represent the largest group affected by both cancer and cardiovascular disease (CVD), with age itself intensifying susceptibility to treatment-related cardiac injury. Common oncologic therapies, including chemotherapies (e.g., anthracyclines), targeted agents (e.g., HER2 inhibitors), and immunotherapies, frequently induce cardiovascular toxicities, which are further exacerbated by age-related declines in myocardial reserve and the presence of multiple comorbidities. However, traditional risk stratification tools often fail to capture the complex interactions among cancer treatments, aging physiology, and subclinical cardiac dysfunction, highlighting an urgent need for innovative, data-driven solutions. ​

Innovative Technologies for Precision Cardio-Oncology​

AI’s ability to analyze high-dimensional data—including imaging, electronic health records, and multi-omics datasets—has revolutionized the landscape of cardio-oncology. Machine learning models can detect subtle changes in cardiac function, such as early alterations in global longitudinal strain on echocardiography, long before they become evident with conventional methods. By integrating clinical data, genomic information, and geriatric assessments (e.g., frailty indices and functional status), AI algorithms generate personalized risk profiles that enable proactive interventions to balance oncologic efficacy with cardiovascular protection. Moreover, multi-omic integration through AI helps identify biomarkers and mechanistic pathways linking cancer therapies to cardiac dysfunction in older adults, facilitating the development of tailored cardiovascular risk models that account for aging physiology.

Looking Ahead​ 

As we navigate an era marked by aging societies and increasingly complex cancer therapies, the integration of innovative technologies into cardio-oncology holds great promise for transforming patient care—from risk assessment at diagnosis to long-term survivorship monitoring. By fostering collaboration among oncologists, cardiologists, geriatricians, and data scientists, this Special Issue aims to advance the adoption of Cardio-oncology solutions that prioritize precision, equity, and patient-centered outcomes. We encourage contributions that apply AI-based strategies to uncover aging-related biomarkers, therapeutic targets, or predictive models to optimize cardiovascular health and guide personalized cardioprotective interventions in older cancer patients.

Cardio-oncology, artificial intelligence, cardiovascular, aging