Precision Prediction of Cardiotoxicity: Imaging, Biomarkers, Genetics, Risk Models, and Digital Innovation in Cardio-Oncology
A special issue of Cancers (ISSN 2072-6694).
Deadline for manuscript submissions: 31 August 2026 | Viewed by 408
Editor
Special Issue Information
Dear Colleagues,
The growing complexity of contemporary cancer therapies has intensified the need for accurate, early, and individualized prediction of cardiotoxicity. Current cardiotoxicity risk scores offer useful frameworks but show limited performance across diverse patient populations and treatment settings, and often fail to incorporate key determinants of vulnerability, including frailty, genetic background, sex-related biological differences, and social, racial, and national factors.
This Special Issue focuses on precision approaches to cardiotoxicity prediction, integrating advanced cardiovascular imaging, circulating biomarkers, multivariable risk scores, and genetic susceptibility with emerging artificial intelligence and machine learning-based models. Particular emphasis is placed on sex-related differences, biological heterogeneity, and the use of digital health technologies, including wearable devices and remote monitoring, to enhance risk stratification and longitudinal surveillance. Contributions spanning methodological innovation, translational research, and clinical implementation are welcome.
By bringing together multimodal data and digital tools, this Special Issue aims to advance personalized prediction strategies and to support more effective prevention and management of cancer therapy-related cardiovascular toxicity.
Dr. Kalliopi Keramida
Guest Editor
Manuscript Submission Information
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Keywords
- cardio-oncology
- imaging
- biomarkers
- genetics
- risk models
- digital innovation
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