Cardiac digital twins: a tool to investigate the function and treatment of the diabetic heart
File(s)
Published version
Author(s)
Strocchi, Marina
Hammersley, Daniel J
Halliday, Brian P
Prasad, Sanjay K
Niederer, Steven A
Type
Journal Article
Abstract
Diabetes increases the risk of cardiovascular disease (CVD) due to its multi-scale and diverse effects on cardiomyocyte metabolism and function, the circulation, and the kidneys. The complex relationship between organ systems affected by diabetes and associated comorbidities leads to challenges in estimating cardiovascular risk and stratifying optimal treatment strategies at the individual patient level. Most recently, sodium-glucose transport protein 2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP1) receptor agonists have been shown to offer substantial cardiac benefits. However, the direct or indirect mechanisms through which these agents protect the heart remain unclear, posing a challenge to patient selection. Amidst a growing burden of diabetes and increased therapeutic armamentarium, there is an important unmet need to develop more precise methods and technologies to understand the effects of diabetes and anti-diabetic treatment on the heart with faster timelines than conventional randomised controlled trials. Cardiac computational models could be used to improve our understanding of the cardiac changes in diabetes and to predict how a patient’s heart will respond to anti-diabetic treatment. In this review, we provide an overview of current cardiac computational models to investigate the diabetic heart and the cardiac effects of anti-diabetic treatment. We discuss how multi-scale and multi-physics models could be applied in future to support the development of novel therapeutic approaches and further improve the treatment of diabetic patients with different CVD risk.
Date Issued
2025-07-18
Date Acceptance
2025-06-24
Citation
Cardiovascular Diabetology, 2025, 24
ISSN
1475-2840
Publisher
BMC
Journal / Book Title
Cardiovascular Diabetology
Volume
24
Copyright Statement
© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Subjects
Heart
anti-diabetic treatment
cardiac computational model
cardiovascular outcome trials
diabetes
digital twin
in-silico trials
model
Publication Status
Published
Article Number
ARTN 293