Cardiac Digital Twins: Heart Research Breakthroughs
- A new study utilizing more than 3,800 anatomically precise digital hearts has revealed key insights into how age, sex, and lifestyle contribute to heart disease and electrical function.
- The creation of these cardiac "digital twins" allowed scientists to determine that age and obesity can alter the heart's electrical properties, possibly explaining the link between these factors...
- The digital twins also illuminated that electrocardiogram (ECG) variations between men and women are mainly attributable to heart size differences, rather than variations in electrical signal conduction.
Researchers have harnessed the power of over 3,800 digital heart twins to uncover critical insights into heart disease. This groundbreaking study reveals the impact of age, obesity, and sex on heart function, with implications for personalized treatments and drug growth. The cardiac digital twins, meticulously crafted using real patient data and advanced AI, offer a revolutionary approach to understanding heart disease. News Directory 3 is following this exciting story. Discover how these virtual replicas are poised to transform how we approach healthcare by tailoring heart device settings and identifying new drug targets. What new revelations about heart disease will emerge next?
Digital Heart Twins Reveal Heart Disease Risk Factors
Updated May 31, 2025
A new study utilizing more than 3,800 anatomically precise digital hearts has revealed key insights into how age, sex, and lifestyle contribute to heart disease and electrical function. Researchers from King’s Collage London, Imperial College London, and The Alan Turing Institute collaborated on the project.
The creation of these cardiac “digital twins” allowed scientists to determine that age and obesity can alter the heart’s electrical properties, possibly explaining the link between these factors and increased heart disease risk. The findings were published in Nature Cardiovascular Research.
The digital twins also illuminated that electrocardiogram (ECG) variations between men and women are mainly attributable to heart size differences, rather than variations in electrical signal conduction. these insights could help clinicians improve treatments, such as tailoring heart device settings or identifying new drug targets for specific patient groups, enhancing personalized care for those with heart conditions and addressing heart disease.
The cardiac digital twins were constructed using real patient data and ECG readings from the UK Biobank and a cohort of patients with heart disease. These digital replicas enable exploration of heart functions that are tough to measure directly, offering a new approach to understanding and treating heart disease and improving heart function.
Recent advancements in machine learning and AI facilitated the creation of this large volume of digital twins, reducing manual tasks and accelerating the building process. digital twins, in general, are computer models simulating physical objects or processes. While frequently enough costly and time-intensive to develop, they can provide novel insights into system behavior.
“Our research shows that the potential of cardiac digital twins goes beyond diagnostics. By replicating the hearts of people across the population, we have shown that digital twins can offer us deeper insights into the people at risk of heart disease. It also shows how lifestyle and gender can affect heart function,” Professor Steven Niederer, senior author and Chair in Biomedical Engineering at Imperial College London, saeid.
Professor Pablo Lamata, report author and professor of biomedical engineering at King’s College London, said, “These insights will help refine treatments and identify new drug targets. By developing this technology at scale, this research paves the way for their use in large population studies. This could lead to personalised treatments and better prevention strategies, ultimately transforming how we understand and treat heart diseases.”
What’s next
Researchers plan to link heart function to genes, potentially revealing how genetic variations influence heart function and paving the way for more precise and personalized care for patients in the future, further advancing the understanding of heart disease.