Researchers from King’s College London, Imperial College London, and the Alan Turing Institute have created more than 3,800 detailed digital replicas of human hearts. In a new study published in Nature Cardiovascular Research, the team showed that it is possible to produce personalized cardiac “digital twins” on a large scale using real patient data and clinical tests.
Digital twin technology allows scientists to simulate organs or tissues. This helps them understand how these organs work in ways that are difficult to measure directly using traditional methods. In this study, the cardiac digital twins were used to explore how age, sex, and lifestyle factors affect the heart’s electrical activity.
The study found that age and obesity change the heart’s electrical properties. This may explain why these factors increase the risk of heart disease. In contrast, differences between men and women in clinical heart measurements were mostly due to variations in heart size, not electrical conductivity.
“These findings will help improve treatments and identify new drug targets,” said Pablo Lamata, PhD, professor of biomedical engineering at King’s College London. “By developing this technology at scale, we can use it in large population studies. This could lead to more personalized treatments and better prevention strategies, transforming how we understand and treat heart disease.”
Previous research has shown that cardiac digital twins can aid clinical decisions and help tailor treatments for heart conditions like atrial fibrillation and cardiomyopathy. However, creating these digital models has been difficult and slow, which limited their widespread use.
Thanks to new advances in artificial intelligence (AI) and statistical tools, the researchers automated and sped up the process. Using magnetic resonance imaging (MRI) and electrocardiogram (ECG) data from 3,461 patients in the UK Biobank, they built a fully automated system that can create cardiac digital twins quickly and at a large scale. The models were then tested on a separate group of 359 patients with ischemic heart disease, confirming consistent changes related to age, sex, and body mass index (BMI).
“Our study shows that cardiac digital twins offer more than just diagnostics,” said Steven Niederer, PhD, professor of biomedical engineering at Imperial College London and lead author. “By replicating hearts from across the population, digital twins provide deeper insights into who is at risk for heart disease. They also reveal how lifestyle and gender affect heart function.”
Looking ahead, the researchers see strong potential for using digital twin technology on a population level. This could help identify new biomarkers, discover therapeutic targets, and predict both the benefits and side effects of current and future treatments.
“The digital heart models we have built set the stage for the next step in our work — linking heart function to genetic data,” said Shuang Qian, PhD, first author and visiting research associate at King’s College London. “This could help us understand how genetic differences affect heart function in new ways, leading to more precise and personalized care for patients in the future.”
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