We are excited for the upcoming Computing in Cardiology conference in Madrid, Spain. Our SMASH-HCM partners have been busy preparing for several posters and presentations! 11 abstracts were accepted. They are the result of collaborations between our partners from Tampere University, the Politecnico di Milano, the University of Bologna, the University of Oxford, and the University of Rennes. We congratulate the team for their fantastic dissemination work!
Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac condition, in which the heart muscle becomes abnormally thick, reducing the heart’s ability to efficiently pump blood. The disease affects people in different ways, which makes understanding how well a patient’s heart is functioning and estimating risk challenging.
Because of the several upcoming presentations at CinC, we want to highlight the six talks and five posters. Each presentation is listed below with general information of when and where it will take place, who is presenting it and what it will be about.
Presentations at CinC 2026
A Framework for Personalized Cardiovascular Models in Hypertrophic Cardiomyopathy
by Francesca Menna on Tuesday 22.09.2026, 09:45 – 10:00, Session S33.
In this study, the researchers developed a framework for creating personalised computer models of the cardiovascular system in people with HCM. The model aims to better understand the underlying mechanisms of myocardial deformation. The approach combines clinical measurements with computer simulations to reproduce how the heart contracts and how the blood flows through the heart.
The framework was tested using data from 50 patients with hypertrophic cardiomyopathy at the Rennes Universtity Hospital. The patients underwent 2D-speckle-tracking echocardiography. Speckle-tracking echocardiography is a technique that uses ultrasound to analyse the motion of tissues or blood in the heart. A set of 85 parameters describing the mechanics of the heart and blood circulation was used to tailor the models to individual patients. The resulting models were able to reproduce the patients’ clinical measurements with good accuracy.
This work represents an important step towards developing digital twins for HCM: personalised virtual representations of a patient’s cardiovascular system. In the future, such models could help researchers better understand the mechanisms underlying HCM and contribute to more personalised assessment of disease and patient risk.
Vessel Biomechanics and Smooth Muscle Active Force in the Coronary Circulation: A Computational Model
by Nicole Anderton on Tuesday 22.09.2026, 14:00 – 14:15, Session 52.
The coronary circulation – the network of blood vessels that supplies the heart muscle with oxygen and nutrients – comprises multiple highly interdependent subsystems that control blood pressure and flow. These processes occur across different scales and influence one another, making it difficult to capture the coronary circulation as a whole in computer models. So far, no model has been able to capture the true multi-layer complexity of the coronary circulation.
In this study, a new multi-scale computer model of the coronary circulation was developed which brings several of these complex processes together. The model combines simulations of blood pressure and flow with the mechanical behaviour of blood vessel walls. At the level of the smallest vessels, it also incorporates the behaviour of smooth muscle cells, which affect the diameter of blood vessels by contracting or relaxing, thus regulating blood flow.
The results show that the different components of the model can successfully interact across scales. When blood pressure changes, the vessel walls and smooth muscle cells adapt, altering the diameter, resistance and elasticity of the vessels. Future work will study additional processes, such as the influence of heart contractions, nitric oxide-mediated vessel relaxation, vessel branching, the wider systemic circulation and hormonal regulation.
Multi-Resolution Cardiovascular Model Coupling in Hypertrophic Cardiomyopathy
by Arthur Ben-Tolila and James Coleman on Tuesday 22.09.2026, 14:15 – 14:30, Session 52.
Arthur will be presenting, the results of a collaboration between the teams at the University of Oxford and Université de Rennes. The researchers have demonstrated how different computer models of the cardiovascular system can be connected and personalised using data from an individual with HCM. The Oxford team developed a detailed 3D model of the heart’s electrical activity, while the Rennes team developed a 0D cardiovascular model that represents the heart chambers, blood circulation, blood pressure regulation and blood flow leaving the heart.
First the 3D model was personalised using data from a patient’s electrocardiogramm (ECG). This allowed the model to reproduce how the electrical signals travel through the heart. Information from this model was then transferred into the 0D model, where it was further personalised using clinical measurements such as heart rate and heart chamber volumes.
The combined models were able to reproduce the patient’s clinical data with good accuracy. This demonstrates the successful coupling and personalisation of multi-scale cardiovascular models, paving the way towards integrated HCM digital twins.
Impact of Ionic Remodelling on Cardiac Dysfunction in Hypertrophic Cardiomyopathy: Multiscale Electromechanical Insights
by Abdallah Hasaballa on Tuesday 22.09.2026, 16:00 – 16:15, Session 62.
In this study, the research team examined the changes caused by HCM to individual heart muscle cells, influencing how they produce electrical signals, contract and relax, and handle calcium. They used a detailed computer model of the human heart to link processes occurring inside the individual heart muscle cells with the contraction and relaxation of the heart as a whole. This allowed the researchers to investigate how changes associated with HCM could affect both the heart’s pumping function and the electrical signals seen on an electrocardiogram (ECG).
The researchers first simulated the effects of a mutation in the MYH7 gene, one of the genes commonly associated with HCM. The mutation alone caused the heart muscle to contract more strongly than normal. They then investigated additional changes that can develop in the electrical behaviour of heart muscle cells as the disease progresses.
The results of this study are the first findings that provide computational evidence that links changes in individual heart cells to changes in the function of the entire heart. It highlights the potential value of this type of multiscale computer modelling for future research.
Stratification of Ectopic Pacing Sites Using a Conduction Block Pre-Test for Functional Arrhythmic Substrates
by James A. Coleman on Wednesday 23.09.2026, 09:00 – 09:15, Session 72.
Abnormal heart rhythms, or arrhythmia, can happen when the electrical signals do not travel normally through the heart. When assessing arrythmic risk, S1-S2 protocls are usually used in cardiac electrophysiology simulations. S1 and S2 are also known as the “lub-dub” sounds that the heart makes. But, the stimulus for S2 can originate anywhere in the myocardium, the thick and muscular middle layer of the heart.
This study looked at where the electrical disturbances, that cause arrhythmia, might develop. One method to examine this is by virtually stimulating the heart at many different locations and to observe hot its electrical activity responds. However, to test every possible location it requires a lot of computing time. The research team has therefore developed and evaluated a pre-screening method that identifies areas of the heart where an additional electrical stimulus is more likely to encounter tissue that has not yet recovered from the previous heart beat.
Their method was evaluated using more than 9,000 heart simulations and successfully identified locations that were more likely to trigger ventricular tachycardia. This approach could make it considerably faster and more efficient to estimate arrhythmia risk using cardiac digital twins.
Development and Validation of a Cellular Automaton Framework for Simulating Heterogeneous Ventricular Restitution Dynamics and Functional Re-entry
by Giada Sira Romitti on Wednesday 23.09.2026, 14:00 – 14:15, Session 91.
Giada will present this study during the Young Investigators Award (YIA) semifinal session. In this study, a faster and more efficient computer modelling approach, a cellular automaton, for simulating the electrical activity of the heart was developed. This new method simplifies some of the calculations while retaining important information about how electrical signals are generated and spread through heart tissue. It can also account for biological differences in electrical behaviour within the same heart, which is an important consideration when studying heart disease.
Hypertrophic Cardiomyopathy was used as an example to test the developed approach. They compared the faster model with simulations that were much more detailed and found that it could reproduce the heart’s electrical behaviour with good accuracy. It was also able to reproduce complex electrical patterns that are associated with serious arrythmias, such as ventricular tachycardia.
The results show that it might be possible to perform large numbers of heart simulations more efficiently and without losing the important information needed to study arrythmia risk.
Posters at CinC 2026
In Silico Validation of Ventricular Activation Sequences Inferred from 12-Lead ECGs for Cardiac Digital Twins
by James A. Coleman on Tuesday 22.09.2026, 12:30 – 14:00, Session P1_5.
Creating accurate digital twins of the heart requires models that reflect how electrical signals spread through an individual patient’s heart. In this study a method was tested that uses a standard 12-lead ECG together with information about the heart’s anatomy to recreate this electrical activation.
The approach was evaluated using 98 virtual hearts, including models that represent both healthy hearts and those with hypertrophic cardiomyopathy. The aim of this study is to make digital heart models more personalised and improve their ability to reproduce the electrical behaviour of a patient’s heart.
Mutation-Specific Benefits of Ranolazine in HCM: a Multiscale Analysis of the MYBC3:c.772G>A Variant
by Abdallah Hasaballa on Tuesday 22.09.2026, 12:30 – 14:00, Session P1_5.
In a collaboration between the University of Bologna (UniBo) and the University of Oxford (UOX), researchers used a quantitative, multiscale modelling approach to investigate a specific genetic variant associated with hypertrophic cardiomyopathy (HCM).
The researchers simulated the effects of the “MYBPC3.772G>A variant” at different levels, from individual heart muscle cells to a 3D model of the whole heart. They also investigated ranolazine, a medication that affects electrical activity in heart cells, to understand how it could influence the changes caused by this HCM variant.
The simulations suggest that ranolazine could help improve the heart’s electrical recovery between beats, while having only a limited effect on its pumping ability. The study demonstrates how combining models across different biological scales can help researchers investigate the mechanisms of specific HCM mutations and their potential response to treatments.
Increased Delayed Afterdepolarisation Susceptibility in Hypertrophic Cardiomyopathy Cardiomyocytes Under Exercise Conditions
by Boluwatife Adebowale on Tuesday 22.09.2026, 17:15 – 18:45, Session P2_5.
Exercise can affect the electrical activity of the heart, but exactly how it may trigger abnormal heart rhythms in people with hypertrophic cardiomyopathy (HCM) is not yet fully understood.
The research team used computer models of heart muscle cells to compare healthy cells with cells showing changes associated with HCM under conditions designed to mimic some of the effects of exercise. The HCM models were more than twice as likely to develop abnormal electrical activity after stimulation and tended to experience these disturbances for longer.
The findings provide new insight into the cellular mechanisms that may contribute to arrhythmia risk in HCM during exercise and identify processes within heart cells that could be investigated further as potential treatment targets.
A Population-of-Models Capturing Vascular Smooth Muscle Cell Variability
by Nicole Anderton on Wednesday 23.09.2026, 12:30 – 13:30, Session P3_5.
Smooth muscle cells in blood vessel walls help control vessel diameter, blood pressure and blood flow. However, these cells can behave differently between individuals , which is something that current computer models often overlook.
Researchers created 10,000 computer models of smooth muscle cells to represent this natural biological variation. The models were tested against experimental data and used to simulate the effects of nifedipine, a medication that relaxes blood vessels.
This approach could help make future cardiovascular computer models more realistic and support research into blood flow, individual differences and responses to medication.
Optimization algorithm performance comparison for hypertrophic cardiomyopathy-modified in-silico cardiomyocytes
by Elina Anniina Nurkkala and Nicole Anderton on Wednesday 23.09.2026, 12:30 – 13:30, Session P3_5.
Computer models of heart muscle cells are a valuable tool to help researchers understand diseases such as hypertrophic cardiomyopathy (HCM) and investigate the effects of different treatments. However, making these models accurately reflect a particular genetic variant can require complex and time-consuming calculations.
In this study, researchers compared three different computational methods for adapting heart cell models to two genetic variants associated with HCM. All three methods produced realistic results, with only relatively small differences in their performance and computing time.
The findings suggest that choosing the right biological measurements and model parameters may be more important than the specific computational method used. This can help researchers develop more efficient and reliable personalised models of HCM.