Cardiovascular disease is the leading cause of death in developed and developing countries, even in Chile. Therefore, the possibility of improving clinical outcomes is a concern for all Sciences, including Mathematics, and Cristóbal Bertoglio, researcher at the Center for Mathematical Modeling of Universidad de Chile (CMM). He arrived recently to CMM from the Technical University of Munich and is investigating potential benefits that mathematical modeling can offer.
On April 10th, in front of an audience composed mainly of CMM academics and students from faculties of Engineering and Medicine, Bertoglio gave a briefing on the subject. There, he started by explaining the basis of the functioning of the heart. This muscle is activated by electrochemical impulses that move ventricles push blood to the lungs, where it is purified, and then to the rest of the body.
Mathematical modeling tries to replicate this chemical and physical heart dynamics. Thus, these models could be used for better therapies, as in the case of atrial arrhythmia. In some hearts, additional electrical stimulations that alter their normal contraction occur. To avoid these distortions spread, physicians burn parts of heart tissue. For doctors, the dilemma is where to intervene: should they cauterize more or less muscle regions? Today, they insert a catheter and choose to burn among certain preset locations in the left atrium. With mathematical models they could calculate in advance the impact of different options in each patient, focusing the therapy to cauterize less tissue.
Another treatment that could benefit from the mathematical modeling is cardiac resynchronization therapy (CRT). This uses a pacemaker that synchronizes the heartbeat and also stimulates the heart to evolve into its normal shape and pumping function. However, it fails in the 30% of cases.
“If you look at CRT surgeries, doctors place the probe where first the electrical stimulation is able to spread. One possibility is to help better choosing the stimulation site also based on the different mechanical responses that the model can predict,” explains Bertoglio. “Another idea is trying to predict whether a stimulation place will allow the heart return to its best form. These processes are regulated at the level of whole body, where the body measures flows, pressure and is accommodating and instructing the heart to do certain actions.”
Exams may also be more complete. For example, they can use biomarkers such as those used in blood tests. In these measurements, the levels of certain substances indicate the disease presence. Also, if you compare mathematical models with measurements in a quantitative way, you could analyze tissue properties, such as stiffness and contractility, and thus trying to detect biological processes that you can’t determine on tests currently.
“You have to find applications where doctors have more options for treatment. If there is just one option, modeling is only able to reproduce what physicians can directly observe from the clinical measurements and is less likely to provide an additional value” concludes Bertoglio.
