Analysis of electrophysiologic data acquired on PhysioHeartTM platform (ex-vivo beating heart)

LifeTec Group is a contract research organization that utilizes their in-house developed simulators to evaluate medical devices and provide realistic training environments to cardiologists and surgeons. One of these simulators is the PhysioHeart^TM platform, an isolated ex-vivo beating porcine heart. It makes use of slaughterhouse byproducts of animals that are being slaughtered for consumption meat. A heart and blood from the same pig are being harvested in the slaughterhouse and treated as a donor organ. Next, the heart is transported to the LifeTec Group laboratory where a heart lung machine is prepared to oxygenate and warm the blood. The heart will be prepared to connect it to the platform, and after a short rehabilitation period it will be defibrillated, and it starts beating again. 

The PhysioHeart^TM can provide valuable information since it is pumping and contracting like a real heart does and it is being used for years to study effects of e.g., valve repairs/replacements and other structural heart related devices. However, less is known about its electrical activity and behaviour, and that is why LifeTec Group participates in a project to study electrophysiology of the platform. 

A start has been made with generating epicardial activation maps by making use of rudimentary equipment. Parameters as wave propagation velocity and activation-recovery intervals are being determined as well. A 6x8 electrode grid has been developed that is being placed on the outside of the heart to measure the electrical signals from the heart. From these acquired signals, the local activation times on the heart can be derived for each electrode, which can give insightful information when diagnosing heart rhythm disorders. Another hypothesis we have is function decline of the heart can be detected at an earlier stage compared to the hemodynamic parameters we are monitoring, which makes acting on it easier and more effective.  

Assignment

Currently the analysis of these signals is being done offline after the experiment, and it is sensitive to errors. To act swiftly, we would require the analysis to be automated and (semi) live, i.e., within 2-3 minutes. 

LifeTec Group also believes more information can be derived from this data compared to what is currently being done. Therefore, we are looking for a student that thinks it would be interesting to derive information out of these datasets and/or to make a workflow and graphical user interface to better represent this data in an automated and fast way.

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Last modified: 2023-08-17