Cloud native EDA tools & pre-optimized hardware platforms
Posted on 31 August 2021 by Rebecca Bryan
Digital twins are growing in importance as a resource for reproducing complex anatomies and carrying out simulations to study the relationship between the body and medical devices. One of the key advantages for the medical industry involves being able to collect data through virtual testing in order to complement clinical trials and add to regulatory evidence for manufacturers. Medtronic Inc. are one of the companies making advances in this area, and recently work published by Dr Kevin Sack used Simpleware software to create a digital twin for investigating atrioventricular (AV) block through a validated electromechanical full-heart model.
Figure 1. Schematic illustrating the connection between the electromechanical four-chamber heart and the lumped circulatory system composed of compliance and resistance terms.
Medtronic constructed and validated a subject-specific, four-chamber porcine heart model to investigate coupled electro-mechanical phenomena from in vivo data. The full workflow is briefly summarized:
From this study, Medtronic was able to demonstrate that, in addition to the interrupted flow, AV block causes elevated stress and strain throughout the heart during diastole following the missed ventricular beat. More generally, the project validated the
electromechanical function of a four-chamber beating heart model to investigate pathological dysfunction and gain valuable insights into the heart.
With digital twins becoming more established as a research tool for medical device manufacturers and clinical professionals,
the results achieved by this Medtronic study show their great potential for accelerating new therapies and understanding of performance.
Furthermore, the flexibility offered by computational models means that data can be obtained that would otherwise be very difficult or
risky to collect from patients.
We're excited to see what the next steps will be for using digital twins as part of computational workflows, from developing new and improved
devices and helping with regulatory clearances. Simpleware software is well-placed to enable quick and accurate segmentation of image data for these
cases, especially with our recent launch of AI-enabled tools for speeding up common workflows when processing scans.
Figure 2: Triggering activation in the normal (middle) and AV block (top) electromechanically coupled full heart model over a complete cycle. Timing events (a -f) correspond to positions marked in left ventricle pressures (bottom).
Read the full presented at Computing in Cardiology (CinC 2020), 13-16 September 2020, Rimini, Italy.
If you would like to know more, please contact us. Our technical specialists will be happy to show you Simpleware software and our Machine Learning-based solutions for any anatomy.