Towards a personalized and dynamic CRT-D. A computational cardiovascular model dedicated to therapy optimization

Area of Science:

• Cardiovascular Physiology
• Medical Device Technology
• Computational Biology

Background:

• Cardiac resynchronization therapy (CRT) benefits a majority of patients, but 25-30% remain non-responders.
• Suboptimal atrioventricular (AV) and interventricular (VV) interval settings are potential causes for CRT non-response.
• Optimizing these intervals is crucial for enhancing CRT efficacy.

Purpose of the Study:

• To utilize a numerical cardiovascular model for optimizing AV and VV intervals in CRT patients.
• To investigate if personalized and dynamic interval adjustments can improve CRT outcomes.
• To compare model-derived optimization results with existing clinical data.

Main Methods:

• A previously developed numerical model of the cardiovascular system dedicated to CRT was employed.
• Echocardiographic data, systemic aortic pressure, and ECG were collected from 20 patients pre- and post-CRT.
• The model simulated patient data to optimize AV and VV intervals based on echocardiographic and electrocardiographic parameters.

Main Results:

• Optimized AV and VV intervals varied per patient and often changed at follow-up.
• The numerical model accurately reproduced clinical data, validated by Bland Altman analysis and t-tests (p > 0.05).
• Model-guided CRT demonstrated a 38.7% left ventricular remodeling and an 11% increase in ejection fraction.

Conclusions:

• The developed numerical model effectively reproduces patient conditions and CRT effects, both at baseline and follow-up.
• This model enables personalized and dynamic optimization of AV and VV intervals for CRT.
• Patient-tailored CRT, guided by this model, has the potential to improve outcomes compared to current literature.