Optimization of cardiac resynchronization therapy based on a cardiac electromechanics-perfusion computational model

Area of Science:

• Computational modeling
• Cardiovascular physiology
• Biomedical engineering

Background:

• Cardiac resynchronization therapy (CRT) is effective for left bundle branch block (LBBB) patients with mechanical dyssynchrony.
• A significant portion of CRT patients (approx. 1/3) do not respond to treatment.
• Understanding factors influencing CRT response is crucial for improving patient outcomes.

Purpose of the Study:

• To develop an electromechanics-perfusion computational model to investigate factors affecting CRT response.
• To identify optimal pacing sites for CRT based on coronary perfusion.
• To explore the impact of ischemia on CRT effectiveness.

Main Methods:

• Developed a computational model integrating left ventricular (LV) geometry, coronary vascular networks, and electrophysiological properties.
• Calibrated the model using swine data, matching LV pressure, volume, and coronary flow measurements under pacing.
• Simulated CRT responses at various pacing sites and perfusion levels, including ischemic conditions.

Main Results:

• Without ischemia, the basal-lateral endocardial region was predicted as the optimal pacing site, improving LV function by 20% and reducing activation time.
• In the presence of ischemia, a non-ischemic region became optimal when ischemic region perfusion dropped below 30%.
• Pacing within an ischemic region yielded minimal benefit at low perfusion levels; optimal sites minimized LV activation time.

Conclusions:

• CRT response is significantly influenced by the interplay between pacing site selection and coronary artery perfusion.
• Optimizing pacing site based on perfusion status may enhance CRT efficacy and improve responder rates.
• The findings suggest personalized CRT strategies considering individual coronary perfusion patterns are warranted.