Efficient characterization of inhomogeneity in contraction strain pattern.

Area of Science:

• Cardiovascular Physiology
• Computational Biology
• Biomedical Engineering

Background:

• Cardiac dyssynchrony is prevalent in heart failure (HF) and increases mortality.
• Cardiac resynchronization therapy (CRT) benefits many HF patients but not all.
• Quantitative characterization of mechanical dyssynchrony is crucial for understanding CRT response.

Purpose of the Study:

• To quantitatively characterize mechanical dyssynchrony using a 3D finite element model.
• To develop and validate a novel method for analyzing cardiac contraction strain patterns.
• To compare the proposed method with the conventional CURE index for assessing dyssynchrony.

Main Methods:

• Utilized a 3D finite element model of canine ventricles with simulated synchronous, right ventricular apical pacing (RVA), and left ventricular free wall pacing (LVFW) conditions.
• Employed piecewise cubic interpolation to generate detailed lookup tables (LUTs) of strain data.
• Calculated and visualized strain in the fiber direction using strain binning, 2D area maps, and 3D point clouds.

Main Results:

• Both RVA and LVFW pacing simulations showed delayed maximum contraction and greater strain disparities compared to the synchronous simulation.
• The developed strain analysis method provided more detailed spatial and temporal information than the CURE index.
• Strain binning effectively visualized strain fields and compartmentalized strain patterns.

Conclusions:

• The novel strain analysis method offers a more comprehensive assessment of mechanical dyssynchrony than the CURE index.
• Detailed characterization of contraction strain patterns can improve understanding of patient response to CRT.
• This modeling approach aids in visualizing and quantifying cardiac mechanical behavior in dyssynchronous states.