Estimating cardiomyofiber strain in vivo by solving a computational model.

Area of Science:

• Cardiovascular Imaging
• Biomedical Engineering
• Computational Mechanics

Background:

• Cardiac contraction relies on cardiomyocyte shortening, a key metric for assessing heart function.
• Accurate measurement of myofiber strains is crucial for understanding cardiac mechanics.
• Existing methods for calculating myofiber strains can be susceptible to experimental noise.

Purpose of the Study:

• To develop and validate a novel method for measuring aggregate cardiomyocyte (myofiber) strains using Magnetic Resonance Imaging (MRI) data.
• To reduce the impact of experimental noise on strain calculations.
• To compare the physiological relevance of the new method's results with standard approaches.

Main Methods:

• Recasting myofiber strain calculation as a boundary value problem (BVP) to minimize noise effects.
• Utilizing MRI data for voxel-wise displacements and myofiber orientation.
• Validating the BVP approach with an analytical phantom and applying it to in vivo swine data.

Main Results:

• The boundary value problem (BVP) approach effectively reduces experimental noise in myofiber strain calculations.
• The method does not require a calibrated material model, offering independence from specific myocardial properties.
• In vivo application demonstrated a more physiological distribution of myofiber strains compared to direct differentiation methods.

Conclusions:

• The proposed boundary value problem (BVP) method offers a robust and noise-resilient approach for quantifying myofiber strains from cardiac MRI.
• This technique provides more physiologically accurate strain distributions, enhancing the diagnostic potential of cardiac MRI.
• The independence from material models simplifies the application and broadens the utility of this novel method in cardiovascular research.