Validating MRI-Derived Myocardial Stiffness Estimates Using In Vitro Synthetic Heart Models.

Area of Science:

• Biomedical Engineering
• Cardiovascular Research
• Medical Imaging

Background:

• Impaired cardiac filling due to increased passive myocardial stiffness is key in heart failure.
• Estimating in vivo myocardial stiffness uses cardiac MRI and pressure data with inverse finite element models.
• Quantifying the accuracy of these stiffness estimates is limited by the lack of in vivo ground truth.

Purpose of the Study:

• To create and validate a method for accurately measuring passive myocardial stiffness.
• To assess the accuracy of MRI-driven computational constitutive modeling for estimating heart material stiffness.

Main Methods:

• 3D printing of homogenous, isotropic, hyperelastic heart phantoms with varying geometries and stiffness.
• Simulating diastolic filling using an MRI-compatible left ventricular inflation system.
• Estimating phantom stiffness via inverse finite element analysis (Neo-Hookean model) using MRI and pressure data.

Main Results:

• Estimated stiffness values (215.7 and 512.3 kPa) showed good agreement with ground truth values (226.2 and 526.4 kPa).
• Overall, estimated stiffnesses demonstrated a low error ([Formula: see text]) compared to ground truth across all phantom models.
• The study successfully validated the computational approach for synthetic material stiffnesses within the 200-500 kPa range.

Conclusions:

• MRI-driven computational constitutive modeling can accurately estimate synthetic heart material stiffness.
• This approach provides a validated method for assessing passive myocardial stiffness, crucial for heart failure research.
• The use of 3D-printed phantoms offers a reliable ground truth for validating computational models in cardiovascular mechanics.