Spline surface interpolation for calculating 3-D ventricular strains from MRI tissue tagging

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Computational Mechanics

Background:

• Accurate assessment of myocardial strain is crucial for diagnosing cardiac conditions.
• Magnetic Resonance Imaging (MRI) with tissue tagging is a common technique for visualizing heart motion.
• Developing robust methods for quantifying finite strains from MRI tag deformations is an ongoing challenge.

Purpose of the Study:

• To develop and validate a novel method for approximating continuous smooth distributions of finite strains in the ventricles.
• To reconstruct three-dimensional (3-D) displacement fields from MRI tissue tagging data.
• To assess the accuracy of the strain calculation method against finite element (FE) simulations.

Main Methods:

• A semiautomated algorithm was used to identify tag lines and their intersections in MRI images.
• Spline surface interpolation was employed for 3-D reconstruction of displacement fields from orthogonal MRI views.
• A measurement analysis solution was defined by fitting coefficients to tag surface displacements to represent the transformation between cardiac states.
• Validation involved simulating deformations using FE models and incorporating measured tag line detection errors.

Main Results:

• The 3-D displacement reconstruction errors averaged 2.4% of the average FE solution.
• The 3-D strain fitting errors averaged 15.9% of the average 3-D FE elasticity solution.
• The strain calculation method magnified small errors in tag line detection and 3-D displacement reconstruction, with overall agreement of 19.2% in 3-D simulations when detection errors were included.

Conclusions:

• The developed method can accurately reconstruct 3-D displacements of MRI tag lines.
• The strain calculation is sensitive to errors in tag line localization and 3-D displacement reconstruction.
• Further refinement is needed to mitigate the impact of small errors on strain quantification.