Simulation Platform To Evaluate Inversion Techniques For Magnetic Resonance Elastography Data

TL;DR

This paper introduces a comprehensive in-silico dataset and benchmarking platform for evaluating inversion algorithms in Magnetic Resonance Elastography, facilitating the development of more accurate tissue property assessments.

Contribution

It provides a detailed simulation dataset with known properties and demonstrates its use in evaluating a direct inversion scheme for MRE data analysis.

Findings

Reconstruction accuracy varies non-monotonically with spatial and temporal resolution.

Successful inhomogeneous domain reconstructions with clear interface boundaries.

Vascular inclusions cause a stiffening effect, increasing the recovered shear modulus.

Abstract

Magnetic Resonance Elastography (MRE) has become an essential tool in assessing the mechanical properties of soft tissues in-vivo, prompting significant progress in new inversion algorithms. This creates a need for a benchmarking framework to promote uniformity and accessibility. To address this, we introduce a comprehensive in-silico dataset acquired by solving the forward Finite Element calculations of shear wave propagation in a linear visco-elastic material. This dataset aims to serve as a platform for evaluating inversion schemes by providing data that can be used as input with known mechanical properties to these methods. It includes simulations on homogeneous cuboidal domains of varying spatial and temporal resolution, and an extension to more physiological variations, including material inhomogeneity and internal arterial pulsation. We present a comprehensive case study using simulated data as an input to a direct inversion (DI) scheme, which allows for an expedient local inversion into the underlying material parameters. When aiming to reconstruct the parameters describing the linear visco-elastic material behavior via DI, we find that due to compromised convergence properties of frequency-domain stencils, stemming from truncation and subtractive cancellation errors, the reconstruction accuracy depends non-monotonically on the spatial and temporal resolution of the measurement grid. For inhomogeneous domains, the reconstruction was successful with notable interface boundaries. In the presence of pressurized vascular inclusions, a general stiffening of the domain was noted, as the recovered shear modulus was higher than the one assumed in forward modeling. Our study highlights the potential of this dataset as a vital benchmarking tool for advancing the development and refinement of MRE techniques, contributing to more accurate and reliable assessment of soft tissue mechanics.