Comparison of inversion methods inMRelastography: An open‐access pipeline for processing multifrequency shear‐wave data and demonstration in a phantom, human kidneys, and brain

Abstract

Purpose Magnetic resonance elastography (MRE) maps the viscoelastic properties of soft tissues for diagnostic purposes. However, different MRE inversion methods yield different results, which hinder comparison of values, standardization, and establishment of quantitative MRE markers. Here, we introduce an expandable, open‐access, webserver‐based platform that offers multiple inversion techniques for multifrequency, 3D MRE data. Methods The platform comprises a data repository and standard MRE inversion methods including local frequency estimation (LFE), direct‐inversion based multifrequency dual elasto‐visco (MDEV) inversion, and wavenumber‐based (k‐) MDEV. The use of the platform is demonstrated in phantom data and in vivo multifrequency MRE data of the kidneys and brains of healthy volunteers. Results Detailed maps of stiffness were generated by all inversion methods showing similar detail of anatomy. Specifically, the inner renal cortex had higher shear wave speed (SWS) than renal medulla and outer cortex without lateral differences. k‐MDEV yielded higher SWS values than MDEV or LFE (full kidney/brain k‐MDEV: 2.71 ± 0.19/1.45 ± 0.14 m/s, MDEV: 2.14 ± 0.16/0.99 ± 0.11 m/s, LFE: 2.12 ± 0.15/0.89 ± 0.06 m/s). Conclusion The freely accessible platform supports the comparison of MRE results obtained with different inversion methods, filter thresholds, or excitation frequencies, promoting reproducibility in MRE across community‐developed methods.

Cerebral tomoelastography based on multifrequency MR elastography in two and three dimensions

“…SWS and PR maps were reconstructed based on 2D phase gradients. The 2D pipeline is publicly available on https://bioqic-apps.charite.de/ (Meyer et al, 2022). For 3D data processing, slice phase offsets and interphase discontinuities between slices were removed after temporal Fourier transform according to Barnhill et al (2019).…”

“…On the other hand, 2D inversion algorithms are less prone to interslice artifacts and do not require multi-slice acquisitions, which expedites image acquisitions of thinner slabs through the tissue of interest (Tzschatzsch et al, 2016;Mura et al, 2020). To tackle the longstanding question of whether 2D or 3D MRE is preferable for intracranial applications we developed a brain processing pipeline which exploits wavenumber (k)-based multifrequency dual elasto-visco (k-MDEV) inversion in two variants, once as a new development with shear wave separation in 3D using the curl operator and once with 2D bandpass filtering (Herthum et al, 2022a;Herthum et al, 2022b) [publicly available (Meyer et al, 2022)]. k-MDEV supports multifrequency inversion as included in the tomoelastography pipeline that has been used in many multifrequency MRE applications in abdominal and pelvic organs (Dittmann et al, 2017;Shahryari et al, 2019;Reiter et al, 2020).…”

“…The entire data processing pipeline developed in this study is publicly available under https://bioqic-apps.charite.de/ (Meyer et al, 2022). We believe that providing reference values and reproducibility scores for different anatomical regions of the human brain, obtained with a processing tool that can be easily accessed by researchers worldwide, will contribute to the urgently needed standardization in MRE.…”

On the relationship between metabolic capacities and in vivo viscoelastic properties of the liver

“…MRE data were processed in MATLAB Release 2021a (The Mathworks Inc. Natick, MN, United States) using wavenumber-based inversion method (k-MDEV) ( Tzschätzsch et al, 2016 ) publicly available at https://bioqic-apps.charite.de ( Meyer et al, 2022b ). A Butterworth low-pass filter of order 3 with a threshold of 250 m −1 was used to suppress noise prior to image unwrapping ( Herthum et al, 2022 ) while a spatial bandpass Butterworth filter of order 3 with thresholds of 15 m −1 and 300 m −1 was used for directional filtering ( Herthum et al, 2022 ).…”

Comparative Analysis of a Locally Resampling MR Elastography Reconstruction Algorithm in Liver Fibrosis

“…The variety in the acquisition conditions and in the type of tissue or organ under study, 3 and the lack of appropriate reference measurements, are all factors that have somewhat obscured the proper comparison of the relative merits of each reconstruction. In the brain or in the kidney, different reconstructions have been compared, and it was found that mean stiffness values could differ significantly between the tested reconstructions 7,8 . In the liver, reports have compared the relative performances obtained with different reconstruction algorithms, but in several cases, the reconstruction algorithms were not compared on identical source data 9–11 .…”