Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity

TY - JOUR

T1 - Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity

AU - Mohammadi, Siawoosh

AU - Streubel, Tobias

AU - Klock, Leonie

AU - Edwards, Luke J

AU - Lutti, Antoine

AU - Pine, Kerrin J

AU - Weber, Sandra

AU - Scheibe, Patrick

AU - Ziegler, Gabriel

AU - Gallinat, Jürgen

AU - Kühn, Simone

AU - Callaghan, Martina F

AU - Weiskopf, Nikolaus

AU - Tabelow, Karsten

N1 - Copyright © 2022. Published by Elsevier Inc.

PY - 2022/11/15

Y1 - 2022/11/15

N2 - Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1, and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the method's sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MTsat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

AB - Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1, and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the method's sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MTsat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

KW - Artifacts

KW - Brain/diagnostic imaging

KW - Humans

KW - Magnetic Resonance Imaging/methods

KW - Myelin Sheath

KW - Neuroimaging/methods

U2 - 10.1016/j.neuroimage.2022.119529

DO - 10.1016/j.neuroimage.2022.119529

M3 - SCORING: Journal article

C2 - 35926761

VL - 262

JO - NEUROIMAGE

JF - NEUROIMAGE

SN - 1053-8119

M1 - 119529

ER -