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Multi‐echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla
Author(s) -
Biondetti Emma,
Karsa Anita,
Grussu Francesco,
Battiston Marco,
Yiannakas Marios C.,
Thomas David L.,
Shmueli Karin
Publication year - 2022
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.29365
Subject(s) - quantitative susceptibility mapping , echo (communications protocol) , imaging phantom , gradient echo , computer science , nuclear magnetic resonance , physics , nuclear medicine , magnetic resonance imaging , medicine , radiology , computer network
Purpose To compare different multi‐echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi‐echo gradient‐recalled echo signal phase information, either before or after applying Laplacian‐base methods (LBMs) for phase unwrapping or background field removal. Methods Multi‐echo gradient‐recalled echo data were simulated in a numerical head phantom, and multi‐echo gradient‐recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image‐based estimation of gradient‐recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE‐dependent phase and then combined multiple TEs via either TE‐weighted or SNR‐weighted averaging; and 2 calculated TE‐dependent susceptibility maps via either multi‐step or single‐step QSM and then combined multiple TEs via magnitude‐weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests). Results Nonlinearly fitting the multi‐echo phase over TEs before applying LBMs provided the highest regional accuracy ofχ $$ \chi $$ and the lowest phase noise propagation compared to averaging the LBM‐processed TE‐dependent phase. This result was especially pertinent in high‐susceptibility venous regions. Conclusion For multi‐echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.