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Yiannakas, M. C.

Publications and source records attributed to Yiannakas, M. C..

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Comparing the Accuracy and Precision of Multi-echo Combination Methods for Quantitative Susceptibility Mapping Using Laplacian-Based Methods at 3 T

PurposeTo compare different multi-echo combination methods for MRI quantitative susceptibility mapping (QSM). Given the current lack of consensus, we aimed to elucidate how to optimally combine multi-echo gradient-recalled echo (GRE) signal phase information, either before or after applying Laplacian-base methods (LBMs) for phase unwrapping or background field removal. MethodsMulti-echo GRE data were simulated in a numerical head phantom, and multiecho GRE images were acquired at 3 T in ten healthy volunteers. To enable image-based estimation of GRE signal noise, five volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: one applied nonlinear phase fitting over echo times (TEs) before LBMs; two applied LBMs to the TE-dependent phase and then combined multiple TEs via either TE-weighted or signal-to-noise ratio (SNR)-weighted averaging; two 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). ResultsNonlinearly fitting the multi-echo phase over TEs before applying LBMs provided the highest regional accuracy of{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. ConclusionFor multi-echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.

neuroscience