Version 1
: Received: 25 June 2021 / Approved: 6 July 2021 / Online: 6 July 2021 (11:29:06 CEST)
Version 2
: Received: 1 September 2021 / Approved: 6 September 2021 / Online: 6 September 2021 (13:20:18 CEST)
Thieleking, R.; Zhang, R.; Paerisch, M.; Wirkner, K.; Anwander, A.; Beyer, F.; Villringer, A.; Witte, A. V. Same Brain, Different Look?—The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters. Journal of Clinical Medicine, 2021, 10, 4987. https://doi.org/10.3390/jcm10214987.
Thieleking, R.; Zhang, R.; Paerisch, M.; Wirkner, K.; Anwander, A.; Beyer, F.; Villringer, A.; Witte, A. V. Same Brain, Different Look?—The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters. Journal of Clinical Medicine, 2021, 10, 4987. https://doi.org/10.3390/jcm10214987.
Thieleking, R.; Zhang, R.; Paerisch, M.; Wirkner, K.; Anwander, A.; Beyer, F.; Villringer, A.; Witte, A. V. Same Brain, Different Look?—The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters. Journal of Clinical Medicine, 2021, 10, 4987. https://doi.org/10.3390/jcm10214987.
Thieleking, R.; Zhang, R.; Paerisch, M.; Wirkner, K.; Anwander, A.; Beyer, F.; Villringer, A.; Witte, A. V. Same Brain, Different Look?—The Impact of Scanner, Sequence and Preprocessing on Diffusion Imaging Outcome Parameters. Journal of Clinical Medicine, 2021, 10, 4987. https://doi.org/10.3390/jcm10214987.
Abstract
In clinical diagnostics and longitudinal studies, the reproducibility of MRI assessments is of high importance in order to detect pathological changes, but developments in MRI hard- and software often outrun extended periods of data acquisition and analysis. This could potentially introduce artefactual changes or masking pathological alterations. However, if and how changes of MRI hardware, scanning protocols or preprocessing software affect complex neuroimaging outcomes from e.g. diffusion weighted imaging (DWI) remains largely understudied. We therefore compared DWI outcomes and artefact severity of 121 healthy participants (age range 19-54 years) who underwent two matched DWI protocols (Siemens product and Center for Magnetic Resonance Research sequence) at two sites (Siemens 3T Magnetom Verio and Skyrafit). After differing preprocessing steps, 3D-fractional anisotropy (FA) maps obtained by tensor fitting were processed with tract-based spatial statistics (TBSS). Inter-scanner and inter-sequence variability of skeletonised FA values reached up to 5% and differed largely in magnitude and direction across the brain. Preprocessing including unringing reduced the Gibbs ringing artefact, and head motion estimates were significantly lower at Skyra. We here demonstrate that DTI outcome measures strongly depend on imaging site and software, and that these biases vary between brain regions. These regionally inhomogeneous biases may exceed and considerably confound physiological effects such as ageing, highlighting the need to harmonise data acquisition and analysis. Future studies thus need to implement novel strategies to augment neuroimaging data reliability and replicability.
Diffusion Magnetic Resonance Imaging; White Matter; Fractional anisotropy; Multi-centre; Reproducibility; Imaging artefacts; Ageing
Subject
Medicine and Pharmacology, Neuroscience and Neurology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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