2022
DOI: 10.1002/nbm.4707
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Robustness and stability of volume‐based tractography in a multicenter setting

Abstract: Muscle diffusion tensor imaging (mDTI)-based tractography is a promising tool with which to detect subclinical changes in muscle injuries and to evaluate pathophysiology in neuromuscular diseases. Classic region of interest (ROI)-based tractography is very time-consuming and requires an examiner with extensive experience. (Semi)automatic approaches such as volume-based tractography (VBT) can diminish this problem but its robustness and stability are unknown. The aim of

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Cited by 3 publications
(1 citation statement)
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“…Results from advanced qMRI techniques like quantitative T2 measures, diffusion tensor imaging (DTI), and Dixon fat fraction (FF) imaging provide additional information about underlying pathophysiology [16]. Whereas quantitative T2 measures have been shown to reflect the degree of myoedema and inflammation, DTI allows conclusions about muscular micro-and macrostructure [14,17,18]. Most importantly, findings based on both techniques were related to histopathologic features in neuromuscular disorders and were sensitive in detecting subtle changes after physical exertion and in otherwise healthy-appearing, non-fat-infiltrated muscles in neuromuscular disorders [16,19].…”
Section: Introductionmentioning
confidence: 99%
“…Results from advanced qMRI techniques like quantitative T2 measures, diffusion tensor imaging (DTI), and Dixon fat fraction (FF) imaging provide additional information about underlying pathophysiology [16]. Whereas quantitative T2 measures have been shown to reflect the degree of myoedema and inflammation, DTI allows conclusions about muscular micro-and macrostructure [14,17,18]. Most importantly, findings based on both techniques were related to histopathologic features in neuromuscular disorders and were sensitive in detecting subtle changes after physical exertion and in otherwise healthy-appearing, non-fat-infiltrated muscles in neuromuscular disorders [16,19].…”
Section: Introductionmentioning
confidence: 99%