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Morphological characterization of neural tissue microstructure using the orientationally-averaged diffusion MRI signal

Diffusion-weighted magnetic resonance imaging (dMRI) is a powerful tool for thecharacterisation of neural tissue microstructural features. The role of neural projectioncurvature on the diffusion signal was recently studied for three temporal regimes of the diffusion pulse sequence in search for a description of the different decay trends in the orientationally-averaged diffusion signal reported in in vivo human studies.This work experimentally investigates the effects of neural projection curvedness in one of these regimes, namely the short diffusion time regime. Multi-shell diffusion MRI acquisitions on fixed rat spinal cord were performed using a custom number of diffusion gradient directions on a vertical bore pre-clinical MRI scanner capable of generating 3000 mT/m. Diffusion was probed in three different q-values ranges [450, 970], [600, 1400] and [1500, 1750] mm-1 using diffusion pulse durations of 1.4,2 and 2.5ms, respectively. Noise correction was performed on the diffusion data and the orientationally-averaged signal was computed for each shell using a weighted mean. The signal from selected regions in the sample was then fitted to a power law. Results show that gray matter areas exhibit a signal reduction with variable decay trends in the range of diffusion sensitivity values used here. This suggests that gray matter microstructure features are pictured by the orientationally-averaged signal in the high diffusion sensitivity regime and, as theoretically suggested, neurite curvature might play a role in characterizing the signal decay. These preliminary results may prove useful in the development of models for the interpretation of the diffusion signal and the design of acquisition strategies that aim to study the high diffusion sensitivity regime.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-158153
Date January 2019
CreatorsTampu, Iulian Emil
PublisherLinköpings universitet, Avdelningen för medicinsk teknik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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