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The effect of realistic geometries on the susceptibility-weighted MR signal in white matter.
Xu, Tianyou; Foxley, Sean; Kleinnijenhuis, Michiel; Chen, Way Cherng; Miller, Karla L.
  • Xu T; Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom.
  • Foxley S; Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom.
  • Kleinnijenhuis M; Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom.
  • Chen WC; Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom.
  • Miller KL; Singapore Bioimaging Consortium, A*STAR, Singapore.
Magn Reson Med ; 79(1): 489-500, 2018 Jan.
Article en En | MEDLINE | ID: mdl-28394030
ABSTRACT

PURPOSE:

To investigate the effect of realistic microstructural geometry on the susceptibility-weighted MR signal in white matter (WM), with application to demyelination.

METHODS:

Previous work has modeled susceptibility-weighted signals under the assumption that axons are cylindrical. In this study, we explored the implications of this assumption by considering the effect of more realistic geometries. A three-compartment WM model incorporating relevant properties based on the literature was used to predict the MR signal. Myelinated axons were modeled with several cross-sectional geometries of increasing realism nested circles, warped/elliptical circles, and measured axonal geometries from electron micrographs. Signal simulations from the different microstructural geometries were compared with measured signals from a cuprizone mouse model with varying degrees of demyelination.

RESULTS:

Simulation results suggest that axonal geometry affects the MR signal. Predictions with realistic models were significantly different compared with circular models under the same microstructural tissue properties, for simulations with and without diffusion.

CONCLUSION:

The geometry of axons affects the MR signal significantly. Literature estimates of myelin susceptibility, which are based on fitting biophysical models to the MR signal, are likely to be biased by the assumed geometry, as will any derived microstructural properties. Magn Reson Med 79489-500, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Sustancia Blanca / Vaina de Mielina Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Sustancia Blanca / Vaina de Mielina Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Año: 2018 Tipo del documento: Article