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Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling

In vivo mapping of the neurite density with diffusion MRI (dMRI) is a high but challenging aim. First, it is unknown whether all neurites exhibit completely anisotropic (“stick‐like”) diffusion. Second, the “density” of tissue components may be confounded by non‐diffusion properties such as T2 relax...

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Autores principales: Lampinen, Björn, Szczepankiewicz, Filip, Novén, Mikael, van Westen, Danielle, Hansson, Oskar, Englund, Elisabet, Mårtensson, Johan, Westin, Carl‐Fredrik, Nilsson, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6503974/
https://www.ncbi.nlm.nih.gov/pubmed/30802367
http://dx.doi.org/10.1002/hbm.24542
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author Lampinen, Björn
Szczepankiewicz, Filip
Novén, Mikael
van Westen, Danielle
Hansson, Oskar
Englund, Elisabet
Mårtensson, Johan
Westin, Carl‐Fredrik
Nilsson, Markus
author_facet Lampinen, Björn
Szczepankiewicz, Filip
Novén, Mikael
van Westen, Danielle
Hansson, Oskar
Englund, Elisabet
Mårtensson, Johan
Westin, Carl‐Fredrik
Nilsson, Markus
author_sort Lampinen, Björn
collection PubMed
description In vivo mapping of the neurite density with diffusion MRI (dMRI) is a high but challenging aim. First, it is unknown whether all neurites exhibit completely anisotropic (“stick‐like”) diffusion. Second, the “density” of tissue components may be confounded by non‐diffusion properties such as T2 relaxation. Third, the domain of validity for the estimated parameters to serve as indices of neurite density is incompletely explored. We investigated these challenges by acquiring data with “b‐tensor encoding” and multiple echo times in brain regions with low orientation coherence and in white matter lesions. Results showed that microscopic anisotropy from b‐tensor data is associated with myelinated axons but not with dendrites. Furthermore, b‐tensor data together with data acquired for multiple echo times showed that unbiased density estimates in white matter lesions require data‐driven estimates of compartment‐specific T2 values. Finally, the “stick” fractions of different biophysical models could generally not serve as neurite density indices across the healthy brain and white matter lesions, where outcomes of comparisons depended on the choice of constraints. In particular, constraining compartment‐specific T2 values was ambiguous in the healthy brain and had a large impact on estimated values. In summary, estimating neurite density generally requires accounting for different diffusion and/or T2 properties between axons and dendrites. Constrained “index” parameters could be valid within limited domains that should be delineated by future studies.
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spelling pubmed-65039742019-05-23 Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling Lampinen, Björn Szczepankiewicz, Filip Novén, Mikael van Westen, Danielle Hansson, Oskar Englund, Elisabet Mårtensson, Johan Westin, Carl‐Fredrik Nilsson, Markus Hum Brain Mapp Research Articles In vivo mapping of the neurite density with diffusion MRI (dMRI) is a high but challenging aim. First, it is unknown whether all neurites exhibit completely anisotropic (“stick‐like”) diffusion. Second, the “density” of tissue components may be confounded by non‐diffusion properties such as T2 relaxation. Third, the domain of validity for the estimated parameters to serve as indices of neurite density is incompletely explored. We investigated these challenges by acquiring data with “b‐tensor encoding” and multiple echo times in brain regions with low orientation coherence and in white matter lesions. Results showed that microscopic anisotropy from b‐tensor data is associated with myelinated axons but not with dendrites. Furthermore, b‐tensor data together with data acquired for multiple echo times showed that unbiased density estimates in white matter lesions require data‐driven estimates of compartment‐specific T2 values. Finally, the “stick” fractions of different biophysical models could generally not serve as neurite density indices across the healthy brain and white matter lesions, where outcomes of comparisons depended on the choice of constraints. In particular, constraining compartment‐specific T2 values was ambiguous in the healthy brain and had a large impact on estimated values. In summary, estimating neurite density generally requires accounting for different diffusion and/or T2 properties between axons and dendrites. Constrained “index” parameters could be valid within limited domains that should be delineated by future studies. John Wiley & Sons, Inc. 2019-02-25 /pmc/articles/PMC6503974/ /pubmed/30802367 http://dx.doi.org/10.1002/hbm.24542 Text en © 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Lampinen, Björn
Szczepankiewicz, Filip
Novén, Mikael
van Westen, Danielle
Hansson, Oskar
Englund, Elisabet
Mårtensson, Johan
Westin, Carl‐Fredrik
Nilsson, Markus
Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling
title Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling
title_full Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling
title_fullStr Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling
title_full_unstemmed Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling
title_short Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling
title_sort searching for the neurite density with diffusion mri: challenges for biophysical modeling
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6503974/
https://www.ncbi.nlm.nih.gov/pubmed/30802367
http://dx.doi.org/10.1002/hbm.24542
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