Literature DB >> 33017644

The sensitivity of diffusion MRI to microstructural properties and experimental factors.

Maryam Afzali1, Tomasz Pieciak2, Sharlene Newman3, Eleftherios Garyfallidis4, Evren Özarslan5, Hu Cheng6, Derek K Jones7.   

Abstract

Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic.
Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Anisotropy; Biophysical model; Diffusion MRI; Experimental factors; Microstructure; Signal representation

Mesh:

Year:  2020        PMID: 33017644      PMCID: PMC7762827          DOI: 10.1016/j.jneumeth.2020.108951

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  343 in total

1.  Relationships between diffusion tensor and q-space MRI.

Authors:  Peter J Basser
Journal:  Magn Reson Med       Date:  2002-02       Impact factor: 4.668

2.  Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo.

Authors:  T G Reese; O Heid; R M Weisskoff; V J Wedeen
Journal:  Magn Reson Med       Date:  2003-01       Impact factor: 4.668

3.  The importance of axonal undulation in diffusion MR measurements: a Monte Carlo simulation study.

Authors:  Markus Nilsson; Jimmy Lätt; Freddy Ståhlberg; Danielle van Westen; Håkan Hagslätt
Journal:  NMR Biomed       Date:  2011-10-21       Impact factor: 4.044

4.  Eddy-current compensated diffusion weighting with a single refocusing RF pulse.

Authors:  Jürgen Finsterbusch
Journal:  Magn Reson Med       Date:  2009-03       Impact factor: 4.668

5.  A viable isolated tissue system: a tool for detailed MR measurements and controlled perturbation in physiologically stable tissue.

Authors:  S Richardson; B Siow; A M Batchelor; M F Lythgoe; D C Alexander
Journal:  Magn Reson Med       Date:  2012-07-20       Impact factor: 4.668

6.  MAPL: Tissue microstructure estimation using Laplacian-regularized MAP-MRI and its application to HCP data.

Authors:  Rutger H J Fick; Demian Wassermann; Emmanuel Caruyer; Rachid Deriche
Journal:  Neuroimage       Date:  2016-04-01       Impact factor: 6.556

7.  Stereological estimation of the total number of myelinated callosal fibers in human subjects.

Authors:  Jesper Riise; Bente Pakkenberg
Journal:  J Anat       Date:  2011-01-19       Impact factor: 2.610

8.  "Squashing peanuts and smashing pumpkins": how noise distorts diffusion-weighted MR data.

Authors:  Derek K Jones; Peter J Basser
Journal:  Magn Reson Med       Date:  2004-11       Impact factor: 4.668

9.  Detecting diffusion-diffraction patterns in size distribution phantoms using double-pulsed field gradient NMR: Theory and experiments.

Authors:  Noam Shemesh; Evren Ozarslan; Peter J Basser; Yoram Cohen
Journal:  J Chem Phys       Date:  2010-01-21       Impact factor: 3.488

10.  Including diffusion time dependence in the extra-axonal space improves in vivo estimates of axonal diameter and density in human white matter.

Authors:  Silvia De Santis; Derek K Jones; Alard Roebroeck
Journal:  Neuroimage       Date:  2016-01-27       Impact factor: 6.556

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  6 in total

Review 1.  Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact.

Authors:  Qiuyun Fan; Cornelius Eichner; Maryam Afzali; Lars Mueller; Chantal M W Tax; Mathias Davids; Mirsad Mahmutovic; Boris Keil; Berkin Bilgic; Kawin Setsompop; Hong-Hsi Lee; Qiyuan Tian; Chiara Maffei; Gabriel Ramos-Llordén; Aapo Nummenmaa; Thomas Witzel; Anastasia Yendiki; Yi-Qiao Song; Chu-Chung Huang; Ching-Po Lin; Nikolaus Weiskopf; Alfred Anwander; Derek K Jones; Bruce R Rosen; Lawrence L Wald; Susie Y Huang
Journal:  Neuroimage       Date:  2022-02-23       Impact factor: 7.400

Review 2.  Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review.

Authors:  Fan Zhang; Alessandro Daducci; Yong He; Simona Schiavi; Caio Seguin; Robert E Smith; Chun-Hung Yeh; Tengda Zhao; Lauren J O'Donnell
Journal:  Neuroimage       Date:  2022-01-01       Impact factor: 7.400

3.  White matter microstructural and morphometric alterations in autism: implications for intellectual capabilities.

Authors:  Chun-Hung Yeh; Rung-Yu Tseng; Hsing-Chang Ni; Luca Cocchi; Jung-Chi Chang; Mei-Yun Hsu; En-Nien Tu; Yu-Yu Wu; Tai-Li Chou; Susan Shur-Fen Gau; Hsiang-Yuan Lin
Journal:  Mol Autism       Date:  2022-05-18       Impact factor: 6.476

4.  Subiculum-BNST structural connectivity in humans and macaques.

Authors:  Samuel C Berry; Andrew D Lawrence; Thomas M Lancaster; Chiara Casella; John P Aggleton; Mark Postans
Journal:  Neuroimage       Date:  2022-03-15       Impact factor: 7.400

5.  Analysis of Brain Structural Connectivity Networks and White Matter Integrity in Patients With Mild Cognitive Impairment.

Authors:  Maurizio Bergamino; Simona Schiavi; Alessandro Daducci; Ryan R Walsh; Ashley M Stokes
Journal:  Front Aging Neurosci       Date:  2022-01-31       Impact factor: 5.750

6.  White matter variability, cognition, and disorders: a systematic review.

Authors:  Stephanie J Forkel; Patrick Friedrich; Michel Thiebaut de Schotten; Henrietta Howells
Journal:  Brain Struct Funct       Date:  2021-11-03       Impact factor: 3.270

  6 in total

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