Literature DB >> 29526642

Empirical reproducibility, sensitivity, and optimization of acquisition protocol, for Neurite Orientation Dispersion and Density Imaging using AMICO.

Prasanna Parvathaneni1, Vishwesh Nath2, Justin A Blaber3, Kurt G Schilling4, Allison E Hainline5, Ed Mojahed6, Adam W Anderson4, Bennett A Landman7.   

Abstract

Neurite Orientation Dispersion and Density Imaging (NODDI) has been gaining prominence for estimating multiple diffusion compartments from MRI data acquired in a clinically feasible time. To establish a pathway for adoption of NODDI in clinical studies, it is important to understand the sensitivity and reproducibility of NODDI metrics on empirical data in the context of acquisition protocol and brain anatomy. Previous studies addressed reproducibility across the 3 T scanners and within session and between subject reproducibility at 1.5 T and 3 T. However, empirical reproducibility on the performance of NODDI metrics based on b-value and diffusion-sensitized directions has not yet been addressed. In this study, we investigate a high angular resolution dataset with 11 repeats of a study with five b-values shells (1000, 1500, 2000, 2500 and 3000 s/mm2) and 96 directions per shell on a single subject. We validated the findings with a dataset from second subject with 10 repeats and 3 b-value shells (1000, 2000, 3000 s/mm2). The NODDI model was estimated using Accelerated Microstructure Imaging via Convex Optimization (AMICO) for different b-values and gradient directions on two-shell High Angular Resolution Density Imaging (HARDI) data fixing the lower shell at b = 1000 s/mm2. NODDI model applied to all acquired imaging data was used as a baseline gold standard for comparison. Additionally, we characterize orientation dispersion index (ODI) reproducibility using single-shell data. The experimental findings confirmed the sensitivity of intracellular volume fraction (Vic) with the choice of outer shell b-value more than with the choice of gradient directions. On the other hand, ODI is more sensitive to the number of gradient directions compared to b-value selection. Single-shell results for ODI are more comparable to 2-shell data at lower b-values than higher b-values. Recommended settings by region of interest and acquisition time are reported for the researchers considering using NODDI in human studies and/or comparing results across acquisition protocols.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  AMICO; Advanced DW-MRI; Microstructure imaging; NODDI; Reproducibility

Mesh:

Year:  2018        PMID: 29526642      PMCID: PMC5970991          DOI: 10.1016/j.mri.2018.03.004

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  43 in total

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Authors:  Mark Jenkinson; Peter Bannister; Michael Brady; Stephen Smith
Journal:  Neuroimage       Date:  2002-10       Impact factor: 6.556

2.  Modeling dendrite density from magnetic resonance diffusion measurements.

Authors:  Sune N Jespersen; Christopher D Kroenke; Leif Østergaard; Joseph J H Ackerman; Dmitriy A Yablonskiy
Journal:  Neuroimage       Date:  2006-12-22       Impact factor: 6.556

3.  Optimal acquisition orders of diffusion-weighted MRI measurements.

Authors:  Philip A Cook; Mark Symms; Philip A Boulby; Daniel C Alexander
Journal:  J Magn Reson Imaging       Date:  2007-05       Impact factor: 4.813

4.  A general framework for experiment design in diffusion MRI and its application in measuring direct tissue-microstructure features.

Authors:  Daniel C Alexander
Journal:  Magn Reson Med       Date:  2008-08       Impact factor: 4.668

5.  Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Authors:  Alessandro Daducci; Erick J Canales-Rodríguez; Hui Zhang; Tim B Dyrby; Daniel C Alexander; Jean-Philippe Thiran
Journal:  Neuroimage       Date:  2014-10-22       Impact factor: 6.556

6.  N4ITK: improved N3 bias correction.

Authors:  Nicholas J Tustison; Brian B Avants; Philip A Cook; Yuanjie Zheng; Alexander Egan; Paul A Yushkevich; James C Gee
Journal:  IEEE Trans Med Imaging       Date:  2010-04-08       Impact factor: 10.048

7.  Axon diameter mapping in the presence of orientation dispersion with diffusion MRI.

Authors:  Hui Zhang; Penny L Hubbard; Geoff J M Parker; Daniel C Alexander
Journal:  Neuroimage       Date:  2011-02-19       Impact factor: 6.556

8.  Neurite density from magnetic resonance diffusion measurements at ultrahigh field: comparison with light microscopy and electron microscopy.

Authors:  Sune N Jespersen; Carsten R Bjarkam; Jens R Nyengaard; M Mallar Chakravarty; Brian Hansen; Thomas Vosegaard; Leif Østergaard; Dmitriy Yablonskiy; Niels Chr Nielsen; Peter Vestergaard-Poulsen
Journal:  Neuroimage       Date:  2009-09-02       Impact factor: 6.556

9.  Identical, but not the same: intra-site and inter-site reproducibility of fractional anisotropy measures on two 3.0T scanners.

Authors:  Christian Vollmar; Jonathan O'Muircheartaigh; Gareth J Barker; Mark R Symms; Pamela Thompson; Veena Kumari; John S Duncan; Mark P Richardson; Matthias J Koepp
Journal:  Neuroimage       Date:  2010-03-23       Impact factor: 6.556

10.  NODDI and Tensor-Based Microstructural Indices as Predictors of Functional Connectivity.

Authors:  Fani Deligianni; David W Carmichael; Gary H Zhang; Chris A Clark; Jonathan D Clayden
Journal:  PLoS One       Date:  2016-04-14       Impact factor: 3.240

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Authors:  Kurt G Schilling; Samantha By; Haley R Feiler; Bailey A Box; Kristin P O'Grady; Atlee Witt; Bennett A Landman; Seth A Smith
Journal:  Neuroimage       Date:  2019-07-19       Impact factor: 6.556

Review 2.  Beyond Diffusion Tensor MRI Methods for Improved Characterization of the Brain after Ischemic Stroke: A Review.

Authors:  E V R DiBella; A Sharma; L Richards; V Prabhakaran; J J Majersik; S K HashemizadehKolowri
Journal:  AJNR Am J Neuroradiol       Date:  2022-03-10       Impact factor: 3.825

3.  Comparing multiband and singleband EPI in NODDI at 3 T: what are the implications for reproducibility and study sample sizes?

Authors:  Samira Bouyagoub; Nicholas G Dowell; Matt Gabel; Mara Cercignani
Journal:  MAGMA       Date:  2020-12-14       Impact factor: 2.310

Review 4.  Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases.

Authors:  Koji Kamagata; Christina Andica; Ayumi Kato; Yuya Saito; Wataru Uchida; Taku Hatano; Matthew Lukies; Takashi Ogawa; Haruka Takeshige-Amano; Toshiaki Akashi; Akifumi Hagiwara; Shohei Fujita; Shigeki Aoki
Journal:  Int J Mol Sci       Date:  2021-05-14       Impact factor: 5.923

Review 5.  The sensitivity of diffusion MRI to microstructural properties and experimental factors.

Authors:  Maryam Afzali; Tomasz Pieciak; Sharlene Newman; Eleftherios Garyfallidis; Evren Özarslan; Hu Cheng; Derek K Jones
Journal:  J Neurosci Methods       Date:  2020-10-02       Impact factor: 2.390

  5 in total

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