Literature DB >> 33960501

Validating pore size estimates in a complex microfiber environment on a human MRI system.

Chu-Chung Huang1,2, Chih-Chin Heather Hsu3,4, Feng-Lei Zhou5,6, Slawomir Kusmia5,7,8, Mark Drakesmith7, Geoff J M Parker5,9,10, Ching-Po Lin4, Derek K Jones7.   

Abstract

PURPOSE: Recent advances in diffusion-weighted MRI provide "restricted diffusion signal fraction" and restricting pore size estimates. Materials based on co-electrospun oriented hollow cylinders have been introduced to provide validation for such methods. This study extends this work, exploring accuracy and repeatability using an extended acquisition on a 300 mT/m gradient human MRI scanner, in substrates closely mimicking tissue, that is, non-circular cross-sections, intra-voxel fiber crossing, intra-voxel distributions of pore-sizes, and smaller pore-sizes overall.
METHODS: In a single-blind experiment, diffusion-weighted data were collected from a biomimetic phantom on a 3T Connectom system using multiple gradient directions/diffusion times. Repeated scans established short-term and long-term repeatability. The total scan time (54 min) matched similar protocols used in human studies. The number of distinct fiber populations was estimated using spherical deconvolution, and median pore size estimated through the combination of CHARMED and AxCaliber3D framework. Diffusion-based estimates were compared with measurements derived from scanning electron microscopy.
RESULTS: The phantom contained substrates with different orientations, fiber configurations, and pore size distributions. Irrespective of one or two populations within the voxel, the pore-size estimates (~5 μm) and orientation-estimates showed excellent agreement with the median values of pore-size derived from scanning electron microscope and phantom configuration. Measurement repeatability depended on substrate complexity, with lower values seen in samples containing crossing-fibers. Sample-level repeatability was found to be good.
CONCLUSION: While no phantom mimics tissue completely, this study takes a step closer to validating diffusion microstructure measurements for use in vivo by demonstrating the ability to quantify microgeometry in relatively complex configurations.
© 2021 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  crossing fiber; diameter; diffusion MRI; electron microscopy; microstructure; phantom

Mesh:

Year:  2021        PMID: 33960501      PMCID: PMC7613441          DOI: 10.1002/mrm.28810

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   3.737


  53 in total

Review 1.  Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review.

Authors:  Yaniv Assaf; Ofer Pasternak
Journal:  J Mol Neurosci       Date:  2008       Impact factor: 3.444

2.  Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging.

Authors:  Ben Jeurissen; Alexander Leemans; Jacques-Donald Tournier; Derek K Jones; Jan Sijbers
Journal:  Hum Brain Mapp       Date:  2012-05-19       Impact factor: 5.038

Review 3.  Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI.

Authors:  D K Jones; D C Alexander; R Bowtell; M Cercignani; F Dell'Acqua; D J McHugh; K L Miller; M Palombo; G J M Parker; U S Rudrapatna; C M W Tax
Journal:  Neuroimage       Date:  2018-05-22       Impact factor: 6.556

4.  AxCaliber: a method for measuring axon diameter distribution from diffusion MRI.

Authors:  Yaniv Assaf; Tamar Blumenfeld-Katzir; Yossi Yovel; Peter J Basser
Journal:  Magn Reson Med       Date:  2008-06       Impact factor: 4.668

5.  Determinants of conduction velocity in myelinated nerve fibers.

Authors:  S G Waxman
Journal:  Muscle Nerve       Date:  1980 Mar-Apr       Impact factor: 3.217

6.  What dominates the time dependence of diffusion transverse to axons: Intra- or extra-axonal water?

Authors:  Hong-Hsi Lee; Els Fieremans; Dmitry S Novikov
Journal:  Neuroimage       Date:  2017-12-16       Impact factor: 6.556

Review 7.  Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

Authors:  David L Raunig; Lisa M McShane; Gene Pennello; Constantine Gatsonis; Paul L Carson; James T Voyvodic; Richard L Wahl; Brenda F Kurland; Adam J Schwarz; Mithat Gönen; Gudrun Zahlmann; Marina V Kondratovich; Kevin O'Donnell; Nicholas Petrick; Patricia E Cole; Brian Garra; Daniel C Sullivan
Journal:  Stat Methods Med Res       Date:  2014-06-11       Impact factor: 3.021

8.  Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300 mT/m maximum gradient strength.

Authors:  Qiuyun Fan; Aapo Nummenmaa; Barbara Wichtmann; Thomas Witzel; Choukri Mekkaoui; Walter Schneider; Lawrence L Wald; Susie Y Huang
Journal:  Neuroimage       Date:  2018-01-12       Impact factor: 6.556

9.  Coaxially electrospun axon-mimicking fibers for diffusion magnetic resonance imaging.

Authors:  Feng-Lei Zhou; Penny L Hubbard; Stephen J Eichhorn; Geoffrey J M Parker
Journal:  ACS Appl Mater Interfaces       Date:  2012-11-14       Impact factor: 9.229

10.  Improving Estimation of Fiber Orientations in Diffusion MRI Using Inter-Subject Information Sharing.

Authors:  Geng Chen; Pei Zhang; Ke Li; Chong-Yaw Wee; Yafeng Wu; Dinggang Shen; Pew-Thian Yap
Journal:  Sci Rep       Date:  2016-11-28       Impact factor: 4.379

View more
  2 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

2.  The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure.

Authors:  Esin Karahan; Luke Tait; Ruoguang Si; Ayşegül Özkan; Maciek J Szul; Kim S Graham; Andrew D Lawrence; Jiaxiang Zhang
Journal:  Commun Biol       Date:  2022-09-23
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.