Literature DB >> 36040334

Primary Multiparametric Quantitative Brain MRI: State-of-the-Art Relaxometric and Proton Density Mapping Techniques.

Hernán Jara1, Osamu Sakai1, Ezequiel Farrher1, Ana-Maria Oros-Peusquens1, N Jon Shah1, David C Alsop1, Kathryn E Keenan1.   

Abstract

This review on brain multiparametric quantitative MRI (MP-qMRI) focuses on the primary subset of quantitative MRI (qMRI) parameters that represent the mobile ("free") and bound ("motion-restricted") proton pools. Such primary parameters are the proton densities, relaxation times, and magnetization transfer parameters. Diffusion qMRI is also included because of its wide implementation in complete clinical MP-qMRI application. MP-qMRI advances were reviewed over the past 2 decades, with substantial progress observed toward accelerating image acquisition and increasing mapping accuracy. Areas that need further investigation and refinement are identified as follows: (a) the biologic underpinnings of qMRI parameter values and their changes with age and/or disease and (b) the theoretical limitations implicitly built into most qMRI mapping algorithms that do not distinguish between the different spatial scales of voxels versus spin packets, the central physical object of the Bloch theory. With rapidly improving image processing techniques and continuous advances in computer hardware, MP-qMRI has the potential for implementation in a wide range of clinical applications. Currently, three emerging MP-qMRI applications are synthetic MRI, macrostructural qMRI, and microstructural tissue modeling. © RSNA, 2022.

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Year:  2022        PMID: 36040334      PMCID: PMC9524578          DOI: 10.1148/radiol.211519

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   29.146


  94 in total

1.  Rapid magnetic resonance quantification on the brain: Optimization for clinical usage.

Authors:  J B M Warntjes; O Dahlqvist Leinhard; J West; P Lundberg
Journal:  Magn Reson Med       Date:  2008-08       Impact factor: 4.668

Review 2.  Validation strategies for the interpretation of microstructure imaging using diffusion MRI.

Authors:  Tim B Dyrby; Giorgio M Innocenti; Martin Bech; Henrik Lundell
Journal:  Neuroimage       Date:  2018-06-18       Impact factor: 6.556

Review 3.  MRI-based myelin water imaging: A technical review.

Authors:  Eva Alonso-Ortiz; Ives R Levesque; G Bruce Pike
Journal:  Magn Reson Med       Date:  2014-03-06       Impact factor: 4.668

4.  Analysis of proton-density bias corrections based on T1 measurement for robust quantification of water content in the brain at 3 Tesla.

Authors:  Zaheer Abbas; Vincent Gras; Klaus Möllenhoff; Fabian Keil; Ana-Maria Oros-Peusquens; Nadim J Shah
Journal:  Magn Reson Med       Date:  2014-01-16       Impact factor: 4.668

5.  Multiple field strength in vivo T1 and T2 for cerebrospinal fluid protons.

Authors:  A L Hopkins; H N Yeung; C B Bratton
Journal:  Magn Reson Med       Date:  1986-04       Impact factor: 4.668

6.  Automated MR image synthesis: feasibility studies.

Authors:  S J Riederer; S A Suddarth; S A Bobman; J N Lee; H Z Wang; J R MacFall
Journal:  Radiology       Date:  1984-10       Impact factor: 11.105

7.  Imaging microstructure in the living human brain: A viewpoint.

Authors:  Tomáš Paus
Journal:  Neuroimage       Date:  2017-10-09       Impact factor: 6.556

8.  Flexible proton density (PD) mapping using multi-contrast variable flip angle (VFA) data.

Authors:  Sara Lorio; Tim M Tierney; Amy McDowell; Owen J Arthurs; Antoine Lutti; Nikolaus Weiskopf; David W Carmichael
Journal:  Neuroimage       Date:  2018-11-19       Impact factor: 6.556

Review 9.  Magnetic Resonance of Myelin Water: An in vivo Marker for Myelin.

Authors:  Alex L MacKay; Cornelia Laule
Journal:  Brain Plast       Date:  2016-12-21

10.  On the accuracy and precision of PLANET for multiparametric MRI using phase-cycled bSSFP imaging.

Authors:  Yulia Shcherbakova; Cornelis A T van den Berg; Chrit T W Moonen; Lambertus W Bartels
Journal:  Magn Reson Med       Date:  2018-10-10       Impact factor: 4.668

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