ORIGINAL RESEARCH article

Front. Neurosci.

Sec. Translational Neuroscience

Volume 19 - 2025 | doi: 10.3389/fnins.2025.1534924

Verifying the concordance between motion corrected and conventional MPRAGE for pediatric morphometric analysis

Provisionally accepted
Barat Gal-ErBarat Gal-Er1Yannick BrackenierYannick Brackenier2Alexandra F BonthroneAlexandra F Bonthrone1Chiara CasellaChiara Casella3Anthony PriceAnthony Price2Sophie ArulkumaranSophie Arulkumaran1Andrew T.M ChewAndrew T.M Chew1Chiara NosartiChiara Nosarti4Michela CleriMichela Cleri5Pierluigi Di CioPierluigi Di Cio5Alexia EgloffAlexia Egloff1Mary Ann RutherfordMary Ann Rutherford1Jonathan O'MuircheartaighJonathan O'Muircheartaigh1Raphael Tomi-TricotRaphael Tomi-Tricot6,7Shaihan MalikShaihan Malik2Lucilio Cordero-GrandeLucilio Cordero-Grande2,8Joseph HajnalJoseph Hajnal2Serena CounsellSerena Counsell1*
  • 1Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
  • 2Research Department of Imaging Physics & Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
  • 3Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences; Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience,, King's College London, London, United Kingdom
  • 4Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
  • 5School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
  • 6Research Department of Imaging Physics & Engineering, School of Biomedical Engineering and Imaging Sciences,, King's College London, London, United Kingdom
  • 7MR Research Collaborations, Siemens (United Kingdom), Camberley, United Kingdom
  • 8Biomedical Image Technologies, ETSI Telecomunicación, Politécnica de Madrid and CIBER-BNN, Madrid, Spain

The final, formatted version of the article will be published soon.

Select one of your emails

You have multiple emails registered with Frontiers:

Notify me on publication

Please enter your email address:

If you already have an account, please login

You don't have a Frontiers account ? You can register here

This study aimed to validate a retrospective motion correction technique, Distributed and Incoherent Sample Orders for Reconstruction Deblurring using Encoding Redundancy (DISORDER), for pediatric brain morphometry.Two T1-weighted MPRAGE 3D datasets were acquired at 3T in thirty-seven children aged 7-8 years: one with conventional linear phase encoding and one using DISORDER. MPRAGE images were scored as motion-free or motion-corrupt.Cortical morphometry and regional brain volumes were measured with FreeSurfer, subcortical grey matter (GM) with FSL-FIRST, and hippocampi with HippUnfold.Intraclass correlation coefficient (ICC) was used to determine agreement. Mann-Whitney U was used to test the difference between measures obtained using DISORDER and (i) motion-free and (ii) motion-corrupt conventional MPRAGE data.ICC measures between conventional MPRAGE and DISORDER data were good/excellent for most subcortical GM (motion-free, 0.75-0.96; motion-corrupt, 0.62-0.98) and regional brain volumes (motion-free 0.47-0.99; motion-corrupt, 0.54-0.99), except for the amygdala and nucleus accumbens (motion-free, 0.38-0.65; motioncorrupt, 0.1-0.42). These values were less consistent for motion-corrupt conventional MPRAGE data for hippocampal volumes (motion-free 0.65-0.99; motion-corrupt, 0.11-0.91) and cortical measures (motion-free 0.76-0.98; motion-corrupt, 0.09-0.74).Mann-Whitney U showed percentage differences in measures obtained with motioncorrupt conventional MPRAGE compared to DISORDER data were significantly greater than in those obtained using motion-free conventional MPRAGE data in 22/58 structures.In the absence of motion, morphometric measures obtained using DISORDER are largely consistent with those from conventional MPRAGE data, whereas improved

Keywords: Brain, MRI, pediatric, Motion Correction, morphometry

Received: 27 Nov 2024; Accepted: 10 Apr 2025.

Copyright: © 2025 Gal-Er, Brackenier, Bonthrone, Casella, Price, Arulkumaran, Chew, Nosarti, Cleri, Di Cio, Egloff, Rutherford, O'Muircheartaigh, Tomi-Tricot, Malik, Cordero-Grande, Hajnal and Counsell. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Serena Counsell, Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Supplementary Material