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

Barat Gal-Er; Yannick Brackenier; Alexandra F Bonthrone; Chiara Casella; Anthony Price; Sophie Arulkumaran; Andrew T M Chew; Chiara Nosarti; Michela Cleri; Pierluigi Di Cio; Alexia Egloff; Mary A Rutherford; Jonathan O'Muircheartaigh; Raphael Tomi-Tricot; Shaihan Malik; Lucilio Cordero-Grande; Joseph V Hajnal; Serena J Counsell

doi:10.3389/fnins.2025.1534924

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

Front Neurosci. 2025 May 9:19:1534924. doi: 10.3389/fnins.2025.1534924. eCollection 2025.

Authors

Barat Gal-Er¹, Yannick Brackenier^{1

2}, Alexandra F Bonthrone¹, Chiara Casella^{1

3}, Anthony Price^{1

4}, Sophie Arulkumaran¹, Andrew T M Chew¹, Chiara Nosarti¹, Michela Cleri², Pierluigi Di Cio², Alexia Egloff¹, Mary A Rutherford¹, Jonathan O'Muircheartaigh^{1

3}, Raphael Tomi-Tricot^{1

2

5}, Shaihan Malik^{1

2}, Lucilio Cordero-Grande^{1

2

6}, Joseph V Hajnal^{1

2}, Serena J Counsell¹

Affiliations

¹ Centre for the Developing Brain, Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
² Research Department of Imaging Physics and Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
³ Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
⁴ Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom.
⁵ MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom.
⁶ Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BNN, ISCIII, Madrid, Spain.

Abstract

Purpose: 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.

Methods: Two T1-weighted MPRAGE 3D datasets were acquired at 3 T 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.

Results: 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; motion-corrupt, 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 motion-corrupt conventional MPRAGE compared to DISORDER data were significantly greater than in those obtained using motion-free conventional MPRAGE data in 22/58 structures.

Conclusion: In the absence of motion, morphometric measures obtained using DISORDER are largely consistent with those from conventional MPRAGE data, whereas improved reliability is obtained by DISORDER for motion-degraded scans. This study validates the use of DISORDER for brain morphometric studies in children.

Keywords: MRI; brain; morphometry; motion correction; pediatric.