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Low-field vs 3T high-field MRI vertex-level measures of neuroanatomy in a paediatric LMIC cohort

Presented During:

Novel Imaging Acquisition Methods

Friday, June 27, 2025: 11:30 AM - 12:45 PM

Brisbane Convention & Exhibition Centre

Room: M4 (Mezzanine Level)

Poster No:

1934

Submission Type:

Abstract Submission

Authors:

Charlotte Pretzsch¹, Frantisek Váša², Michael Brammer¹, Lucy Brink³, Cindy Pham¹, Hein Odendaal⁴, Dan Stein⁵, Elizabeth Sowell⁶, Priscilla Springer⁷, Eva Loth¹, Declan Murphy¹, Christine Ecker⁸

Institutions:

¹Dept of Forensic and Neurodevelopmental Sciences, King's College London, London, United Kingdom, ²Dept of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom, ³Dept of Obstetrics and Gynaecology, Stellenbosch University, Stellenbosch, South Africa, ⁴Dept of Obstetrics and Gynaecology, Stellenbosch University, South Africa, Stellenbosch, South Africa, ⁵Dept of Psychiatry and Mental Health, University of Capetown, Capetown, South Africa, ⁶Dept of Paediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA, ⁷Dept of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, South Africa, ⁸Dept of Child and Adolescent Psychiatry, Psychosomatics, Psychotherapy, Goethe-University Frankfurt, Frankfurt, Germany

First Author:

Charlotte Pretzsch
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom

Co-Author(s):

Frantisek Váša
Dept of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London
London, United Kingdom

Michael Brammer
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom

Lucy Brink
Dept of Obstetrics and Gynaecology, Stellenbosch University
Stellenbosch, South Africa

Cindy Pham
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom

Hein Odendaal
Dept of Obstetrics and Gynaecology, Stellenbosch University, South Africa
Stellenbosch, South Africa

Dan Stein
Dept of Psychiatry and Mental Health, University of Capetown
Capetown, South Africa

Elizabeth Sowell
Dept of Paediatrics, Keck School of Medicine, University of Southern California
Los Angeles, CA, USA

Priscilla Springer
Dept of Paediatrics and Child Health, Stellenbosch University
Stellenbosch, South Africa

Eva Loth
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom

Declan Murphy
Dept of Forensic and Neurodevelopmental Sciences, King's College London
London, United Kingdom

Christine Ecker
Dept of Child and Adolescent Psychiatry, Psychosomatics, Psychotherapy, Goethe-University Frankfurt
Frankfurt, Germany

Introduction:

Conventional, high-field (3 Tesla) magnetic resonance imaging can provide crucial insights into brain structure and function but remains limited to high-resource settings. Novel, low-field (<0.1T) imaging techniques offer a more cost-effective, accessible alternative (1). However, to harness their potential, including in low- and middle-income countries (LMIC), we first need to establish the validity of low-field data at spatial resolutions relevant to research and clinic (including at the vertex-level); and this was the aim of the present study.

Methods:

We acquired paired high-field and low-field neuroimaging data from 12 children aged 10–12 years in a LMIC (interscan interval <6 months). High-field images, processed using standard neuroimaging toolkits, served as reference. Low-field images (either single-orientation scans or multiple orthogonal orientations combined into one scan), were analysed with and without prior image enhancement, and processed using a range of established and novel processing pipelines. We assessed correspondence between high-field and low-field vertex-level measures of cortical volume, surface area, and cortical thickness using correlation-based techniques (Pearson correlation, Intraclass Correlation Coefficient, and Lin's Concordance Correlation Coefficient); and compared processing strategies using Pearson correlation, mixed-effects models, and Steiger's Z-tests.

·Figure 1: Study schematic

Results:

Across analytic strategies, high-field and low-field images showed weak to moderate global correspondence (cortical volume and surface area: Pearson's r≤0.6, cortical thickness r≤0.3), and weak to very strong local correspondence (r≤0.99). Greatest correspondence was achieved with multi-orientation images using either a pipeline adjusted for low-resolution images (recon-all-clinical) or a combination of image enhancement (SynthSR) and a standard imaging toolbox (FastSurfer); but agreement varied across brain regions based on input data, analytic strategy, and neuroanatomical feature. To increase the impact of our research, we have developed an application that enables the user to interactively view and access our results – e.g., to download spatial masks of brain regions with a particularly high low-field/high-field correspondence for a specified processing pipeline and neuroanatomical feature.

Conclusions:

Our results extend prior research by demonstrating that low-field imaging can provide reliable, high-resolution estimates of cortical volume and surface area, but not cortical thickness. The choice of analytic approach should be guided by multiple considerations, including e.g., the brain region of interest and available data and computational resources; and the application we have developed may support this selection. Once validated in larger and more heterogeneous cohorts, this research may pave a way towards deploying low-field imaging as a powerful toolkit to aid research and evidence-based clinical work in high- and low-resource settings, including in LMICs.

Modeling and Analysis Methods:

Methods Development ²

Motion Correction and Preprocessing

Neuroanatomy, Physiology, Metabolism and Neurotransmission:

Cortical Anatomy and Brain Mapping

Neuroinformatics and Data Sharing:

Workflows

Novel Imaging Acquisition Methods:

Imaging Methods Other ¹

Keywords:

Acquisition

Cortex

Data analysis

MRI

STRUCTURAL MRI

Other - Low-field MRI

^1|2Indicates the priority used for review

Abstract Information

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Please indicate below if your study was a "resting state" or "task-activation” study.

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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Healthy subjects

Was this research conducted in the United States?

Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Structural MRI

Other, Please specify - Low-field MRI

For human MRI, what field strength scanner do you use?

3.0T

If Other, please list - low-field (64mT)

Which processing packages did you use for your study?

Free Surfer

Other, Please list - FastSurfer, SynthSR, SynthSeg

Provide references using APA citation style.

Vasa, F. (under review). Ultra-low-field brain MRI morphometry: test-retest reliability and correspondence to high-field MRI.

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