Assessing optimisation of 3T MRI protocol across multi-site, multi-vendor settings for studying mild Traumatic Brain Injury: mTBI Predict Consortium study

Pradeepa Ruwan Wanni Arachchige; Yidian Gao; Iman Idrees; Jessikah Fildes; Aliza Finch; Waheeda Hawa; Martin Craig; Matthew J. Brookes; Lisa J. Hill; Samuel J.E. Lucas; James L. Mitchell; Alexandra J. Sinclair; Jan Novak; Andrew P. Bagshaw; Martin Wilson; Davinia Fernandez-Espejo; Karen J. Mullinger; UK mTBI Predict Consortium

doi:10.52294/001c.157692

Assessing optimisation of 3T MRI protocol across multi-site, multi-vendor settings for studying mild Traumatic Brain Injury: mTBI Predict Consortium study

Pradeepa Ruwan Wanni Arachchige^*
, Yidian Gao
, Iman Idrees
, Jessikah Fildes
, Aliza Finch
, Waheeda Hawa
, Martin Craig
, Matthew J. Brookes
, Lisa J. Hill
, Samuel J.E. Lucas
, James L. Mitchell
, Alexandra J. Sinclair
, Jan Novak
, Andrew P. Bagshaw
, Martin Wilson
, Davinia Fernandez-Espejo
, Karen J. Mullinger^*
, UK mTBI Predict Consortium

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Downloads (Pure)

Abstract

Large multi-site, multi-vendor MRI studies offer opportunities to advance clinical practice and neuroscience research by increasing sample sizes, especially in clinical populations. However, variability between scanners or sites can affect the reproducibility of quantitative MRI metrics, which is vital for using MRI beyond visual inspection of structural images. This study aimed to assess the reproducibility of MRI metrics for the mild traumatic brain injury-Predict (mTBI-Predict) consortium, spanning Philips and Siemens scanners across three sites.

We conducted a travelling head study (n=1), acquiring repeated measurements from a healthy participant across three sites. Evaluated metrics included cortical thickness and subcortical volume from T1-weighted images, fractional anisotropy (FA) and mean diffusivity (MD) from diffusion-weighted imaging, temporal signal-to-noise ratio (tSNR) from echo planar imaging, and cerebral blood flow (CBF) from arterial spin labelling. Image quality metrics (point spread function and motion) were also assessed across all DWI, fMRI, and pCASL data. Standardised pipelines were used for preprocessing and analysis. Within-subject coefficients of variation (wCV%) and linear regressions assessed repeatability and consistency.

Structural measures, including cortical thickness, subcortical volume, FA, and MD, demonstrated excellent reproducibility (wCV ≤5%, R² ≥0.85) within and between sites. Minimal differences in participant motion were observed across sessions. However, as expected, tSNR and CBF showed greater variability than structural measures, due to their functional nature. Despite this, wCV% remained below 10% for all metrics, a threshold indicating very good agreement for biological measures. These findings align with previous work, demonstrating the feasibility of obtaining comparable MRI measurements across sites for studying brain structure and function. This study lays the groundwork for further evaluation of clinically relevant MRI biomarkers for mTBI.

Original language	English
Number of pages	22
Journal	Aperture Neuro
Volume	6
DOIs	https://doi.org/10.52294/001c.157692
Publication status	Published - 27 Mar 2026

Keywords

Neuroimaging
T1 anatomical
Diffusion Weighted Imaging
Echo Planar Imaging,
Arterial Spin Labelling

Access to Document

10.52294/001c.157692Licence: Creative Commons: Attribution (CC BY)

ArachchigeP2026AssessingFinal published version, 1.28 MBLicence: Creative Commons: Attribution (CC BY)

Military Traumatic Brain Injury Biomarker Study, a prospective cohort biomarker study of military and civilian participants with mTBI
Lucas, S. (Co-Investigator), Karavitaki, N. (Co-Investigator), Bagshaw, A. (Co-Investigator), Sinclair, A. (Principal Investigator), Morris, K. (Co-Investigator), Deeks, J. (Co-Investigator), Blanch, R. (Co-Investigator), Fernandez-Espejo, D. (Co-Investigator), Upthegrove, R. (Co-Investigator), Terry, J. (Co-Investigator), Jensen, O. (Co-Investigator), Belli, T. (Co-Investigator), Sitch, A. (Co-Investigator), Jenkinson, N. (Co-Investigator), Mullinger, K. (Co-Investigator), Dehghani, H. (Co-Investigator), Smith, D. (Co-Investigator), Mazaheri, A. (Co-Investigator), Berhane, S. (Co-Investigator) & Ottridge, R. (Co-Investigator)
Ministry Of Defence
17/12/21 → 31/12/24
Project: Other Government Departments

Cite this

Ruwan Wanni Arachchige, P., Gao, Y., Idrees, I., Fildes, J., Finch, A., Hawa, W., Craig, M., Brookes, M. J., Hill, L. J., Lucas, S. J. E., Mitchell, J. L., Sinclair, A. J., Novak, J., Bagshaw, A. P., Wilson, M., Fernandez-Espejo, D., Mullinger, K. J., & UK mTBI Predict Consortium (2026). Assessing optimisation of 3T MRI protocol across multi-site, multi-vendor settings for studying mild Traumatic Brain Injury: mTBI Predict Consortium study. Aperture Neuro, 6. https://doi.org/10.52294/001c.157692

@article{67bd50d1506b40fdbf1309f7126e3553,

title = "Assessing optimisation of 3T MRI protocol across multi-site, multi-vendor settings for studying mild Traumatic Brain Injury: mTBI Predict Consortium study",

abstract = "Large multi-site, multi-vendor MRI studies offer opportunities to advance clinical practice and neuroscience research by increasing sample sizes, especially in clinical populations. However, variability between scanners or sites can affect the reproducibility of quantitative MRI metrics, which is vital for using MRI beyond visual inspection of structural images. This study aimed to assess the reproducibility of MRI metrics for the mild traumatic brain injury-Predict (mTBI-Predict) consortium, spanning Philips and Siemens scanners across three sites. We conducted a travelling head study (n=1), acquiring repeated measurements from a healthy participant across three sites. Evaluated metrics included cortical thickness and subcortical volume from T1-weighted images, fractional anisotropy (FA) and mean diffusivity (MD) from diffusion-weighted imaging, temporal signal-to-noise ratio (tSNR) from echo planar imaging, and cerebral blood flow (CBF) from arterial spin labelling. Image quality metrics (point spread function and motion) were also assessed across all DWI, fMRI, and pCASL data. Standardised pipelines were used for preprocessing and analysis. Within-subject coefficients of variation (wCV\%) and linear regressions assessed repeatability and consistency. Structural measures, including cortical thickness, subcortical volume, FA, and MD, demonstrated excellent reproducibility (wCV ≤5\%, R² ≥0.85) within and between sites. Minimal differences in participant motion were observed across sessions. However, as expected, tSNR and CBF showed greater variability than structural measures, due to their functional nature. Despite this, wCV\% remained below 10\% for all metrics, a threshold indicating very good agreement for biological measures. These findings align with previous work, demonstrating the feasibility of obtaining comparable MRI measurements across sites for studying brain structure and function. This study lays the groundwork for further evaluation of clinically relevant MRI biomarkers for mTBI.",

keywords = "Neuroimaging, T1 anatomical, Diffusion Weighted Imaging, Echo Planar Imaging,, Arterial Spin Labelling",

author = "\{Ruwan Wanni Arachchige\}, Pradeepa and Yidian Gao and Iman Idrees and Jessikah Fildes and Aliza Finch and Waheeda Hawa and Martin Craig and Brookes, \{Matthew J.\} and Hill, \{Lisa J.\} and Lucas, \{Samuel J.E.\} and Mitchell, \{James L.\} and Sinclair, \{Alexandra J.\} and Jan Novak and Bagshaw, \{Andrew P.\} and Martin Wilson and Davinia Fernandez-Espejo and Mullinger, \{Karen J.\} and \{UK mTBI Predict Consortium\}",

year = "2026",

month = mar,

day = "27",

doi = "10.52294/001c.157692",

language = "English",

volume = "6",

journal = "Aperture Neuro",

issn = "2957-3963",

}

Ruwan Wanni Arachchige, P, Gao, Y, Idrees, I, Fildes, J, Finch, A, Hawa, W, Craig, M, Brookes, MJ, Hill, LJ , Lucas, SJE, Mitchell, JL, Sinclair, AJ, Novak, J, Bagshaw, AP , Wilson, M , Fernandez-Espejo, D , Mullinger, KJ & UK mTBI Predict Consortium 2026, 'Assessing optimisation of 3T MRI protocol across multi-site, multi-vendor settings for studying mild Traumatic Brain Injury: mTBI Predict Consortium study', Aperture Neuro, vol. 6. https://doi.org/10.52294/001c.157692

TY - JOUR

T1 - Assessing optimisation of 3T MRI protocol across multi-site, multi-vendor settings for studying mild Traumatic Brain Injury

T2 - mTBI Predict Consortium study

AU - Ruwan Wanni Arachchige, Pradeepa

AU - Gao, Yidian

AU - Idrees, Iman

AU - Fildes, Jessikah

AU - Finch, Aliza

AU - Hawa, Waheeda

AU - Craig, Martin

AU - Brookes, Matthew J.

AU - Hill, Lisa J.

AU - Lucas, Samuel J.E.

AU - Mitchell, James L.

AU - Sinclair, Alexandra J.

AU - Novak, Jan

AU - Bagshaw, Andrew P.

AU - Wilson, Martin

AU - Fernandez-Espejo, Davinia

AU - Mullinger, Karen J.

AU - UK mTBI Predict Consortium

PY - 2026/3/27

Y1 - 2026/3/27

N2 - Large multi-site, multi-vendor MRI studies offer opportunities to advance clinical practice and neuroscience research by increasing sample sizes, especially in clinical populations. However, variability between scanners or sites can affect the reproducibility of quantitative MRI metrics, which is vital for using MRI beyond visual inspection of structural images. This study aimed to assess the reproducibility of MRI metrics for the mild traumatic brain injury-Predict (mTBI-Predict) consortium, spanning Philips and Siemens scanners across three sites. We conducted a travelling head study (n=1), acquiring repeated measurements from a healthy participant across three sites. Evaluated metrics included cortical thickness and subcortical volume from T1-weighted images, fractional anisotropy (FA) and mean diffusivity (MD) from diffusion-weighted imaging, temporal signal-to-noise ratio (tSNR) from echo planar imaging, and cerebral blood flow (CBF) from arterial spin labelling. Image quality metrics (point spread function and motion) were also assessed across all DWI, fMRI, and pCASL data. Standardised pipelines were used for preprocessing and analysis. Within-subject coefficients of variation (wCV%) and linear regressions assessed repeatability and consistency. Structural measures, including cortical thickness, subcortical volume, FA, and MD, demonstrated excellent reproducibility (wCV ≤5%, R² ≥0.85) within and between sites. Minimal differences in participant motion were observed across sessions. However, as expected, tSNR and CBF showed greater variability than structural measures, due to their functional nature. Despite this, wCV% remained below 10% for all metrics, a threshold indicating very good agreement for biological measures. These findings align with previous work, demonstrating the feasibility of obtaining comparable MRI measurements across sites for studying brain structure and function. This study lays the groundwork for further evaluation of clinically relevant MRI biomarkers for mTBI.

AB - Large multi-site, multi-vendor MRI studies offer opportunities to advance clinical practice and neuroscience research by increasing sample sizes, especially in clinical populations. However, variability between scanners or sites can affect the reproducibility of quantitative MRI metrics, which is vital for using MRI beyond visual inspection of structural images. This study aimed to assess the reproducibility of MRI metrics for the mild traumatic brain injury-Predict (mTBI-Predict) consortium, spanning Philips and Siemens scanners across three sites. We conducted a travelling head study (n=1), acquiring repeated measurements from a healthy participant across three sites. Evaluated metrics included cortical thickness and subcortical volume from T1-weighted images, fractional anisotropy (FA) and mean diffusivity (MD) from diffusion-weighted imaging, temporal signal-to-noise ratio (tSNR) from echo planar imaging, and cerebral blood flow (CBF) from arterial spin labelling. Image quality metrics (point spread function and motion) were also assessed across all DWI, fMRI, and pCASL data. Standardised pipelines were used for preprocessing and analysis. Within-subject coefficients of variation (wCV%) and linear regressions assessed repeatability and consistency. Structural measures, including cortical thickness, subcortical volume, FA, and MD, demonstrated excellent reproducibility (wCV ≤5%, R² ≥0.85) within and between sites. Minimal differences in participant motion were observed across sessions. However, as expected, tSNR and CBF showed greater variability than structural measures, due to their functional nature. Despite this, wCV% remained below 10% for all metrics, a threshold indicating very good agreement for biological measures. These findings align with previous work, demonstrating the feasibility of obtaining comparable MRI measurements across sites for studying brain structure and function. This study lays the groundwork for further evaluation of clinically relevant MRI biomarkers for mTBI.

KW - Neuroimaging

KW - T1 anatomical

KW - Diffusion Weighted Imaging

KW - Echo Planar Imaging,

KW - Arterial Spin Labelling

U2 - 10.52294/001c.157692

DO - 10.52294/001c.157692

M3 - Article

SN - 2957-3963

VL - 6

JO - Aperture Neuro

JF - Aperture Neuro

ER -

Assessing optimisation of 3T MRI protocol across multi-site, multi-vendor settings for studying mild Traumatic Brain Injury: mTBI Predict Consortium study

Abstract

Keywords

Access to Document

Fingerprint

Projects

Military Traumatic Brain Injury Biomarker Study, a prospective cohort biomarker study of military and civilian participants with mTBI

Cite this