Integrating large-scale neuroimaging research datasets: Harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets

Bordin, Valentina; Bertani, Ilaria; Mattioli, Irene; Sundaresan, Vaanathi; McCarthy, Paul; Suri, Sana; Zsoldos, Enikő; Filippini, Nicola; Mahmood, Abda; Melazzini, Luca; Laganà, Maria Marcella; Zamboni, Giovanna; Singh‐Manoux, Archana; Kivimäki, Mika; Ebmeier, Klaus P.; Baselli, Giuseppe; Jenkinson, Mark; Mackay, Clare E.; Duff, Eugene; Griffanti, Ludovica

doi:10.1016/j.neuroimage.2021.118189

Cited by 11 publications

(7 citation statements)

References 38 publications

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“…These findings are somewhat unsurprising given that the software tool for WMH measurement (BIANCA) was trained on data collected from the Siemens MRI protocol. When adequate training data are available from the GE protocol, and in older subjects where higher WMH volumes are expected, it will be important to retrain the BIANCA algorithm on both Siemens and GE data, and this may improve consistency of WMH IDPs across scanners from the different manufacturers [ 38 ].…”

Section: Resultsmentioning

confidence: 99%

Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study

Duff

Zelaya²,

Almagro³

et al. 2022

PLoS ONE

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Introduction Magnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King’s College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data. Conclusion These results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study.

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Section: Resultsmentioning

confidence: 99%

Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study

Duff

Zelaya²,

Almagro³

et al. 2022

PLoS ONE

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“…First, one major limitation is the scanner change and differences in the acquisition protocol during the follow-ups, which are known to induce measurement variability. 46 However, these differences become almost inevitable with improvements in hardware and sequence design, especially for very long follow-up studies. Second, nonparticipants were older at baseline and had a higher WMH volume compared with participants.…”

Section: Discussionmentioning

confidence: 99%

Determinants and Temporal Dynamics of Cerebral Small Vessel Disease: 14-Year Follow-Up

Cai

Jacob

Loenen

et al. 2022

Stroke

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Background: The aim of this study is to investigate the temporal dynamics of small vessel disease (SVD) and the effect of vascular risk factors and baseline SVD burden on progression of SVD with 4 neuroimaging assessments over 14 years in patients with SVD. Methods: Five hundred three patients with sporadic SVD (50–85 years) from the ongoing prospective cohort study (RUN DMC [Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort]) underwent baseline assessment in 2006 and follow-up in 2011, 2015, and 2020. Vascular risk factors and magnetic resonance imaging markers of SVD were evaluated. Linear mixed-effects model and negative binomial regression model were used to examine the determinants of temporal dynamics of SVD markers. Results: A total of 382 SVD patients (mean [SD] 64.1 [8.4]; 219 men and 163 women) who underwent at least 2 serial brain magnetic resonance imaging scans were included, with mean (SD) follow-up of 11.15 (3.32) years. We found a highly variable temporal course of SVD. Mean (SD) WMH progression rate was 0.6 (0.74) mL/y (range, 0.02–4.73 mL/y) and 13.6% of patients had incident lacunes (1.03%/y) over the 14-year follow-up. About 4% showed net WMH regression over 14 years, whereas 38 out of 361 (10.5%), 5 out of 296 (2%), and 61 out of 231 (26%) patients showed WMH regression for the intervals 2006 to 2011, 2011 to 2015, and 2015 to 2020, respectively. Of these, 29 (76%), 5 (100%), and 57 (93%) showed overall progression across the 14-year follow-up, and the net overall WMH change between first and last scan considering all participants was a net average WMH progression over the 14-year period. Older age was a strong predictor for faster WMH progression and incident lacunes. Patients with mild baseline WMH rarely progressed to severe WMH. In addition, both baseline burden of SVD lesions and vascular risk factors independently and synergistically predicted WMH progression, whereas only baseline SVD burden predicted incident lacunes over the 14-year follow-up. Conclusions: SVD shows pronounced progression over time, but mild WMH rarely progresses to clinically severe WMH. WMH regression is noteworthy during some magnetic resonance imaging intervals, although it could be overall compensated by progression over the long follow-up.

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“…This semi-automatized neuroimaging method has been successfully used to quantify macrostructural brain changesin volume or densityin longitudinal and cross-sectional studies on development and disease (Ashburner and Friston 2001). Previous results demonstrated that this type of multi-center study is methodologically feasible and reliable for the assessment of local changes in tissue integrity induced by a given pathological condition (Biswal et al 2010;Bordin et al 2021). The processing pipeline was standardized for patients and healthy controls as described by Ashburner and Friston (2001).…”

Section: Methodsmentioning

confidence: 99%

Grey matter reshaping of language-related regions depends on tumor lateralization

Manso‐Ortega

Frutos-Sagastuy

Gisbert-Muñoz

et al. 2023

Preprint

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A brain tumor in the left hemisphere can decrease language laterality as assessed with fMRI. However, it remains unclear whether or not this decreased language laterality is associated with a structural reshaping of the grey matter, particularly within the language network. Here, we examine if the disruption of language hubs exclusively affects macrostructural properties of contralateral homologues (as suggested by previous research), or whether it affects both hemispheres. This study uses voxel-based morphometry applied to high-resolution MR T1-weighted MPRAGE images from 31 adult patients left-dominant for language. Eighteen patients had brain tumors in the left hemisphere, and 13 had tumors in the right hemisphere. A cohort of 71 healthy individuals matched on age and sex was used as a baseline. We defined 10 ROIs per hemisphere known to subserve language function. Two separate repeated-measures ANOVAs were conducted with the volume per region as the dependent variable. For the patients, tumor lateralization (right versus left) served as a between-subject factor. The current study demonstrated that the presence of a brain tumor generates a global volumetric change affecting left language regions and their contralateral homologues. These changes are mediated by the lateralization of the lesion. Our findings suggest that compensatory functional mechanisms are supported by the rearrangement of the grey matter, although future longitudinal research should determine the temporal course of such changes.

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Integrating large-scale neuroimaging research datasets: Harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets

Abstract: Highlights We harmonised measures of WMHs across two studies on healthy ageing. Specific pre-processing strategies can increase comparability across studies. Modelling of biological differences is crucial to provide calibrated measures.

Cited by 11 publications

References 38 publications

Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study

Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study

Determinants and Temporal Dynamics of Cerebral Small Vessel Disease: 14-Year Follow-Up

Grey matter reshaping of language-related regions depends on tumor lateralization

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