Please use this identifier to cite or link to this item:
https://doi.org/10.1016/j.nicl.2021.102886
DC Field | Value | |
---|---|---|
dc.title | Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease | |
dc.contributor.author | Robalo, Bruno M de Brito | |
dc.contributor.author | Biessels, Geert Jan | |
dc.contributor.author | Chen, Christopher | |
dc.contributor.author | Dewenter, Anna | |
dc.contributor.author | Duering, Marco | |
dc.contributor.author | Hilal, Saima | |
dc.contributor.author | Koek, Huiberdina L | |
dc.contributor.author | Kopczak, Anna | |
dc.contributor.author | Lam, Bonnie Yin Ka | |
dc.contributor.author | Leemans, Alexander | |
dc.contributor.author | Mok, Vincent | |
dc.contributor.author | Onkenhout, Laurien P | |
dc.contributor.author | van den Brink, Hilde | |
dc.contributor.author | de Luca, Alberto | |
dc.date.accessioned | 2022-04-08T06:29:58Z | |
dc.date.available | 2022-04-08T06:29:58Z | |
dc.date.issued | 2021-11-20 | |
dc.identifier.citation | Robalo, Bruno M de Brito, Biessels, Geert Jan, Chen, Christopher, Dewenter, Anna, Duering, Marco, Hilal, Saima, Koek, Huiberdina L, Kopczak, Anna, Lam, Bonnie Yin Ka, Leemans, Alexander, Mok, Vincent, Onkenhout, Laurien P, van den Brink, Hilde, de Luca, Alberto (2021-11-20). Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease. NEUROIMAGE-CLINICAL 32. ScholarBank@NUS Repository. https://doi.org/10.1016/j.nicl.2021.102886 | |
dc.identifier.issn | 2213-1582 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/218719 | |
dc.description.abstract | Objectives: Acquisition-related differences in diffusion magnetic resonance imaging (dMRI) hamper pooling of multicentre data to achieve large sample sizes. A promising solution is to harmonize the raw diffusion signal using rotation invariant spherical harmonic (RISH) features, but this has not been tested in elderly subjects. Here we aimed to establish if RISH harmonization effectively removes acquisition-related differences in multicentre dMRI of elderly subjects with cerebral small vessel disease (SVD), while preserving sensitivity to disease effects. Methods: Five cohorts of patients with SVD (N = 397) and elderly controls (N = 175) with 3 Tesla MRI on different systems were included. First, to establish effectiveness of harmonization, the RISH method was trained with data of 13 to 15 age and sex-matched controls from each site. Fractional anisotropy (FA) and mean diffusivity (MD) were compared in matched controls between sites using tract-based spatial statistics (TBSS) and voxel-wise analysis, before and after harmonization. Second, to assess sensitivity to disease effects, we examined whether the contrast (effect sizes of FA, MD and peak width of skeletonized MD - PSMD) between patients and controls within each site remained unaffected by harmonization. Finally, we evaluated the association between white matter hyperintensity (WMH) burden, FA, MD and PSMD using linear regression analyses both within individual cohorts as well as with pooled scans from multiple sites, before and after harmonization. Results: Before harmonization, significant differences in FA and MD were observed between matched controls of different sites (p < 0.05). After harmonization these site-differences were removed. Within each site, RISH harmonization did not alter the effect sizes of FA, MD and PSMD between patients and controls (relative change in Cohen's d = 4 %) nor the strength of association with WMH volume (relative change in R2 = 2.8 %). After harmonization, patient data of all sites could be aggregated in a single analysis to infer the association between WMH volume and FA (R2 = 0.62), MD (R2 = 0.64), and PSMD (R2 = 0.60). Conclusions: We showed that RISH harmonization effectively removes acquisition-related differences in dMRI of elderly subjects while preserving sensitivity to SVD-related effects. This study provides proof of concept for future multicentre SVD studies with pooled datasets. | |
dc.language.iso | en | |
dc.publisher | ELSEVIER SCI LTD | |
dc.source | Elements | |
dc.subject | Science & Technology | |
dc.subject | Life Sciences & Biomedicine | |
dc.subject | Neuroimaging | |
dc.subject | Neurosciences & Neurology | |
dc.subject | Diffusion MRI | |
dc.subject | Harmonization | |
dc.subject | Cerebral small vessel disease | |
dc.subject | Multicentre | |
dc.subject | White matter hyperintensities | |
dc.subject | WHITE-MATTER | |
dc.subject | COGNITIVE IMPAIRMENT | |
dc.subject | MEAN DIFFUSIVITY | |
dc.subject | HUMAN BRAIN | |
dc.subject | NETWORK | |
dc.subject | DISRUPTION | |
dc.subject | DEMENTIA | |
dc.subject | SCANNER | |
dc.type | Article | |
dc.date.updated | 2022-04-08T02:24:07Z | |
dc.contributor.department | PHARMACOLOGY | |
dc.contributor.department | SAW SWEE HOCK SCHOOL OF PUBLIC HEALTH | |
dc.description.doi | 10.1016/j.nicl.2021.102886 | |
dc.description.sourcetitle | NEUROIMAGE-CLINICAL | |
dc.description.volume | 32 | |
dc.published.state | Published | |
Appears in Collections: | Staff Publications Elements |
Show simple item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease.pdf | 15.8 MB | Adobe PDF | OPEN | None | View/Download |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.