Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease
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 bee...
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2021
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oai:doaj.org-article:11ff756994d94119bbbf4bffb35bdbd42021-11-22T04:25:02ZDiffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease2213-158210.1016/j.nicl.2021.102886https://doaj.org/article/11ff756994d94119bbbf4bffb35bdbd42021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2213158221003302https://doaj.org/toc/2213-1582Objectives: 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.Bruno M. de Brito RobaloGeert Jan BiesselsChristopher ChenAnna DewenterMarco DueringSaima HilalHuiberdina L. KoekAnna KopczakBonnie Yin Ka LamAlexander LeemansVincent MokLaurien P. OnkenhoutHilde van den BrinkAlberto de LucaElsevierarticleDiffusion MRIHarmonizationCerebral small vessel diseaseMulticentreWhite matter hyperintensitiesComputer applications to medicine. Medical informaticsR858-859.7Neurology. Diseases of the nervous systemRC346-429ENNeuroImage: Clinical, Vol 32, Iss , Pp 102886- (2021) |
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Diffusion MRI Harmonization Cerebral small vessel disease Multicentre White matter hyperintensities Computer applications to medicine. Medical informatics R858-859.7 Neurology. Diseases of the nervous system RC346-429 |
| spellingShingle |
Diffusion MRI Harmonization Cerebral small vessel disease Multicentre White matter hyperintensities Computer applications to medicine. Medical informatics R858-859.7 Neurology. Diseases of the nervous system RC346-429 Bruno M. de Brito Robalo Geert Jan Biessels Christopher Chen Anna Dewenter Marco Duering Saima Hilal Huiberdina L. Koek Anna Kopczak Bonnie Yin Ka Lam Alexander Leemans Vincent Mok Laurien P. Onkenhout Hilde van den Brink Alberto de Luca Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease |
| description |
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. |
| format |
article |
| author |
Bruno M. de Brito Robalo Geert Jan Biessels Christopher Chen Anna Dewenter Marco Duering Saima Hilal Huiberdina L. Koek Anna Kopczak Bonnie Yin Ka Lam Alexander Leemans Vincent Mok Laurien P. Onkenhout Hilde van den Brink Alberto de Luca |
| author_facet |
Bruno M. de Brito Robalo Geert Jan Biessels Christopher Chen Anna Dewenter Marco Duering Saima Hilal Huiberdina L. Koek Anna Kopczak Bonnie Yin Ka Lam Alexander Leemans Vincent Mok Laurien P. Onkenhout Hilde van den Brink Alberto de Luca |
| author_sort |
Bruno M. de Brito Robalo |
| title |
Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease |
| title_short |
Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease |
| title_full |
Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease |
| title_fullStr |
Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease |
| title_full_unstemmed |
Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease |
| title_sort |
diffusion mri harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease |
| publisher |
Elsevier |
| publishDate |
2021 |
| url |
https://doaj.org/article/11ff756994d94119bbbf4bffb35bdbd4 |
| work_keys_str_mv |
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