Diffusion MRI metrics and their relation to dementia severity: effects of harmonization approaches

Sophia I Thomopoulos; Talia M. Nir; Julio E. Villalon-Reina; Artemis Zavaliangos-Petropulu; Piyush Maiti; Hong Zheng; Elnaz Nourollahimoghadam; Neda Jahanshad; Paul M. Thompson

doi:10.1117/12.2606337

10 December 2021 Diffusion MRI metrics and their relation to dementia severity: effects of harmonization approaches

Sophia I Thomopoulos, Talia M. Nir, Julio E. Villalon-Reina, Artemis Zavaliangos-Petropulu, Piyush Maiti, Hong Zheng, Elnaz Nourollahimoghadam, Neda Jahanshad, Paul M. Thompson

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Proceedings Volume 12088, 17th International Symposium on Medical Information Processing and Analysis; 120880K (2021) https://doi.org/10.1117/12.2606337
Event: Seventeenth International Symposium on Medical Information Processing and Analysis, 2021, Campinas, Brazil

Abstract

Diffusion-weighted magnetic resonance imaging (dMRI) is sensitive to microstructural changes in the brain that occur with normal aging and Alzheimer’s disease (AD). There is much interest in which dMRI measures are most strongly correlated with (1) AD diagnosis, (2) clinical measures of AD severity, such as the clinical dementia rating (CDR), and (3) biological processes that may be disrupted in AD, such as brain amyloid load measured using PET. Of these processes, some can be targeted using novel drugs. Since 2016, the Alzheimer’s Disease Neuroimaging Initiative (ADNI) has collected dMRI data from three scanner manufacturers across 58 sites using 7 different protocols that vary in angular resolution, scan duration, and distribution of diffusion-weighted gradients. Here, we assessed dMRI data from 730 of those individuals (447 healthy controls, 214 with mild cognitive impairment, 69 with dementia; age: 74.1±7.9 years; 381 female/349 male). To harmonize data from different protocols, we applied ComBat, ComBat-GAM, and CovBat to dMRI metrics from 28 brain regions of interest. We ranked all dMRI metrics in order of the strength of clinically relevant associations, and assessed how this depended on the harmonization methods employed. dMRI metrics were strongly associated with age and AD severity, but also with amyloid positivity. All harmonization methods gave comparable results when assessing associations with age, dementia and amyloid load, while enabling data integration across multiple scanners and protocols.

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Sophia I Thomopoulos, Talia M. Nir, Julio E. Villalon-Reina, Artemis Zavaliangos-Petropulu, Piyush Maiti, Hong Zheng, Elnaz Nourollahimoghadam, Neda Jahanshad, and Paul M. Thompson "Diffusion MRI metrics and their relation to dementia severity: effects of harmonization approaches", Proc. SPIE 12088, 17th International Symposium on Medical Information Processing and Analysis, 120880K (10 December 2021); https://doi.org/10.1117/12.2606337

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KEYWORDS

Data modeling

Dementia

Magnetic resonance imaging

Neuroimaging

Scanners

Statistical analysis

Data acquisition

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