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Artemis Zavaliangos-Petropulu1, Talia M Nir1, Sophia I Thomopoulos1
1Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States.
Abstract:
Brain imaging with diffusion-weighted MRI (dMRI) is sensitive to microstructural white matter (WM) changes associated with brain aging and neurodegeneration. In its third phase, the Alzheimer's Disease Neuroimaging Initiative (ADNI3) is collecting data across multiple sites and scanners using different dMRI acquisition protocols, to better understand disease effects. It is vital to understand when data can be pooled across scanners, and how the choice of dMRI protocol affects the sensitivity of extracted measures to differences in clinical impairment. Here, we analyzed ADNI3 data from 317 participants (mean age: 75.4 ± 7.9 years; 143 men/174 women), who were each scanned at one of 47 sites with one of six dMRI protocols using scanners from three different manufacturers. We computed four standard diffusion tensor imaging (DTI) indices including fractional anisotropy (FADTI) and mean, radial, and axial diffusivity, and one FA index based on the tensor distribution function (FATDF), in 24 bilaterally averaged WM regions of interest. We found that protocol differences significantly affected dMRI indices, in particular FADTI. We ranked the diffusion indices for their strength of association with four clinical assessments. In addition to diagnosis, we evaluated cognitive impairment as indexed by three commonly used screening tools for detecting dementia and AD: the AD Assessment Scale (ADAS-cog), the Mini-Mental State Examination (MMSE), and the Clinical Dementia Rating scale sum-of-boxes (CDR-sob). Using a nested random-effects regression model to account for protocol and site, we found that across all dMRI indices and clinical measures, the hippocampal-cingulum and fornix (crus)/stria terminalis regions most consistently showed strong associations with clinical impairment. Overall, the greatest effect sizes were detected in the hippocampal-cingulum (CGH) and uncinate fasciculus (UNC) for associations between axial or mean diffusivity and CDR-sob. FATDF detected robust widespread associations with clinical measures, while FADTI was the weakest of the five indices for detecting associations. Ultimately, we were able to successfully pool dMRI data from multiple acquisition protocols from ADNI3 and detect consistent and robust associations with clinical impairment and age.
Insights
Diffusion-weighted MRI (dMRI) data from Alzheimer's Disease Neuroimaging Initiative 3 (ADNI3) can be pooled across scanners and protocols. Certain dMRI indices and brain regions show strong associations with clinical impairment in aging and neurodegeneration.
Area of Science:
- Neuroimaging
- Neuroscience
- Medical Imaging Analysis
Background:
- Diffusion-weighted MRI (dMRI) is sensitive to white matter (WM) microstructural changes in aging and neurodegeneration.
- The Alzheimer's Disease Neuroimaging Initiative 3 (ADNI3) collects dMRI data across multiple sites, scanners, and protocols, necessitating an understanding of data pooling.
- Assessing the impact of dMRI acquisition protocols on the sensitivity of WM measures to clinical impairment is crucial for multi-site studies.
Purpose of the Study:
- To determine if dMRI data from ADNI3 can be pooled across different acquisition protocols and scanners.
- To evaluate how different dMRI protocols affect the sensitivity of diffusion indices in detecting associations with clinical impairment.
- To identify specific dMRI indices and WM regions that are most robustly associated with cognitive decline and aging.
Main Methods:
- Analysis of ADNI3 dMRI data from 317 participants scanned across 47 sites using six different dMRI protocols on three manufacturers' scanners.
- Computation of five diffusion indices: fractional anisotropy (FADTI), mean diffusivity, radial diffusivity, axial diffusivity, and tensor distribution function fractional anisotropy (FATDF) in 24 WM regions.
- Application of a nested random-effects regression model to assess associations between diffusion indices and clinical assessments (diagnosis, ADAS-cog, MMSE, CDR-sob), accounting for protocol and site effects.
Main Results:
- Protocol differences significantly impacted dMRI indices, particularly FADTI.
- The hippocampal-cingulum and fornix (crus)/stria terminalis regions showed consistent strong associations with clinical impairment across all diffusion indices and clinical measures.
- FATDF demonstrated robust associations with clinical measures, outperforming FADTI, which was the weakest index. Axial or mean diffusivity in the hippocampal-cingulum (CGH) and uncinate fasciculus (UNC) showed the largest effect sizes with CDR-sob.
Conclusions:
- ADNI3 dMRI data acquired with multiple protocols can be successfully pooled to detect robust associations with clinical impairment and age.
- FATDF is a sensitive index for detecting widespread associations with clinical measures in aging and neurodegeneration.
- Specific WM regions like the hippocampal-cingulum are key targets for understanding the relationship between white matter integrity and cognitive function.
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