Ranking diffusion tensor measures of brain aging and Alzheimer's disease

Artemis Zavaliangos-Petropulu, Talia M. Nir, Sophia I. Thomopoulos, Neda Jahanshad, Robert I. Reid, Matthew A Bernstein, Bret Borowski, Clifford R Jr. Jack, Michael W. Weiner, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Diffusion-weighted MRI (dMRI) offers a range of measures that are sensitive to brain aging and neurodegeneration. Here we analyzed data from 318 participants (mean age: 75.4±7.9 years; 143 men/175 women) from the third phase of the Alzheimer's Disease Neuroimaging Initiative (ADNI3), who were each scanned with one of six different diffusion MRI protocols using scanners from three different manufacturers. We computed 4 standard diffusion tensor imaging (DTI) anisotropy and diffusivity indices, and one advanced anisotropy index based on the tensor distribution function (TDF), in 24 white matter regions of interest. Modeling protocol effects, we ranked the diffusion indices for their strength of correlation with 3 standard clinical measures of cognitive impairment: the ADAS-Cog, MMSE, and sum-of-boxes Clinical Dementia Rating. Across all dMRI indices and cognitive measures, the cingulum-hippocampal region and the uncinate showed some of the strongest associations with cognitive impairment; largest effect sizes were detected with axial diffusivity (AxDDTI). While fractional anisotropy (FA) derived from the DTI model was the weakest in detecting associations with cognitive measures, FA derived from the TDF detected widespread, robust associations. Protocol differences affected dMRI indices; however by modeling protocol effects, we were able to pool dMRI data from multiple acquisition protocols and detect consistent associations with cognitive impairment and age. dMRI indices computed from the upgraded scanning protocols in ADNI3 were sensitive to cognitive impairment in brain aging, offering a benchmark to compare to future multi-shell or multi-compartment diffusion indices.

Original languageEnglish (US)
Title of host publication14th International Symposium on Medical Information Processing and Analysis
EditorsNatasha Lepore, Eduardo Romero, Jorge Brieva
PublisherSPIE
Volume10975
ISBN (Electronic)9781510626058
DOIs
StatePublished - Jan 1 2018
Event14th International Symposium on Medical Information Processing and Analysis, SIPAIM 2018 - Mazatlan, Mexico
Duration: Oct 24 2018Oct 26 2018

Other

Other14th International Symposium on Medical Information Processing and Analysis, SIPAIM 2018
CountryMexico
CityMazatlan
Period10/24/1810/26/18

Keywords

  • ADNI3
  • Aging
  • Alzheimer's Disease
  • Diffusion
  • Diffusion Tensor Imaging

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Zavaliangos-Petropulu, A., Nir, T. M., Thomopoulos, S. I., Jahanshad, N., Reid, R. I., Bernstein, M. A., Borowski, B., Jack, C. R. J., Weiner, M. W., & Thompson, P. M. (2018). Ranking diffusion tensor measures of brain aging and Alzheimer's disease. In N. Lepore, E. Romero, & J. Brieva (Eds.), 14th International Symposium on Medical Information Processing and Analysis (Vol. 10975). [109750O] SPIE. https://doi.org/10.1117/12.2506694