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. Jack Jr.; Michael W. Weiner; Paul M. Thompson

doi:10.1117/12.2506694

21 December 2018 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. Jack Jr., Michael W. Weiner, Paul M. Thompson

Author Affiliations +

Proceedings Volume 10975, 14th International Symposium on Medical Information Processing and Analysis; 109750O (2018) https://doi.org/10.1117/12.2506694
Event: 14th International Symposium on Medical Information Processing and Analysis, 2018, Mazatlán, Mexico

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 (Ax^DDTI). 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.

Citation Download Citation

Artemis Zavaliangos-Petropulu, Talia M. Nir, Sophia I. Thomopoulos, Neda Jahanshad, Robert I. Reid, Matthew A. Bernstein, Bret Borowski, Clifford R. Jack Jr., Michael W. Weiner, and Paul M. Thompson "Ranking diffusion tensor measures of brain aging and Alzheimer’s disease", Proc. SPIE 10975, 14th International Symposium on Medical Information Processing and Analysis, 109750O (21 December 2018); https://doi.org/10.1117/12.2506694

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available