Analysis of Brain Structural Connectivity Networks and White Matter Integrity in Patients With Mild Cognitive Impairment

Maurizio Bergamino,Ashley M Stokes,Simona Schiavi,Alessandro Daducci,Ryan R Walsh

doi:10.3389/fnagi.2022.793991

Abstract

White matter integrity and structural connectivity may be altered in mild cognitive impairment (MCI), and these changes may closely reflect decline in specific cognitive domains. Multi-shell diffusion data in healthy control (HC, n = 31) and mild cognitive impairment (MCI, n = 19) cohorts were downloaded from the ADNI3 database. The data were analyzed using an advanced approach to assess both white matter microstructural integrity and structural connectivity. Compared with HC, lower intracellular compartment (IC) and higher isotropic (ISO) values were found in MCI. Additionally, significant correlations were found between IC and Montreal Cognitive Assessment (MoCA) scores in the MCI cohort. Network analysis detected structural connectivity differences between the two groups, with lower connectivity in MCI. Additionally, significant differences between HC and MCI were observed for global network efficiency. Our results demonstrate the potential of advanced diffusion MRI biomarkers for understanding brain changes in MCI.

Highlights

Mild cognitive impairment (MCI) is defined by a mild but objective decline in cognitive function beyond that associated with normal aging; while patients with mild cognitive impairment (MCI) do not yet meet the criteria for dementia, MCI is thought to represent a prodromal phase of Alzheimer’s disease (AD) (MetzlerBaddeley et al, 2012)
Microstructural integrity can be assessed by fitting a relevant model to obtain voxel-wise measures related to the local diffusion of water around axons, while tractography can yield biomarkers related to the large-scale structural connectivity of the brain
The Mini-Mental State Exam (MMSE) score was available for all participants, while the Montreal Cognitive Assessment (MoCA) score was available for 28 healthy controls (HC) and 15 MCI subjects

Summary

Introduction

Mild cognitive impairment (MCI) is defined by a mild but objective decline in cognitive function beyond that associated with normal aging; while patients with MCI do not yet meet the criteria for dementia, MCI is thought to represent a prodromal phase of Alzheimer’s disease (AD) (MetzlerBaddeley et al, 2012). The standard single-tensor DTI model is based on a Gaussian diffusion assumption, which has only a single directional maximum; as a result, DTI cannot resolve multiple fiber orientations within a voxel (Tuch et al, 2002). This has led to the development of more complex, higher order models (Zhan et al, 2015) to resolve multiple intravoxel fiber orientations. A previous study using this model, combined with a probabilistic tractography method, showed superior performance in differentiating between normal controls and MCI (Zhan et al, 2015)

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