Intravoxel incoherent motion diffusion-weighted imaging in the characterization of Alzheimer's disease

Altered resting-state functional connectivity and dynamic network properties in cognitive impairment: an independent component and dominant-coactivation pattern analyses study

Introduction

Cognitive impairment (CI) due to Alzheimer's disease (AD) encompasses a decline in cognitive abilities and can significantly impact an individual's quality of life. Early detection and intervention are crucial in managing CI, both in the preclinical and prodromal stages of AD prior to dementia.

Methods

In this preliminary study, we investigated differences in resting-state functional connectivity and dynamic network properties between 23 individual with CI due to AD based on clinical assessment and 15 healthy controls (HC) using Independent Component Analysis (ICA) and Dominant-Coactivation Pattern (d-CAP) analysis. The cognitive status of the two groups was also compared, and correlations between cognitive scores and d-CAP switching probability were examined.

Results

Results showed comparable numbers of d-CAPs in the Default Mode Network (DMN), Executive Control Network (ECN), and Frontoparietal Network (FPN) between HC and CI groups. However, the Visual Network (VN) exhibited fewer d-CAPs in the CI group, suggesting altered dynamic properties of this network for the CI group. Additionally, ICA revealed significant connectivity differences for all networks. Spatial maps and effect size analyses indicated increased coactivation and more synchronized activity within the DMN in HC compared to CI. Furthermore, reduced switching probabilities were observed for the CI group in DMN, VN, and FPN networks, indicating less dynamic and flexible functional interactions.

Discussion

The findings highlight altered connectivity patterns within the DMN, VN, ECN, and FPN, suggesting the involvement of multiple functional networks in CI. Understanding these brain processes may contribute to developing targeted diagnostic and therapeutic strategies for CI due to AD.

The dependence of cerebral interstitial fluid on diffusion-sensitizing directions: A multi-b-value diffusion MRI study in a memory clinic sample

Three-component intravoxel incoherent motion (3C-IVIM) imaging with spectral analysis provides a proxy for interstitial fluid (ISF) (e.g., in perivascular spaces (PVS), granting a potential marker for altered cerebral clearance. When 3C-IVIM images are acquired with three orthogonal diffusion-sensitizing directions, these are often averaged into the Trace image. This may result in loss of valuable direction-specific information, particularly in PVS-rich regions (basal ganglia (BG) and centrum semiovale (CSO)). This study assessed the dependence of individual diffusion-sensitizing directions to the ISF fraction in PVS-rich regions. Additionally, we explored the value of diffusion direction-specific information on ISF characteristics in distinguishing thirty-one patients with cognitive impairment (CI) (Alzheimer's disease (n = 15) or Mild Cognitive Impairment (n = 16)) from thirty cognitively healthy elderly controls (CON). Multi-b-value diffusion-weighted images were acquired in three orthogonal directions (L-R (left-right), A-P (anterior-posterior) and S-I (superior-inferior)) at 3 T. Voxel-based spectral analysis using non-negative least squares was conducted to independently analyze the L-R, A-P, S-I, and Trace images. 3C-IVIM measures were first compared between diffusion-sensitizing directions and the Trace within the BG using repeated measures ANOVA. Subsequently, the 3C-IVIM measures were compared per direction between the CI and CSO group in the BG and CSO with multivariable linear regression. Our results show that the ISF fraction significantly differs between all diffusion-sensitizing directions and Trace in the BG, with the highest ISF fraction detected using S-I. Solely using S-I, a higher ISF fraction was identified in CI compared to CON in the BG (p = .020) and CSO (p = .046). Thereby, this study found that the measured ISF fraction depends on the acquired diffusion-sensitizing direction, where S-I is most sensitive to detect ISF and differences between CI and CON. The Trace approach is not always sensitive enough to ISF characteristics. Solely acquiring S-I may offer an alternative to reduce scanning time.