MRI-guided clustering of patients with mild dementia due to Alzheimer's disease using self-organizing maps.

ABSTRACT:

Introduction

Alzheimer's disease (AD) is a phenotypically and pathologically heterogenous neurodegenerative disorder. This heterogeneity can be studied and disentangled using data-driven clustering techniques.

Methods

We implemented a self-organizing map clustering algorithm on baseline volumetric MRI measures from nine brain regions of interest (ROIs) to cluster 1041 individuals enrolled in the placebo arm of the EXPEDITION3 trial. Volumetric MRI differences were compared among clusters. Demographics as well as baseline and longitudinal cognitive performance metrics were used to evaluate cluster characteristics.

Results

Three distinct clusters, with an overall silhouette coefficient of 0.491, were identified based on MRI volumetrics. Cluster 1 (N = 400) had the large

SUBMITTER: Petersen KK 

PROVIDER: S-EPMC11781377 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature