Association Between Hippocampal Atrophy and Cognitive Decline in Alzheimer’s Disease Using ADNI Data

Presenter Information

Start Date

April 2026

Location

2nd floor - Library

Abstract

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and structural brain atrophy, particularly within the hippocampus. Quantifying the relationship between hippocampal volume and cognitive performance is helpful for understanding the disease progression and identifying potential imaging biomarkers. This study aimed to evaluate the association between hippocampal atrophy and cognitive decline across diagnostic groups using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). A cohort of 641 subjects spanning cognitively normal (CN), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) groups was analyzed. MRI-derived hippocampal volumes were combined with clinical cognitive measures, including the Clinical Dementia Rating Scale Sum of Boxes (CDRSB) and Mini-Mental State Examination (MMSE). Pearson correlation analyses were performed to assess relationships between hippocampal volume and cognitive scores. One-way ANOVA was used to compare differences across diagnostic groups. Hippocampal volume was significantly negatively correlated with CDRSB scores (r = -0.45, p < 0.001) and positively correlated with MMSE scores (r = 0.42, p < 0.001), indicating that reduced hippocampal volume is associated with worse cognitive performance. Additionally, significant differences in hippocampal volume and cognitive scores were observed across diagnostic groups (ANOVA, p < 0.001), with AD participants exhibiting the lowest hippocampal volumes and greatest cognitive impairment. Visual assessment of representative MRI scans further demonstrated progressive hippocampal atrophy from CN to MCI to AD. These findings support hippocampal atrophy as a biomarker of cognitive decline and disease severity in Alzheimer’s disease and reinforce the value of combining neuroimaging and clinical data for tracking disease progression.

This document is currently not available here.

Share

COinS
 
Apr 22nd, 3:35 PM Apr 22nd, 4:35 PM

Association Between Hippocampal Atrophy and Cognitive Decline in Alzheimer’s Disease Using ADNI Data

2nd floor - Library

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and structural brain atrophy, particularly within the hippocampus. Quantifying the relationship between hippocampal volume and cognitive performance is helpful for understanding the disease progression and identifying potential imaging biomarkers. This study aimed to evaluate the association between hippocampal atrophy and cognitive decline across diagnostic groups using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). A cohort of 641 subjects spanning cognitively normal (CN), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) groups was analyzed. MRI-derived hippocampal volumes were combined with clinical cognitive measures, including the Clinical Dementia Rating Scale Sum of Boxes (CDRSB) and Mini-Mental State Examination (MMSE). Pearson correlation analyses were performed to assess relationships between hippocampal volume and cognitive scores. One-way ANOVA was used to compare differences across diagnostic groups. Hippocampal volume was significantly negatively correlated with CDRSB scores (r = -0.45, p < 0.001) and positively correlated with MMSE scores (r = 0.42, p < 0.001), indicating that reduced hippocampal volume is associated with worse cognitive performance. Additionally, significant differences in hippocampal volume and cognitive scores were observed across diagnostic groups (ANOVA, p < 0.001), with AD participants exhibiting the lowest hippocampal volumes and greatest cognitive impairment. Visual assessment of representative MRI scans further demonstrated progressive hippocampal atrophy from CN to MCI to AD. These findings support hippocampal atrophy as a biomarker of cognitive decline and disease severity in Alzheimer’s disease and reinforce the value of combining neuroimaging and clinical data for tracking disease progression.