Cortical tortuosity as a potential clinical biomarker for Alzheimer’s disease: A 3D MRI analysis of brain morphological changes

Cortical tortuosity provides a complementary measure of brain morphological changes in AD, with potential as a biomarker for disease progression and cognitive decline. These findings highlight the clinical utility of cortical tortuosity in understanding and monitoring AD-related brain changes.

Authors

Institutions

Publication Details

Journal
NeuroImage Clinical
Published
2025-01-01
DOI
https://doi.org/10.1016/j.nicl.2025.103877
Primary Topic
Connective tissue disorders research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cortical tortuosity as a potential clinical biomarker for Alzheimer’s disease: A 3D MRI analysis of brain morphological changes

Deqiang Qiu, Maria-Julieta Mateos, James J. Lah
NeuroImage Clinical
Connective tissue disorders research
article

Cortical tortuosity as a potential clinical biomarker for Alzheimer’s disease: A 3D MRI analysis of brain morphological changes

Deqiang Qiu, Maria-Julieta Mateos, James J. Lah
article en

Abstract

Cortical tortuosity provides a complementary measure of brain morphological changes in AD, with potential as a biomarker for disease progression and cognitive decline. These findings highlight the clinical utility of cortical tortuosity in understanding and monitoring AD-related brain changes.

NeuroImage ClinicalVol. 48
Emory University (US)
Openalex Percentile: Top 73%
Connective tissue disorders research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.