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Brain Functional Network Analysis of Patients with Primary Angle-Closure Glaucoma
Dan Liu1, Junwei Gao2, Tao You3
1Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430079 Hubei Province, China.
Disease Markers
|January 17, 2022
Summary
Primary angle-closure glaucoma (PACG) patients show altered regional brain network organization, particularly in visual and non-visual areas, despite normal global network efficiency. These changes correlate with clinical measures of glaucoma severity.
Area of Science:
- Neuroscience
- Ophthalmology
- Medical Imaging
Background:
- Glaucoma is associated with neuronal degeneration, but functional brain network topology differences in primary angle-closure glaucoma (PACG) are understudied.
- Resting-state fMRI reveals spontaneous brain activity patterns relevant to neurological conditions.
Purpose of the Study:
- To investigate alterations in functional brain network topology and efficiency in patients with PACG.
- To compare network properties between PACG patients and healthy controls using graph theory.
Main Methods:
- Resting-state fMRI data acquired from 33 PACG patients and 33 matched healthy controls.
- Functional connectivity networks constructed and analyzed using graph theoretical approaches.
- Partial correlations assessed between altered regional network values and clinical glaucoma parameters (RNFLT, V C/D).
Main Results:
- No significant differences in global topological network measures between PACG patients and controls.
- Significant regional topological alterations observed in PACG patients, affecting visual, somatomotor, and cognition-emotion networks.
- Right superior parietal gyrus efficiency correlated with RNFLT and V C/D; left middle frontal gyrus betweenness correlated with V C/D.
Conclusions:
- Regional network inefficiencies and compensatory increases in local properties in PACG patients maintain global network integrity.
- Functional brain network alterations in PACG extend beyond visual processing areas.
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