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Published on: June 26, 2013
Functional magnetic resonance-based analysis of dynamic functional connectivity in patients with olfactory impairment
1The 924th Hospital of the People's Liberation Army Joint Logistics Support Force, 541000, China.
Objective:
The purpose of this research is to utilize resting-state functional magnetic resonance imaging (rs-fMRI), combined with sliding-window and cluster analysis methods. To identify alterations in functional connectivity (FC) patterns in patients with Parkinson's disease who exhibit olfactory dysfunction prior to the onset of motor symptoms, compared to healthy individuals.This method is intended to improve capabilities for the early detection of PD.
Materials And Methods:
We recruited fifteen individuals from three distinct groups: PD patients with no or mild olfactory dysfunction (PD-N/MH), those with severe olfactory dysfunction, and healthy controls (HC). We gathered and analyzed resting-state fMRI data to examine dynamic FC across these groups, subsequently conducting a thorough statistical evaluation.
Results:
Our cluster analysis identified two unique states of brain network connections across the groups. Notably, the subgroup with PD exhibited a more frequent occurrence and extended duration in state 1, along with reduced state transitions. Notably, the severity of olfactory dysfunction was significantly correlated with increased durations and frequencies in state 1 (P ＜0.05).
Conclusion:
These observations underscore the significant relationship between state 1 connectivity patterns and olfactory impairment in PD patients. The discovery that PD patients with Parkinson's disease (PD) "linger" in the sparsely connected state 1 provides a dynamic functional correlate of the progressive pathology that initially affects olfaction. Dynamic functional connectivity analysis successfully distinguished PD patients from healthy controls even prior to the onset of motor symptoms, suggesting its potential as a neuroimaging biomarker for Parkinson's disease. Consequently, this method may facilitate early identification, timely intervention, and improved clinical management of PD by providing an early warning signal before motor symptom--based diagnosis, thereby potentially delaying disease progression and alleviating the burden on patients, families, and society.
