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Decreased Brain Structural Network Connectivity in Patients with Mild Cognitive Impairment: A Novel Fractal Dimension
Chi Ieong Lau1,2,3,4,5, Jiann-Horng Yeh2,6, Yuh-Feng Tsai2,7
1Institute of Biophotonics, National Yang Ming Chiao Tung University, Taipei 112, Taiwan.
Abstract:
Mild cognitive impairment (MCI) is widely regarded to be the intermediate stage to Alzheimer's disease. Cerebral morphological alteration in cortical subregions can provide an accurate predictor for early recognition of MCI. Thirty patients with MCI and thirty healthy control subjects participated in this study. The Desikan-Killiany cortical atlas was applied to segment participants' cerebral cortex into 68 subregions. A complexity measure termed fractal dimension (FD) was applied to assess morphological changes in cortical subregions of participants. The MCI group revealed significantly decreased FD values in the bilateral temporal lobes, right parietal lobe including the medial temporal, fusiform, para hippocampal, and also the orbitofrontal lobes. We further proposed a novel FD-based brain structural network to compare network parameters, including intra- and inter-lobular connectivity between groups. The control group had five modules, and the MCI group had six modules in their brain networks. The MCI group demonstrated shrinkage of modular sizes with fewer components integrated, and significantly decreased global modularity in the brain network. The MCI group had lower intra- and inter-lobular connectivity in all lobes. Between cerebral lobes, the MCI patients may maintain nodal connections between both hemispheres to reduce connectivity loss in the lateral hemispheres. The method and results presented in this study could be a suitable tool for early detection of MCI.
Insights
Mild cognitive impairment (MCI) shows altered brain structure. Fractal dimension analysis reveals reduced connectivity in MCI patients, offering a potential tool for early Alzheimer's disease detection.
Area of Science:
- Neuroscience
- Medical Imaging
- Computational Biology
Background:
- Mild cognitive impairment (MCI) is a precursor to Alzheimer's disease.
- Cerebral morphological alterations are key indicators for early MCI detection.
Purpose of the Study:
- To investigate cerebral morphological changes in MCI using fractal dimension (FD).
- To develop and analyze an FD-based brain structural network for MCI.
- To compare network parameters between MCI patients and healthy controls.
Main Methods:
- Utilized the Desikan-Killiany cortical atlas to segment the brain into 68 subregions.
- Applied fractal dimension (FD) analysis to assess morphological complexity.
- Constructed and analyzed FD-based brain structural networks, comparing modularity and connectivity.
Main Results:
- MCI patients exhibited significantly decreased FD in bilateral temporal, right parietal, and orbitofrontal lobes.
- Brain networks in MCI patients showed altered modularity (six modules vs. five in controls) and reduced global modularity.
- MCI group displayed lower intra- and inter-lobular connectivity across all lobes.
Conclusions:
- FD analysis effectively detects cerebral morphological alterations in MCI.
- FD-based brain network analysis reveals significant structural network changes in MCI.
- This approach shows promise as a tool for the early detection of mild cognitive impairment.

