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.

Brain Sciences
|January 21, 2023
PubMed

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.