Exploring cortical morphology biomarkers of amnesic mild cognitive impairment using novel fractal dimension-based

Chi-Wen Jao1,2, Yu-Te Wu1,3, Jiann-Horng Yeh4,5

  • 1Institute of Biophotonics, National Yang Ming Chiao Tung University, Taipei, Taiwan.

Insights

Fractal dimension analysis of brain MRIs effectively distinguishes amnestic mild cognitive impairment (aMCI) from healthy individuals. This novel biomarker shows higher accuracy than traditional cortical thickness measurements for detecting early Alzheimer's disease changes.

Area of Science:

  • Neuroimaging
  • Biomarker Discovery
  • Alzheimer's Disease Research

Background:

  • Amnestic mild cognitive impairment (aMCI) is a precursor to Alzheimer's disease, lacking effective MRI biomarkers for early detection.
  • Current methods like cortical thickness have limitations in capturing subtle morphological changes.
  • Fractal dimension offers a more sensitive quantitative measure of brain structure.

Purpose of the Study:

  • To develop an automated method for distinguishing aMCI from healthy controls using cerebral cortex fractal dimension.
  • To compare the efficacy of fractal dimension versus cortical thickness in identifying aMCI-related brain changes.

Main Methods:

  • Structural MRI scans were acquired from 30 aMCI patients and 30 healthy controls.
  • Cortical atrophy was assessed using fractal dimension and cortical thickness across Desikan-Killiany atlas regions.
  • An unsupervised discriminator was trained using fractal dimension and cortical thickness data.

Main Results:

  • Fractal dimension was more sensitive than cortical thickness, detecting changes in more brain regions.
  • Significantly lower fractal dimension values were observed in the temporal, limbic, and parietal lobes of aMCI patients.
  • The fractal dimension-based discriminator achieved 80.54% accuracy in differentiating aMCI from healthy controls.

Conclusions:

  • Fractal dimension is a promising MRI biomarker for detecting cortical morphology alterations in aMCI.
  • This quantitative measure can effectively discriminate individuals with aMCI from healthy controls.
  • Further research can leverage fractal dimension for earlier and more accurate Alzheimer's disease diagnosis.