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Multi-structure network shape analysis via normal surface momentum maps.

Anqi Qiu1, Michael I Miller

  • 1Division of Bioengineering, National University of Singapore, Singapore. bieqa@nus.edu.sg

Neuroimage
|August 5, 2008
PubMed
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We developed a novel shape analysis pipeline to assess anatomical variations in brain subcortical networks using MR images. This method reveals shape compression in the hippocampus-amygdala network in healthy elders, indicating altered anatomical connectivity.

Area of Science:

  • Neuroimaging
  • Computational Anatomy
  • Medical Image Analysis

Background:

  • Subcortical networks are crucial for cognitive functions.
  • Assessing anatomical variations in these networks is challenging.
  • Magnetic Resonance Imaging (MRI) provides detailed brain structure information.

Purpose of the Study:

  • To present a shape analysis pipeline for assessing anatomical variations in subcortical networks from MR images.
  • To apply the pipeline to study anatomical connectivity in the hippocampus-amygdala network during healthy aging.

Main Methods:

  • Utilized large deformation diffeomorphic metric mapping (LDDMM) to inject global shape properties of a template into subcortical parcellations.
  • Employed random field representation of template surface momentum maps to encode shape variations.

Related Experiment Videos

  • Developed a two-level statistical model on momentum maps to assess anatomical connectivity based on surface deformation.

    • Main Results:

    • Demonstrated the shape analysis pipeline's capability in assessing subcortical structure variations using OASIS database samples.
    • Identified significant shape compression in the hippocampus-amygdala network of healthy elders compared to young adults.
    • Revealed anatomical connectivity between the basolateral complex of the amygdala and the subiculum of the hippocampus based on shape compression.

    Conclusions:

    • The shape analysis pipeline effectively quantifies anatomical variations in subcortical networks.
    • Healthy aging is associated with specific patterns of shape compression in the hippocampus-amygdala network.
    • The findings suggest altered anatomical connectivity in aging individuals, particularly between key amygdala and hippocampal subregions.