The Effect of Segmentation Method on Medial Temporal Lobe Subregion Volumes in Aging

Negar Mazloum-Farzaghi1,2, Morgan D Barense1,2, Jennifer D Ryan1,2,3

  • 1Department of Psychology, University of Toronto, Toronto, Ontario, Canada.

Human Brain Mapping
|October 25, 2024
PubMed

Insights

Automated segmentation of medial temporal lobe (MTL) subregions using ASHS-OAP shows promise for detecting early Alzheimer's disease (AD) changes. This method offers a faster alternative to manual segmentation for identifying neurodegeneration in healthy older adults.

Area of Science:

  • Neuroimaging
  • Neurodegeneration
  • Computational anatomy

Background:

  • Early Alzheimer's disease (AD) is linked to medial temporal lobe (MTL) volume reductions.
  • Manual segmentation protocols (e.g., Olsen-Amaral-Palombo) are time-consuming.
  • Cognitive status (Montreal Cognitive Assessment scores) correlates with MTL atrophy in healthy older adults.

Purpose of the Study:

  • To evaluate the utility of Automatic Segmentation of Hippocampal Subfields (ASHS) for detecting volumetric differences in MTL subregions.
  • To compare an ASHS atlas trained on the OAP protocol (ASHS-OAP) with manual segmentation and another ASHS atlas (ASHS-PMC).

Main Methods:

  • Trained ASHS on the OAP protocol to create the ASHS-OAP atlas.
  • Compared volumetric measures from ASHS-OAP and ASHS-PMC with manual segmentation.
  • Analyzed volumetric differences in MTL subregions in healthy older adults with varying cognitive status (MoCA scores).

Main Results:

  • ASHS-OAP replicated manual segmentation findings for anterolateral entorhinal cortex and perirhinal cortex.
  • Both ASHS-OAP and ASHS-PMC detected early neurodegeneration signs in CA2/CA3/DG.
  • ASHS-OAP and ASHS-PMC yielded different volumes for most regions but identified similar trends in neurodegeneration.

Conclusions:

  • Automated segmentation using ASHS-OAP is a viable alternative to manual methods for detecting cognitive status-related volumetric differences in MTL.
  • Further development is needed for a unified and harmonized MTL segmentation atlas.
  • Automated methods show potential for efficient early detection of neurodegenerative changes.