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Synthetic Atrophy for Longitudinal Cortical Surface Analyses.

Kathleen E Larson1, Ipek Oguz2

  • 1Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States.

Frontiers in Neuroimaging
|August 9, 2023
PubMed
Summary

This study introduces a novel method to create synthetic brain atrophy for validating cortical thickness measurements. This technique generates a ground truth dataset, improving accuracy assessment in longitudinal neuroimaging studies.

Keywords:
accuracy validationcortical segmentationcortical thicknessregistrationsynthetic atrophy

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Area of Science:

  • Neuroimaging
  • Computational Anatomy

Background:

  • Assessing accuracy in longitudinal cortical segmentation and thickness measurement is challenging due to the lack of ground truth.
  • Existing synthetic data methods lack robust mechanisms for measuring exact thickness changes in surface-based analyses.

Purpose of the Study:

  • To present a registration-based technique for inducing synthetic cortical atrophy.
  • To create a longitudinal ground truth dataset for validating surface-based accuracy.

Main Methods:

  • Developed a method to induce localized synthetic cortical atrophy (0.8-2.5 mm) based on regional thickness.
  • Calculated image deformation at 400% resolution to achieve sub-voxel atrophy, minimizing partial volume effects.

Main Results:

  • The method successfully generated synthetic cortical atrophy with sub-voxel resolution.
  • Cortical segmentations of synthetic atrophied images showed segmentation errors comparable to naturally atrophied brains.

Conclusions:

  • The presented technique provides a robust tool for validating surface-based cortical thickness measurement accuracy.
  • This method utilizes publicly available software and datasets, facilitating wider adoption.