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Published VersionCC BY-NC-ND V4.0, Open Access
Journal article
Quantifiable brain atrophy synthesis for benchmarking of cortical thickness estimation methods
Medical Image Analysis, Vol.82, pp.1-16
2022
PMID: 36126404
Abstract
Cortical thickness (CTh) is routinely used to quantify grey matter atrophy as it is a significant biomarker in studying neurodegenerative and neurological conditions. Clinical studies commonly employ one of several available CTh estimation software tools to estimate CTh from brain MRI scans. In recent years, machine learning-based methods emerged as a faster alternative to the main-stream CTh estimation methods (e.g. FreeSurfer). Evaluation and comparison of CTh estimation methods often include various metrics and downstream tasks, but none fully covers the sensitivity to sub-voxel atrophy characteristic of neurodegeneration. In addition, current evaluation methods do not provide a framework for the intra-method region-wise evaluation of CTh estimation methods. Therefore, we propose a method for brain MRI synthesis capable of generating a range of sub-voxel atrophy levels (global and local) with quantifiable changes from the baseline scan. We further create a synthetic test set and evaluate four different CTh estimation methods: FreeSurfer (cross-sectional), FreeSurfer (longitudinal), DL+DiReCT and HerstonNet. DL+DiReCT showed superior sensitivity to sub-voxel atrophy over other methods in our testing framework. The obtained results indicate that our synthetic test set is suitable for benchmarking CTh estimation methods on both global and local scales as well as regional inter-and intra-method performance comparison.
Details
- Title
- Quantifiable brain atrophy synthesis for benchmarking of cortical thickness estimation methods
- Authors
- Filip Rusak (Corresponding Author) - CSIRO Health and BiosecurityRodrigo Santa Cruz (Author) - CSIRO Health and BiosecurityLéo Lebrat (Author) - CSIRO Health and BiosecurityOndrej Hlinka (Author) - The Australian eHealth Research Centre, CSIRO Health and Biosecurity, 296 Herston Road, Herston, 4029, AustraliaJurgen Fripp (Author) - CSIRO Health and BiosecurityElliot Smith (Author) - Maxwell PlusClinton Fookes (Author) - Queensland University of TechnologyAndrew P. Bradley (Author) - Queensland University of TechnologyPierrick Bourgeat (Author) - CSIRO Health and BiosecurityAlzheimer’s Disease Neuroimaging Initiative (Author)
- Publication details
- Medical Image Analysis, Vol.82, pp.1-16
- Publisher
- Elsevier BV
- Date published
- 2022
- DOI
- 10.1016/j.media.2022.102576
- ISSN
- 1361-8423; 1361-8415
- PMID
- 36126404
- Copyright note
- © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99704998202621
- Output Type
- Journal article
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- Domestic collaboration
- Web Of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Interdisciplinary Applications
- Engineering, Biomedical
- Radiology, Nuclear Medicine & Medical Imaging
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