Systematic validation of an automated thalamic parcellation technique using anatomical data at 3T.
The thalamus is a brain region formed from functionally distinct nuclei, which contribute in important ways to various cognitive processes. Yet, much of the human neuroscience literature treats the thalamus as one homogeneous region, and consequently the unique contribution of specific nuclei to beh...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811922004591 |
| _version_ | 1818114533483347968 |
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| author | Brendan Williams Etienne Roesch Anastasia Christakou |
| author_facet | Brendan Williams Etienne Roesch Anastasia Christakou |
| author_sort | Brendan Williams |
| collection | DOAJ |
| description | The thalamus is a brain region formed from functionally distinct nuclei, which contribute in important ways to various cognitive processes. Yet, much of the human neuroscience literature treats the thalamus as one homogeneous region, and consequently the unique contribution of specific nuclei to behaviour remains under-appreciated. This is likely due in part to the technical challenge of dissociating nuclei using conventional structural imaging approaches. Yet, multiple algorithms exist in the neuroimaging literature for the automated segmentation of thalamic nuclei. One recent approach developed by Iglesias and colleagues (2018) generates segmentations by applying a probabilistic atlas to subject-space anatomical images using the FreeSurfer software. Here, we systematically validate the efficacy of this segmentation approach in delineating thalamic nuclei using Human Connectome Project data. We provide several metrics quantifying the quality of segmentations relative to the Morel stereotaxic atlas, a widely accepted anatomical atlas based on cyto- and myeloarchitecture. The automated segmentation approach generated boundaries between the anterior, lateral, posterior, and medial divisions of the thalamus. Segmentation efficacy, as measured by metrics of dissimilarity (Average Hausdorff Distance) and overlap (DICE coefficient) within groups was mixed. Regions were better delineated in anterior, lateral and medial thalamus than the posterior thalamus, however all the volumes for all segmented nuclei were significantly different to the corresponding region of the Morel atlas. These mixed results suggest users should exercise care when using this approach to study the structural or functional relevance of a given thalamic nucleus. |
| first_indexed | 2024-12-11T03:52:14Z |
| format | Article |
| id | doaj.art-9438b2ea30044ba98c84fe7d9c10e99c |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-11T03:52:14Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-9438b2ea30044ba98c84fe7d9c10e99c2022-12-22T01:21:52ZengElsevierNeuroImage1095-95722022-09-01258119340Systematic validation of an automated thalamic parcellation technique using anatomical data at 3T.Brendan Williams0Etienne Roesch1Anastasia Christakou2Centre for Integrative Neuroscience and Neurodynamics, University of Reading, Reading, Berkshire, RG6 6AL, UK; School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire, RG6 7BE, UK; Corresponding author: Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire, RG6 6ALCentre for Integrative Neuroscience and Neurodynamics, University of Reading, Reading, Berkshire, RG6 6AL, UK; School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire, RG6 7BE, UKCentre for Integrative Neuroscience and Neurodynamics, University of Reading, Reading, Berkshire, RG6 6AL, UK; School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire, RG6 7BE, UKThe thalamus is a brain region formed from functionally distinct nuclei, which contribute in important ways to various cognitive processes. Yet, much of the human neuroscience literature treats the thalamus as one homogeneous region, and consequently the unique contribution of specific nuclei to behaviour remains under-appreciated. This is likely due in part to the technical challenge of dissociating nuclei using conventional structural imaging approaches. Yet, multiple algorithms exist in the neuroimaging literature for the automated segmentation of thalamic nuclei. One recent approach developed by Iglesias and colleagues (2018) generates segmentations by applying a probabilistic atlas to subject-space anatomical images using the FreeSurfer software. Here, we systematically validate the efficacy of this segmentation approach in delineating thalamic nuclei using Human Connectome Project data. We provide several metrics quantifying the quality of segmentations relative to the Morel stereotaxic atlas, a widely accepted anatomical atlas based on cyto- and myeloarchitecture. The automated segmentation approach generated boundaries between the anterior, lateral, posterior, and medial divisions of the thalamus. Segmentation efficacy, as measured by metrics of dissimilarity (Average Hausdorff Distance) and overlap (DICE coefficient) within groups was mixed. Regions were better delineated in anterior, lateral and medial thalamus than the posterior thalamus, however all the volumes for all segmented nuclei were significantly different to the corresponding region of the Morel atlas. These mixed results suggest users should exercise care when using this approach to study the structural or functional relevance of a given thalamic nucleus.http://www.sciencedirect.com/science/article/pii/S1053811922004591ThalamusThalamic nucleiSegmentationMRIHuman Connectome Project |
| spellingShingle | Brendan Williams Etienne Roesch Anastasia Christakou Systematic validation of an automated thalamic parcellation technique using anatomical data at 3T. NeuroImage Thalamus Thalamic nuclei Segmentation MRI Human Connectome Project |
| title | Systematic validation of an automated thalamic parcellation technique using anatomical data at 3T. |
| title_full | Systematic validation of an automated thalamic parcellation technique using anatomical data at 3T. |
| title_fullStr | Systematic validation of an automated thalamic parcellation technique using anatomical data at 3T. |
| title_full_unstemmed | Systematic validation of an automated thalamic parcellation technique using anatomical data at 3T. |
| title_short | Systematic validation of an automated thalamic parcellation technique using anatomical data at 3T. |
| title_sort | systematic validation of an automated thalamic parcellation technique using anatomical data at 3t |
| topic | Thalamus Thalamic nuclei Segmentation MRI Human Connectome Project |
| url | http://www.sciencedirect.com/science/article/pii/S1053811922004591 |
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