Automatic segmentation of deep grey nuclei using a high‐resolution 7T magnetic resonance imaging atlas—Quantification of T1 values in healthy volunteers.
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| Title: | Automatic segmentation of deep grey nuclei using a high‐resolution 7T magnetic resonance imaging atlas—Quantification of T1 values in healthy volunteers. |
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| Authors: | Brun, Gilles (AUTHOR), Testud, Benoit (AUTHOR), Girard, Olivier M. (AUTHOR), Lehmann, Pierre (AUTHOR), de Rochefort, Ludovic (AUTHOR), Besson, Pierre (AUTHOR), Massire, Aurélien (AUTHOR), Ridley, Ben (AUTHOR), Girard, Nadine (AUTHOR), Guye, Maxime (AUTHOR), Ranjeva, Jean‐Philippe (AUTHOR), Le Troter, Arnaud (AUTHOR) |
| Source: | European Journal of Neuroscience. Jan2022, Vol. 55 Issue 2, p438-460. 23p. 5 Color Photographs, 1 Diagram, 6 Charts, 1 Graph. |
| Subjects: | Magnetic resonance imaging, Thalamic nuclei, Image registration, Volunteers, Neurological disorders |
| Abstract: | We present a new consensus atlas of deep grey nuclei obtained by shape‐based averaging of manual segmentation of two experienced neuroradiologists and optimized from 7T MP2RAGE images acquired at (.6 mm)3 in 60 healthy subjects. A group‐wise normalization method was used to build a high‐contrast and high‐resolution T1‐weighted brain template (.5 mm)3 using data from 30 out of the 60 controls. Delineation of 24 deep grey nuclei per hemisphere, including the claustrum and 12 thalamic nuclei, was then performed by two expert neuroradiologists and reviewed by a third neuroradiologist according to tissue contrast and external references based on the Morel atlas. Corresponding deep grey matter structures were also extracted from the Morel and CIT168 atlases. The data‐derived, Morel and CIT168 atlases were all applied at the individual level using non‐linear registration to fit the subject reference and to extract absolute mean quantitative T1 values derived from the 3D‐MP2RAGE volumes, after correction for residual B1+ biases. Three metrics (the Dice and the volumetric similarity coefficients and a novel Hausdorff distance) were used to estimate the inter‐rater agreement of manual MRI segmentation and inter‐atlas variability, and these metrics were measured to quantify biases due to image registration, and their impact on the measurements of the quantitative T1 values was highlighted. This represents a fully automated segmentation process permitting the extraction of unbiased normative T1 values in a population of young healthy controls as a reference for characterizing subtle structural alterations of deep grey nuclei relevant to a range of neurological diseases. [ABSTRACT FROM AUTHOR] |
| Copyright of European Journal of Neuroscience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 154885982 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Automatic segmentation of deep grey nuclei using a high‐resolution 7T magnetic resonance imaging atlas—Quantification of T1 values in healthy volunteers. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Brun%2C+Gilles%22">Brun, Gilles</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Testud%2C+Benoit%22">Testud, Benoit</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Girard%2C+Olivier+M%2E%22">Girard, Olivier M.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lehmann%2C+Pierre%22">Lehmann, Pierre</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22de+Rochefort%2C+Ludovic%22">de Rochefort, Ludovic</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Besson%2C+Pierre%22">Besson, Pierre</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Massire%2C+Aurélien%22">Massire, Aurélien</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ridley%2C+Ben%22">Ridley, Ben</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Girard%2C+Nadine%22">Girard, Nadine</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guye%2C+Maxime%22">Guye, Maxime</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ranjeva%2C+Jean‐Philippe%22">Ranjeva, Jean‐Philippe</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Le+Troter%2C+Arnaud%22">Le Troter, Arnaud</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Neuroscience%22">European Journal of Neuroscience</searchLink>. Jan2022, Vol. 55 Issue 2, p438-460. 23p. 5 Color Photographs, 1 Diagram, 6 Charts, 1 Graph. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Thalamic+nuclei%22">Thalamic nuclei</searchLink><br /><searchLink fieldCode="DE" term="%22Image+registration%22">Image registration</searchLink><br /><searchLink fieldCode="DE" term="%22Volunteers%22">Volunteers</searchLink><br /><searchLink fieldCode="DE" term="%22Neurological+disorders%22">Neurological disorders</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We present a new consensus atlas of deep grey nuclei obtained by shape‐based averaging of manual segmentation of two experienced neuroradiologists and optimized from 7T MP2RAGE images acquired at (.6 mm)3 in 60 healthy subjects. A group‐wise normalization method was used to build a high‐contrast and high‐resolution T1‐weighted brain template (.5 mm)3 using data from 30 out of the 60 controls. Delineation of 24 deep grey nuclei per hemisphere, including the claustrum and 12 thalamic nuclei, was then performed by two expert neuroradiologists and reviewed by a third neuroradiologist according to tissue contrast and external references based on the Morel atlas. Corresponding deep grey matter structures were also extracted from the Morel and CIT168 atlases. The data‐derived, Morel and CIT168 atlases were all applied at the individual level using non‐linear registration to fit the subject reference and to extract absolute mean quantitative T1 values derived from the 3D‐MP2RAGE volumes, after correction for residual B1+ biases. Three metrics (the Dice and the volumetric similarity coefficients and a novel Hausdorff distance) were used to estimate the inter‐rater agreement of manual MRI segmentation and inter‐atlas variability, and these metrics were measured to quantify biases due to image registration, and their impact on the measurements of the quantitative T1 values was highlighted. This represents a fully automated segmentation process permitting the extraction of unbiased normative T1 values in a population of young healthy controls as a reference for characterizing subtle structural alterations of deep grey nuclei relevant to a range of neurological diseases. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of European Journal of Neuroscience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/ejn.15575 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 438 Subjects: – SubjectFull: Magnetic resonance imaging Type: general – SubjectFull: Thalamic nuclei Type: general – SubjectFull: Image registration Type: general – SubjectFull: Volunteers Type: general – SubjectFull: Neurological disorders Type: general Titles: – TitleFull: Automatic segmentation of deep grey nuclei using a high‐resolution 7T magnetic resonance imaging atlas—Quantification of T1 values in healthy volunteers. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Brun, Gilles – PersonEntity: Name: NameFull: Testud, Benoit – PersonEntity: Name: NameFull: Girard, Olivier M. – PersonEntity: Name: NameFull: Lehmann, Pierre – PersonEntity: Name: NameFull: de Rochefort, Ludovic – PersonEntity: Name: NameFull: Besson, Pierre – PersonEntity: Name: NameFull: Massire, Aurélien – PersonEntity: Name: NameFull: Ridley, Ben – PersonEntity: Name: NameFull: Girard, Nadine – PersonEntity: Name: NameFull: Guye, Maxime – PersonEntity: Name: NameFull: Ranjeva, Jean‐Philippe – PersonEntity: Name: NameFull: Le Troter, Arnaud IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 01 Text: Jan2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 0953816X Numbering: – Type: volume Value: 55 – Type: issue Value: 2 Titles: – TitleFull: European Journal of Neuroscience Type: main |
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