A spatio-temporal atlas of the developing fetal brain with spina bifida aperta

Lucas Fidon; Elizabeth Viola; Nada Mufti; Anna L David; Andrew Melbourne; Philippe Demaerel; Sébastien Ourselin; Tom Vercauteren; Jan Deprest; Michael Aertsen

doi:10.12688/openreseurope.13914.2

A spatio-temporal atlas of the developing fetal brain with spina bifida aperta

Lucas Fidon, Elizabeth Viola, Nada Mufti, Anna L David, Andrew Melbourne, Philippe Demaerel, Sébastien Ourselin, Tom Vercauteren, Jan Deprest, Michael Aertsen

School of Biomedical Engineering and Imaging Sciences
1Department of Hepatology, Imperial College London, London, UK. 2Institute of Liver Studies at King's College School of Medicine at King's College Hospital, London, UK. 3Institute of Human Health and Performance, University College London, London, UK. 4Department of Asthma Allergy and Lung Biology, King's College London, London, UK. 5Division of Critical Care Medicine, University of Alberta, Edmonton, Canada.
Univ London, Birkbeck University London, University College London, University of London Royal Veterinary College, University of London, St Georges University London, Imperial College London, Kings College London, Royal Holloway University London, Queen Mary University London, Div Populat Hlth Sci & Educ
Department of Neurology, University Hospitals Leuven, B-3000 Leuven, Belgium.

Research output: Contribution to journal › Article › peer-review

Abstract

Background: Spina bifida aperta (SBA) is a birth defect associated with severe anatomical changes in the developing fetal brain. Brain magnetic resonance imaging (MRI) atlases are popular tools for studying neuropathology in the brain anatomy, but previous fetal brain MRI atlases have focused on the normal fetal brain. We aimed to develop a spatio-temporal fetal brain MRI atlas for SBA. Methods: We developed a semi-automatic computational method to compute the first spatio-temporal fetal brain MRI atlas for SBA. We used 90 MRIs of fetuses with SBA with gestational ages ranging from 21 to 35 weeks. Isotropic and motion-free 3D reconstructed MRIs were obtained for all the examinations. We propose a protocol for the annotation of anatomical landmarks in brain 3D MRI of fetuses with SBA with the aim of making spatial alignment of abnormal fetal brain MRIs more robust. In addition, we propose a weighted generalized Procrustes method based on the anatomical landmarks for the initialization of the atlas. The proposed weighted generalized Procrustes can handle temporal regularization and missing annotations. After initialization, the atlas is refined iteratively using non-linear image registration based on the image intensity and the anatomical land-marks. A semi-automatic method is used to obtain a parcellation of our fetal brain atlas into eight tissue types: white matter, ventricular system, cerebellum, extra-axial cerebrospinal fluid, cortical gray matter, deep gray matter, brainstem, and corpus callosum. Results: An intra-rater variability analysis suggests that the seven anatomical land-marks are sufficiently reliable. We find that the proposed atlas outperforms a normal fetal brain atlas for the automatic segmentation of brain 3D MRI of fetuses with SBA. Conclusions: We make publicly available a spatio-temporal fetal brain MRI atlas for SBA, available here: https://doi.org/10.7303/syn25887675. This atlas can support future research on automatic segmentation methods for brain 3D MRI of fetuses with SBA.

Original language	English
Pages (from-to)	123
Journal	Open Research Europe
Volume	1
DOIs	https://doi.org/10.12688/openreseurope.13914.2
Publication status	Published - 2021

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10.12688/openreseurope.13914.2

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title = "A spatio-temporal atlas of the developing fetal brain with spina bifida aperta",

abstract = " Background: Spina bifida aperta (SBA) is a birth defect associated with severe anatomical changes in the developing fetal brain. Brain magnetic resonance imaging (MRI) atlases are popular tools for studying neuropathology in the brain anatomy, but previous fetal brain MRI atlases have focused on the normal fetal brain. We aimed to develop a spatio-temporal fetal brain MRI atlas for SBA. Methods: We developed a semi-automatic computational method to compute the first spatio-temporal fetal brain MRI atlas for SBA. We used 90 MRIs of fetuses with SBA with gestational ages ranging from 21 to 35 weeks. Isotropic and motion-free 3D reconstructed MRIs were obtained for all the examinations. We propose a protocol for the annotation of anatomical landmarks in brain 3D MRI of fetuses with SBA with the aim of making spatial alignment of abnormal fetal brain MRIs more robust. In addition, we propose a weighted generalized Procrustes method based on the anatomical landmarks for the initialization of the atlas. The proposed weighted generalized Procrustes can handle temporal regularization and missing annotations. After initialization, the atlas is refined iteratively using non-linear image registration based on the image intensity and the anatomical land-marks. A semi-automatic method is used to obtain a parcellation of our fetal brain atlas into eight tissue types: white matter, ventricular system, cerebellum, extra-axial cerebrospinal fluid, cortical gray matter, deep gray matter, brainstem, and corpus callosum. Results: An intra-rater variability analysis suggests that the seven anatomical land-marks are sufficiently reliable. We find that the proposed atlas outperforms a normal fetal brain atlas for the automatic segmentation of brain 3D MRI of fetuses with SBA. Conclusions: We make publicly available a spatio-temporal fetal brain MRI atlas for SBA, available here: https://doi.org/10.7303/syn25887675. This atlas can support future research on automatic segmentation methods for brain 3D MRI of fetuses with SBA. ",

author = "Lucas Fidon and Elizabeth Viola and Nada Mufti and David, {Anna L} and Andrew Melbourne and Philippe Demaerel and S{\'e}bastien Ourselin and Tom Vercauteren and Jan Deprest and Michael Aertsen",

note = "Copyright: {\textcopyright} 2022 Fidon L et al.",

year = "2021",

doi = "10.12688/openreseurope.13914.2",

language = "English",

volume = "1",

pages = "123",

journal = "Open Research Europe",

issn = "2732-5121",

publisher = "Taylor and Francis",

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TY - JOUR

T1 - A spatio-temporal atlas of the developing fetal brain with spina bifida aperta

AU - Fidon, Lucas

AU - Viola, Elizabeth

AU - Mufti, Nada

AU - David, Anna L

AU - Melbourne, Andrew

AU - Demaerel, Philippe

AU - Ourselin, Sébastien

AU - Vercauteren, Tom

AU - Deprest, Jan

AU - Aertsen, Michael

PY - 2021

Y1 - 2021

N2 - Background: Spina bifida aperta (SBA) is a birth defect associated with severe anatomical changes in the developing fetal brain. Brain magnetic resonance imaging (MRI) atlases are popular tools for studying neuropathology in the brain anatomy, but previous fetal brain MRI atlases have focused on the normal fetal brain. We aimed to develop a spatio-temporal fetal brain MRI atlas for SBA. Methods: We developed a semi-automatic computational method to compute the first spatio-temporal fetal brain MRI atlas for SBA. We used 90 MRIs of fetuses with SBA with gestational ages ranging from 21 to 35 weeks. Isotropic and motion-free 3D reconstructed MRIs were obtained for all the examinations. We propose a protocol for the annotation of anatomical landmarks in brain 3D MRI of fetuses with SBA with the aim of making spatial alignment of abnormal fetal brain MRIs more robust. In addition, we propose a weighted generalized Procrustes method based on the anatomical landmarks for the initialization of the atlas. The proposed weighted generalized Procrustes can handle temporal regularization and missing annotations. After initialization, the atlas is refined iteratively using non-linear image registration based on the image intensity and the anatomical land-marks. A semi-automatic method is used to obtain a parcellation of our fetal brain atlas into eight tissue types: white matter, ventricular system, cerebellum, extra-axial cerebrospinal fluid, cortical gray matter, deep gray matter, brainstem, and corpus callosum. Results: An intra-rater variability analysis suggests that the seven anatomical land-marks are sufficiently reliable. We find that the proposed atlas outperforms a normal fetal brain atlas for the automatic segmentation of brain 3D MRI of fetuses with SBA. Conclusions: We make publicly available a spatio-temporal fetal brain MRI atlas for SBA, available here: https://doi.org/10.7303/syn25887675. This atlas can support future research on automatic segmentation methods for brain 3D MRI of fetuses with SBA.

AB - Background: Spina bifida aperta (SBA) is a birth defect associated with severe anatomical changes in the developing fetal brain. Brain magnetic resonance imaging (MRI) atlases are popular tools for studying neuropathology in the brain anatomy, but previous fetal brain MRI atlases have focused on the normal fetal brain. We aimed to develop a spatio-temporal fetal brain MRI atlas for SBA. Methods: We developed a semi-automatic computational method to compute the first spatio-temporal fetal brain MRI atlas for SBA. We used 90 MRIs of fetuses with SBA with gestational ages ranging from 21 to 35 weeks. Isotropic and motion-free 3D reconstructed MRIs were obtained for all the examinations. We propose a protocol for the annotation of anatomical landmarks in brain 3D MRI of fetuses with SBA with the aim of making spatial alignment of abnormal fetal brain MRIs more robust. In addition, we propose a weighted generalized Procrustes method based on the anatomical landmarks for the initialization of the atlas. The proposed weighted generalized Procrustes can handle temporal regularization and missing annotations. After initialization, the atlas is refined iteratively using non-linear image registration based on the image intensity and the anatomical land-marks. A semi-automatic method is used to obtain a parcellation of our fetal brain atlas into eight tissue types: white matter, ventricular system, cerebellum, extra-axial cerebrospinal fluid, cortical gray matter, deep gray matter, brainstem, and corpus callosum. Results: An intra-rater variability analysis suggests that the seven anatomical land-marks are sufficiently reliable. We find that the proposed atlas outperforms a normal fetal brain atlas for the automatic segmentation of brain 3D MRI of fetuses with SBA. Conclusions: We make publicly available a spatio-temporal fetal brain MRI atlas for SBA, available here: https://doi.org/10.7303/syn25887675. This atlas can support future research on automatic segmentation methods for brain 3D MRI of fetuses with SBA.

U2 - 10.12688/openreseurope.13914.2

DO - 10.12688/openreseurope.13914.2

M3 - Article

C2 - 37645096

SN - 2732-5121

VL - 1

SP - 123

JO - Open Research Europe

JF - Open Research Europe

ER -

A spatio-temporal atlas of the developing fetal brain with spina bifida aperta

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