Segmentation of Periventricular White Matter in Neonatal Brain MRI: Analysis of Brain Maturation in Term and Preterm Cohorts

Alena U. Uus; Mohammad Usamah Ayub; Abi Gartner; Vanessa Kyriakopoulou; Maximilian Pietsch; Irina Grigorescu; Daan Christiaens; Jana Hutter; Lucilio Cordero Grande; Anthony Price; Dafnis Batalle; Serena Counsell; Joseph V. Hajnal; A. David Edwards; Mary A. Rutherford; Maria Deprez

doi:10.1007/978-3-031-17117-8_9

Segmentation of Periventricular White Matter in Neonatal Brain MRI: Analysis of Brain Maturation in Term and Preterm Cohorts

Alena U. Uus^*, Mohammad Usamah Ayub, Abi Gartner, Vanessa Kyriakopoulou, Maximilian Pietsch, Irina Grigorescu, Daan Christiaens, Jana Hutter, Lucilio Cordero Grande, Anthony Price, Dafnis Batalle, Serena Counsell, Joseph V. Hajnal, A. David Edwards, Mary A. Rutherford, Maria Deprez

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

2 Citations (Scopus)

Abstract

MRI is conventionally employed in neonatal brain diagnosis and research studies. However, the traditional segmentation protocols omit differentiation between heterogeneous white matter (WM) tissue zones that rapidly evolve and change during the early brain development. There is a reported correlations of characteristics of the transient WM compartments (including periventricular regions, subplate, etc.) with brain maturation [23, 26] and neurodevelopment scores [22]. However, there are no currently available standards for parcellation of these regions in MRI scans. Therefore, in this work, we propose the first deep learning solution for automated 3D segmentation of periventricular WM (PWM) regions that would be the first step towards tissue-specific WM analysis. The implemented segmentation method based on UNETR [13] was then used for assessment of the differences between term and preterm cohorts (200 subjects) from the developing Human Connectome Project (dHCP) (dHCP) project [1] in terms of the ROI-specific volumetry and microstructural diffusion MRI indices.

Original language	English
Title of host publication	Perinatal, Preterm and Paediatric Image Analysis - 7th International Workshop, PIPPI 2022, Held in Conjunction with MICCAI 2022, Proceedings
Editors	Roxane Licandro, Roxane Licandro, Andrew Melbourne, Jana Hutter, Esra Abaci Turk, Christopher Macgowan
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	94-104
Number of pages	11
ISBN (Print)	9783031171161
DOIs	https://doi.org/10.1007/978-3-031-17117-8_9
Publication status	Published - 22 Sept 2022
Event	7th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022 - Singapore, Singapore Duration: 18 Sept 2022 → 18 Sept 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13575 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022
Country/Territory	Singapore
City	Singapore
Period	18/09/2022 → 18/09/2022

Keywords

Automated segmentation
Brain maturation
Neonatal brain MRI
Periventricular white matter

Access to Document

10.1007/978-3-031-17117-8_9

Cite this

Uus, A. U., Ayub, M. U., Gartner, A., Kyriakopoulou, V., Pietsch, M., Grigorescu, I., Christiaens, D., Hutter, J., Grande, L. C., Price, A., Batalle, D., Counsell, S., Hajnal, J. V., Edwards, A. D., Rutherford, M. A., & Deprez, M. (2022). Segmentation of Periventricular White Matter in Neonatal Brain MRI: Analysis of Brain Maturation in Term and Preterm Cohorts. In R. Licandro, R. Licandro, A. Melbourne, J. Hutter, E. Abaci Turk, & C. Macgowan (Eds.), Perinatal, Preterm and Paediatric Image Analysis - 7th International Workshop, PIPPI 2022, Held in Conjunction with MICCAI 2022, Proceedings (pp. 94-104). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13575 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-17117-8_9

Uus, Alena U. ; Ayub, Mohammad Usamah ; Gartner, Abi et al. / Segmentation of Periventricular White Matter in Neonatal Brain MRI : Analysis of Brain Maturation in Term and Preterm Cohorts. Perinatal, Preterm and Paediatric Image Analysis - 7th International Workshop, PIPPI 2022, Held in Conjunction with MICCAI 2022, Proceedings. editor / Roxane Licandro ; Roxane Licandro ; Andrew Melbourne ; Jana Hutter ; Esra Abaci Turk ; Christopher Macgowan. Springer Science and Business Media Deutschland GmbH, 2022. pp. 94-104 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Segmentation of Periventricular White Matter in Neonatal Brain MRI: Analysis of Brain Maturation in Term and Preterm Cohorts",

abstract = "MRI is conventionally employed in neonatal brain diagnosis and research studies. However, the traditional segmentation protocols omit differentiation between heterogeneous white matter (WM) tissue zones that rapidly evolve and change during the early brain development. There is a reported correlations of characteristics of the transient WM compartments (including periventricular regions, subplate, etc.) with brain maturation [23, 26] and neurodevelopment scores [22]. However, there are no currently available standards for parcellation of these regions in MRI scans. Therefore, in this work, we propose the first deep learning solution for automated 3D segmentation of periventricular WM (PWM) regions that would be the first step towards tissue-specific WM analysis. The implemented segmentation method based on UNETR [13] was then used for assessment of the differences between term and preterm cohorts (200 subjects) from the developing Human Connectome Project (dHCP) (dHCP) project [1] in terms of the ROI-specific volumetry and microstructural diffusion MRI indices.",

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author = "Uus, {Alena U.} and Ayub, {Mohammad Usamah} and Abi Gartner and Vanessa Kyriakopoulou and Maximilian Pietsch and Irina Grigorescu and Daan Christiaens and Jana Hutter and Grande, {Lucilio Cordero} and Anthony Price and Dafnis Batalle and Serena Counsell and Hajnal, {Joseph V.} and Edwards, {A. David} and Rutherford, {Mary A.} and Maria Deprez",

note = "Funding Information: We thank everyone who was involved in acquisition and analysis of the datasets as a part of dHCP project. We thank all participants and their families. This work was supported by the Academy of Medical Sciences Springboard Award (SBF004\1040), the European Research Council under the European Union{\textquoteright}s Seventh Framework Programme [FP7/ 20072013]/ERC grant agreement no. 319456 dHCP project, the Wellcome/EPSRC Centre for Medical Engineering at King{\textquoteright}s College London [WT 203148/Z/16/Z)], the NIHR Clinical Research Facility (CRF) at Guy{\textquoteright}s and St Thomas{\textquoteright} and by the National Institute for Health Research Biomedical Research Centre based at Guy{\textquoteright}s and St Thomas{\textquoteright} NHS Foundation Trust and King{\textquoteright}s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Funding Information: This work was supported by the Academy of Medical Sciences Springboard Award (SBF004\1040), the European Research Council under the European Union{\textquoteright}s Seventh Framework Programme [FP7/ 20072013]/ERC grant agreement no. 319456 dHCP project, the Wellcome/EPSRC Centre for Medical Engineering at King{\textquoteright}s College London [WT 203148/Z/16/Z)], the NIHR Clinical Research Facility (CRF) at Guy{\textquoteright}s and St Thomas{\textquoteright} and by the National Institute for Health Research Biomedical Research Centre based at Guy{\textquoteright}s and St Thomas{\textquoteright} NHS Foundation Trust and King{\textquoteright}s College London. Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 7th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022 ; Conference date: 18-09-2022 Through 18-09-2022",

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editor = "Roxane Licandro and Roxane Licandro and Andrew Melbourne and Jana Hutter and {Abaci Turk}, Esra and Christopher Macgowan",

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Uus, AU, Ayub, MU, Gartner, A , Kyriakopoulou, V , Pietsch, M, Grigorescu, I, Christiaens, D , Hutter, J, Grande, LC, Price, A , Batalle, D , Counsell, S , Hajnal, JV , Edwards, AD , Rutherford, MA & Deprez, M 2022, Segmentation of Periventricular White Matter in Neonatal Brain MRI: Analysis of Brain Maturation in Term and Preterm Cohorts. in R Licandro, R Licandro, A Melbourne, J Hutter, E Abaci Turk & C Macgowan (eds), Perinatal, Preterm and Paediatric Image Analysis - 7th International Workshop, PIPPI 2022, Held in Conjunction with MICCAI 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13575 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 94-104, 7th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2022, held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, Singapore, Singapore, 18/09/2022. https://doi.org/10.1007/978-3-031-17117-8_9

Segmentation of Periventricular White Matter in Neonatal Brain MRI: Analysis of Brain Maturation in Term and Preterm Cohorts. / Uus, Alena U.; Ayub, Mohammad Usamah; Gartner, Abi et al.
Perinatal, Preterm and Paediatric Image Analysis - 7th International Workshop, PIPPI 2022, Held in Conjunction with MICCAI 2022, Proceedings. ed. / Roxane Licandro; Roxane Licandro; Andrew Melbourne; Jana Hutter; Esra Abaci Turk; Christopher Macgowan. Springer Science and Business Media Deutschland GmbH, 2022. p. 94-104 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13575 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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Uus AU, Ayub MU, Gartner A , Kyriakopoulou V , Pietsch M, Grigorescu I et al. Segmentation of Periventricular White Matter in Neonatal Brain MRI: Analysis of Brain Maturation in Term and Preterm Cohorts. In Licandro R, Licandro R, Melbourne A, Hutter J, Abaci Turk E, Macgowan C, editors, Perinatal, Preterm and Paediatric Image Analysis - 7th International Workshop, PIPPI 2022, Held in Conjunction with MICCAI 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 94-104. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-17117-8_9