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3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas

Structural fetal body MRI provides true 3D information required for volumetry of fetal organs. However, current clinical and research practice primarily relies on manual slice-wise segmentation of raw T2-weighted stacks, which is time consuming, subject to inter- and intra-observer bias and affected...

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Autores principales: Uus, Alena U., Hall, Megan, Grigorescu, Irina, Zampieri, Carla Avena, Collado, Alexia Egloff, Payette, Kelly, Matthew, Jacqueline, Kyriakopoulou, Vanessa, Hajnal, Joseph V., Hutter, Jana, Rutherford, Mary A., Deprez, Maria, Story, Lisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312818/
https://www.ncbi.nlm.nih.gov/pubmed/37398121
http://dx.doi.org/10.1101/2023.05.31.23290751
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author Uus, Alena U.
Hall, Megan
Grigorescu, Irina
Zampieri, Carla Avena
Collado, Alexia Egloff
Payette, Kelly
Matthew, Jacqueline
Kyriakopoulou, Vanessa
Hajnal, Joseph V.
Hutter, Jana
Rutherford, Mary A.
Deprez, Maria
Story, Lisa
author_facet Uus, Alena U.
Hall, Megan
Grigorescu, Irina
Zampieri, Carla Avena
Collado, Alexia Egloff
Payette, Kelly
Matthew, Jacqueline
Kyriakopoulou, Vanessa
Hajnal, Joseph V.
Hutter, Jana
Rutherford, Mary A.
Deprez, Maria
Story, Lisa
author_sort Uus, Alena U.
collection PubMed
description Structural fetal body MRI provides true 3D information required for volumetry of fetal organs. However, current clinical and research practice primarily relies on manual slice-wise segmentation of raw T2-weighted stacks, which is time consuming, subject to inter- and intra-observer bias and affected by motion-corruption. Furthermore, there are no existing standard guidelines defining a universal approach to parcellation of fetal organs. This work produces the first parcellation protocol of the fetal body organs for motion-corrected 3D fetal body MRI. It includes 10 organ ROIs relevant to fetal quantitative volumetry studies. We also introduce the first population-averaged T2w MRI atlas of the fetal body. The protocol was used as a basis for training of a neural network for automated organ segmentation. It showed robust performance for different gestational ages. This solution minimises the need for manual editing and significantly reduces time. The general feasibility of the proposed pipeline was also assessed by analysis of organ growth charts created from automated parcellations of 91 normal control 3T MRI datasets that showed expected increase in volumetry during 22–38 weeks gestational age range. In addition, the results of comparison between 60 normal and 12 fetal growth restriction datasets revealed significant differences in organ volumes.
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spelling pubmed-103128182023-07-01 3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas Uus, Alena U. Hall, Megan Grigorescu, Irina Zampieri, Carla Avena Collado, Alexia Egloff Payette, Kelly Matthew, Jacqueline Kyriakopoulou, Vanessa Hajnal, Joseph V. Hutter, Jana Rutherford, Mary A. Deprez, Maria Story, Lisa medRxiv Article Structural fetal body MRI provides true 3D information required for volumetry of fetal organs. However, current clinical and research practice primarily relies on manual slice-wise segmentation of raw T2-weighted stacks, which is time consuming, subject to inter- and intra-observer bias and affected by motion-corruption. Furthermore, there are no existing standard guidelines defining a universal approach to parcellation of fetal organs. This work produces the first parcellation protocol of the fetal body organs for motion-corrected 3D fetal body MRI. It includes 10 organ ROIs relevant to fetal quantitative volumetry studies. We also introduce the first population-averaged T2w MRI atlas of the fetal body. The protocol was used as a basis for training of a neural network for automated organ segmentation. It showed robust performance for different gestational ages. This solution minimises the need for manual editing and significantly reduces time. The general feasibility of the proposed pipeline was also assessed by analysis of organ growth charts created from automated parcellations of 91 normal control 3T MRI datasets that showed expected increase in volumetry during 22–38 weeks gestational age range. In addition, the results of comparison between 60 normal and 12 fetal growth restriction datasets revealed significant differences in organ volumes. Cold Spring Harbor Laboratory 2023-09-18 /pmc/articles/PMC10312818/ /pubmed/37398121 http://dx.doi.org/10.1101/2023.05.31.23290751 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Uus, Alena U.
Hall, Megan
Grigorescu, Irina
Zampieri, Carla Avena
Collado, Alexia Egloff
Payette, Kelly
Matthew, Jacqueline
Kyriakopoulou, Vanessa
Hajnal, Joseph V.
Hutter, Jana
Rutherford, Mary A.
Deprez, Maria
Story, Lisa
3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas
title 3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas
title_full 3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas
title_fullStr 3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas
title_full_unstemmed 3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas
title_short 3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas
title_sort 3d t2w fetal body mri: automated organ volumetry, growth charts and population-averaged atlas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312818/
https://www.ncbi.nlm.nih.gov/pubmed/37398121
http://dx.doi.org/10.1101/2023.05.31.23290751
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