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Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI

PURPOSE: Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. The current clinical practice is to measure the diameter of the tumour in its largest dimension. It has been shown that volumetric measurement is more accurate and mor...

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Autores principales: McGrath, Hari, Li, Peichao, Dorent, Reuben, Bradford, Robert, Saeed, Shakeel, Bisdas, Sotirios, Ourselin, Sebastien, Shapey, Jonathan, Vercauteren, Tom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7419453/
https://www.ncbi.nlm.nih.gov/pubmed/32676869
http://dx.doi.org/10.1007/s11548-020-02222-y
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author McGrath, Hari
Li, Peichao
Dorent, Reuben
Bradford, Robert
Saeed, Shakeel
Bisdas, Sotirios
Ourselin, Sebastien
Shapey, Jonathan
Vercauteren, Tom
author_facet McGrath, Hari
Li, Peichao
Dorent, Reuben
Bradford, Robert
Saeed, Shakeel
Bisdas, Sotirios
Ourselin, Sebastien
Shapey, Jonathan
Vercauteren, Tom
author_sort McGrath, Hari
collection PubMed
description PURPOSE: Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. The current clinical practice is to measure the diameter of the tumour in its largest dimension. It has been shown that volumetric measurement is more accurate and more reliable as a measure of VS size. The reference approach to achieve such volumetry is to manually segment the tumour, which is a time intensive task. We suggest that semi-automated segmentation may be a clinically applicable solution to this problem and that it could replace linear measurements as the clinical standard. METHODS: Using high-quality software available for academic purposes, we ran a comparative study of manual versus semi-automated segmentation of VS on MRI with 5 clinicians and scientists. We gathered both quantitative and qualitative data to compare the two approaches; including segmentation time, segmentation effort and segmentation accuracy. RESULTS: We found that the selected semi-automated segmentation approach is significantly faster (167 s vs 479 s, [Formula: see text] ), less temporally and physically demanding and has approximately equal performance when compared with manual segmentation, with some improvements in accuracy. There were some limitations, including algorithmic unpredictability and error, which produced more frustration and increased mental effort in comparison with manual segmentation. CONCLUSION: We suggest that semi-automated segmentation could be applied clinically for volumetric measurement of VS on MRI. In future, the generic software could be refined for use specifically for VS segmentation, thereby improving accuracy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11548-020-02222-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-74194532020-08-18 Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI McGrath, Hari Li, Peichao Dorent, Reuben Bradford, Robert Saeed, Shakeel Bisdas, Sotirios Ourselin, Sebastien Shapey, Jonathan Vercauteren, Tom Int J Comput Assist Radiol Surg Original Article PURPOSE: Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. The current clinical practice is to measure the diameter of the tumour in its largest dimension. It has been shown that volumetric measurement is more accurate and more reliable as a measure of VS size. The reference approach to achieve such volumetry is to manually segment the tumour, which is a time intensive task. We suggest that semi-automated segmentation may be a clinically applicable solution to this problem and that it could replace linear measurements as the clinical standard. METHODS: Using high-quality software available for academic purposes, we ran a comparative study of manual versus semi-automated segmentation of VS on MRI with 5 clinicians and scientists. We gathered both quantitative and qualitative data to compare the two approaches; including segmentation time, segmentation effort and segmentation accuracy. RESULTS: We found that the selected semi-automated segmentation approach is significantly faster (167 s vs 479 s, [Formula: see text] ), less temporally and physically demanding and has approximately equal performance when compared with manual segmentation, with some improvements in accuracy. There were some limitations, including algorithmic unpredictability and error, which produced more frustration and increased mental effort in comparison with manual segmentation. CONCLUSION: We suggest that semi-automated segmentation could be applied clinically for volumetric measurement of VS on MRI. In future, the generic software could be refined for use specifically for VS segmentation, thereby improving accuracy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11548-020-02222-y) contains supplementary material, which is available to authorized users. Springer International Publishing 2020-07-16 2020 /pmc/articles/PMC7419453/ /pubmed/32676869 http://dx.doi.org/10.1007/s11548-020-02222-y Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
McGrath, Hari
Li, Peichao
Dorent, Reuben
Bradford, Robert
Saeed, Shakeel
Bisdas, Sotirios
Ourselin, Sebastien
Shapey, Jonathan
Vercauteren, Tom
Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI
title Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI
title_full Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI
title_fullStr Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI
title_full_unstemmed Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI
title_short Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI
title_sort manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on mri
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7419453/
https://www.ncbi.nlm.nih.gov/pubmed/32676869
http://dx.doi.org/10.1007/s11548-020-02222-y
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