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Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers

BACKGROUND: Since intensity-modulated radiation therapy (IMRT) has become popular for the treatment of gynecologic cancers, the contouring process has become more critical. This study evaluated the feasibility of atlas-based auto-segmentation (ABAS) for contouring in patients with endometrial and ce...

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Autores principales: Kim, Nalee, Chang, Jee Suk, Kim, Yong Bae, Kim, Jin Sung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218589/
https://www.ncbi.nlm.nih.gov/pubmed/32404123
http://dx.doi.org/10.1186/s13014-020-01562-y
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author Kim, Nalee
Chang, Jee Suk
Kim, Yong Bae
Kim, Jin Sung
author_facet Kim, Nalee
Chang, Jee Suk
Kim, Yong Bae
Kim, Jin Sung
author_sort Kim, Nalee
collection PubMed
description BACKGROUND: Since intensity-modulated radiation therapy (IMRT) has become popular for the treatment of gynecologic cancers, the contouring process has become more critical. This study evaluated the feasibility of atlas-based auto-segmentation (ABAS) for contouring in patients with endometrial and cervical cancers. METHODS: A total of 75 sets of planning CT images from 75 patients were collected. Contours for the pelvic nodal clinical target volume (CTV), femur, and bladder were carefully generated by two skilled radiation oncologists. Of 75 patients, 60 were randomly registered in three different atlas libraries for ABAS in groups of 20, 40, or 60. ABAS was conducted in 15 patients, followed by manual correction (ABAS(c)). The time required to generate all contours was recorded, and the accuracy of segmentation was assessed using Dice’s coefficient (DC) and the Hausdorff distance (HD) and compared to those of manually delineated contours. RESULTS: For ABAS-CTV, the best results were achieved with groups of 60 patients (DC, 0.79; HD, 19.7 mm) and the worst results with groups of 20 patients (DC, 0.75; p = 0.012; HD, 21.3 mm; p = 0.002). ABAS(c)-CTV performed better than ABAS-CTV in terms of both HD and DC (ABAS(c) [n = 60]; DC, 0.84; HD, 15.6 mm; all p < 0.017). ABAS required an average of 45.1 s, whereas ABAS(c) required 191.1 s; both methods required less time than the manual methods (p < 0.001). Both ABAS-Femur and simultaneous ABAS-Bilateral-femurs showed satisfactory performance, regardless of the atlas library used (DC > 0.9 and HD ≤10.0 mm), with significant time reduction compared to that needed for manual delineation (p < 0.001). However, ABAS-Bladder did not prove to be feasible, with inferior results regardless of library size (DC < 0.6 and HD > 40 mm). Furthermore, ABAS(c)-Bladder required a longer processing time than manual contouring to achieve the same accuracy. CONCLUSIONS: ABAS could help physicians to delineate the CTV and organs-at-risk (e.g., femurs) in IMRT planning considering its consistency, efficacy, and accuracy.
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spelling pubmed-72185892020-05-18 Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers Kim, Nalee Chang, Jee Suk Kim, Yong Bae Kim, Jin Sung Radiat Oncol Research BACKGROUND: Since intensity-modulated radiation therapy (IMRT) has become popular for the treatment of gynecologic cancers, the contouring process has become more critical. This study evaluated the feasibility of atlas-based auto-segmentation (ABAS) for contouring in patients with endometrial and cervical cancers. METHODS: A total of 75 sets of planning CT images from 75 patients were collected. Contours for the pelvic nodal clinical target volume (CTV), femur, and bladder were carefully generated by two skilled radiation oncologists. Of 75 patients, 60 were randomly registered in three different atlas libraries for ABAS in groups of 20, 40, or 60. ABAS was conducted in 15 patients, followed by manual correction (ABAS(c)). The time required to generate all contours was recorded, and the accuracy of segmentation was assessed using Dice’s coefficient (DC) and the Hausdorff distance (HD) and compared to those of manually delineated contours. RESULTS: For ABAS-CTV, the best results were achieved with groups of 60 patients (DC, 0.79; HD, 19.7 mm) and the worst results with groups of 20 patients (DC, 0.75; p = 0.012; HD, 21.3 mm; p = 0.002). ABAS(c)-CTV performed better than ABAS-CTV in terms of both HD and DC (ABAS(c) [n = 60]; DC, 0.84; HD, 15.6 mm; all p < 0.017). ABAS required an average of 45.1 s, whereas ABAS(c) required 191.1 s; both methods required less time than the manual methods (p < 0.001). Both ABAS-Femur and simultaneous ABAS-Bilateral-femurs showed satisfactory performance, regardless of the atlas library used (DC > 0.9 and HD ≤10.0 mm), with significant time reduction compared to that needed for manual delineation (p < 0.001). However, ABAS-Bladder did not prove to be feasible, with inferior results regardless of library size (DC < 0.6 and HD > 40 mm). Furthermore, ABAS(c)-Bladder required a longer processing time than manual contouring to achieve the same accuracy. CONCLUSIONS: ABAS could help physicians to delineate the CTV and organs-at-risk (e.g., femurs) in IMRT planning considering its consistency, efficacy, and accuracy. BioMed Central 2020-05-13 /pmc/articles/PMC7218589/ /pubmed/32404123 http://dx.doi.org/10.1186/s13014-020-01562-y Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Kim, Nalee
Chang, Jee Suk
Kim, Yong Bae
Kim, Jin Sung
Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers
title Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers
title_full Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers
title_fullStr Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers
title_full_unstemmed Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers
title_short Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers
title_sort atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218589/
https://www.ncbi.nlm.nih.gov/pubmed/32404123
http://dx.doi.org/10.1186/s13014-020-01562-y
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