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A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy
BACKGROUND: Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utilit...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3405479/ https://www.ncbi.nlm.nih.gov/pubmed/22704464 http://dx.doi.org/10.1186/1748-717X-7-90 |
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author | Hardcastle, Nicholas Tomé, Wolfgang A Cannon, Donald M Brouwer, Charlotte L Wittendorp, Paul WH Dogan, Nesrin Guckenberger, Matthias Allaire, Stéphane Mallya, Yogish Kumar, Prashant Oechsner, Markus Richter, Anne Song, Shiyu Myers, Michael Polat, Bülent Bzdusek, Karl |
author_facet | Hardcastle, Nicholas Tomé, Wolfgang A Cannon, Donald M Brouwer, Charlotte L Wittendorp, Paul WH Dogan, Nesrin Guckenberger, Matthias Allaire, Stéphane Mallya, Yogish Kumar, Prashant Oechsner, Markus Richter, Anne Song, Shiyu Myers, Michael Polat, Bülent Bzdusek, Karl |
author_sort | Hardcastle, Nicholas |
collection | PubMed |
description | BACKGROUND: Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs. METHODS: Target (GTV) and organ-at-risk (OAR) ROIs were non-rigidly propagated from a planning CT scan to a per-treatment CT scan for 22 patients. Propagated ROIs were quantitatively compared with expert physician-drawn ROIs on the per-treatment scan using Dice scores and mean slicewise Hausdorff distances, and center of mass distances for GTVs. The propagated ROIs were qualitatively examined by experts and scored based on their clinical utility. RESULTS: Good agreement between the DIR-propagated ROIs and expert-drawn ROIs was observed based on the metrics used. 94% of all ROIs generated using DIR were scored as being clinically useful, requiring minimal or no edits. However, 27% (12/44) of the GTVs required major edits. CONCLUSION: DIR was successfully used on 22 patients to propagate target and OAR structures for ART with good anatomical agreement for OARs. It is recommended that propagated target structures be thoroughly reviewed by the treating physician. |
format | Online Article Text |
id | pubmed-3405479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34054792012-07-26 A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy Hardcastle, Nicholas Tomé, Wolfgang A Cannon, Donald M Brouwer, Charlotte L Wittendorp, Paul WH Dogan, Nesrin Guckenberger, Matthias Allaire, Stéphane Mallya, Yogish Kumar, Prashant Oechsner, Markus Richter, Anne Song, Shiyu Myers, Michael Polat, Bülent Bzdusek, Karl Radiat Oncol Research BACKGROUND: Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs. METHODS: Target (GTV) and organ-at-risk (OAR) ROIs were non-rigidly propagated from a planning CT scan to a per-treatment CT scan for 22 patients. Propagated ROIs were quantitatively compared with expert physician-drawn ROIs on the per-treatment scan using Dice scores and mean slicewise Hausdorff distances, and center of mass distances for GTVs. The propagated ROIs were qualitatively examined by experts and scored based on their clinical utility. RESULTS: Good agreement between the DIR-propagated ROIs and expert-drawn ROIs was observed based on the metrics used. 94% of all ROIs generated using DIR were scored as being clinically useful, requiring minimal or no edits. However, 27% (12/44) of the GTVs required major edits. CONCLUSION: DIR was successfully used on 22 patients to propagate target and OAR structures for ART with good anatomical agreement for OARs. It is recommended that propagated target structures be thoroughly reviewed by the treating physician. BioMed Central 2012-06-15 /pmc/articles/PMC3405479/ /pubmed/22704464 http://dx.doi.org/10.1186/1748-717X-7-90 Text en Copyright ©2012 Hardcastle et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Hardcastle, Nicholas Tomé, Wolfgang A Cannon, Donald M Brouwer, Charlotte L Wittendorp, Paul WH Dogan, Nesrin Guckenberger, Matthias Allaire, Stéphane Mallya, Yogish Kumar, Prashant Oechsner, Markus Richter, Anne Song, Shiyu Myers, Michael Polat, Bülent Bzdusek, Karl A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy |
title | A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy |
title_full | A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy |
title_fullStr | A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy |
title_full_unstemmed | A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy |
title_short | A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy |
title_sort | multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3405479/ https://www.ncbi.nlm.nih.gov/pubmed/22704464 http://dx.doi.org/10.1186/1748-717X-7-90 |
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