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Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer
PURPOSE: To validate, in the context of adaptive radiotherapy, three commercial software solutions for atlas-based segmentation. METHODS AND MATERIALS: Fifteen patients, five for each group, with cancer of the Head&Neck, pleura, and prostate were enrolled in the study. In addition to the treatme...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3493511/ https://www.ncbi.nlm.nih.gov/pubmed/22989046 http://dx.doi.org/10.1186/1748-717X-7-160 |
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author | La Macchia, Mariangela Fellin, Francesco Amichetti, Maurizio Cianchetti, Marco Gianolini, Stefano Paola, Vitali Lomax, Antony J Widesott, Lamberto |
author_facet | La Macchia, Mariangela Fellin, Francesco Amichetti, Maurizio Cianchetti, Marco Gianolini, Stefano Paola, Vitali Lomax, Antony J Widesott, Lamberto |
author_sort | La Macchia, Mariangela |
collection | PubMed |
description | PURPOSE: To validate, in the context of adaptive radiotherapy, three commercial software solutions for atlas-based segmentation. METHODS AND MATERIALS: Fifteen patients, five for each group, with cancer of the Head&Neck, pleura, and prostate were enrolled in the study. In addition to the treatment planning CT (pCT) images, one replanning CT (rCT) image set was acquired for each patient during the RT course. Three experienced physicians outlined on the pCT and rCT all the volumes of interest (VOIs). We used three software solutions (VelocityAI 2.6.2 (V), MIM 5.1.1 (M) by MIMVista and ABAS 2.0 (A) by CMS-Elekta) to generate the automatic contouring on the repeated CT. All the VOIs obtained with automatic contouring (AC) were successively corrected manually. We recorded the time needed for: 1) ex novo ROIs definition on rCT; 2) generation of AC by the three software solutions; 3) manual correction of AC. To compare the quality of the volumes obtained automatically by the software and manually corrected with those drawn from scratch on rCT, we used the following indexes: overlap coefficient (DICE), sensitivity, inclusiveness index, difference in volume, and displacement differences on three axes (x, y, z) from the isocenter. RESULTS: The time saved by the three software solutions for all the sites, compared to the manual contouring from scratch, is statistically significant and similar for all the three software solutions. The time saved for each site are as follows: about an hour for Head&Neck, about 40 minutes for prostate, and about 20 minutes for mesothelioma. The best DICE similarity coefficient index was obtained with the manual correction for: A (contours for prostate), A and M (contours for H&N), and M (contours for mesothelioma). CONCLUSIONS: From a clinical point of view, the automated contouring workflow was shown to be significantly shorter than the manual contouring process, even though manual correction of the VOIs is always needed. |
format | Online Article Text |
id | pubmed-3493511 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34935112012-11-09 Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer La Macchia, Mariangela Fellin, Francesco Amichetti, Maurizio Cianchetti, Marco Gianolini, Stefano Paola, Vitali Lomax, Antony J Widesott, Lamberto Radiat Oncol Research PURPOSE: To validate, in the context of adaptive radiotherapy, three commercial software solutions for atlas-based segmentation. METHODS AND MATERIALS: Fifteen patients, five for each group, with cancer of the Head&Neck, pleura, and prostate were enrolled in the study. In addition to the treatment planning CT (pCT) images, one replanning CT (rCT) image set was acquired for each patient during the RT course. Three experienced physicians outlined on the pCT and rCT all the volumes of interest (VOIs). We used three software solutions (VelocityAI 2.6.2 (V), MIM 5.1.1 (M) by MIMVista and ABAS 2.0 (A) by CMS-Elekta) to generate the automatic contouring on the repeated CT. All the VOIs obtained with automatic contouring (AC) were successively corrected manually. We recorded the time needed for: 1) ex novo ROIs definition on rCT; 2) generation of AC by the three software solutions; 3) manual correction of AC. To compare the quality of the volumes obtained automatically by the software and manually corrected with those drawn from scratch on rCT, we used the following indexes: overlap coefficient (DICE), sensitivity, inclusiveness index, difference in volume, and displacement differences on three axes (x, y, z) from the isocenter. RESULTS: The time saved by the three software solutions for all the sites, compared to the manual contouring from scratch, is statistically significant and similar for all the three software solutions. The time saved for each site are as follows: about an hour for Head&Neck, about 40 minutes for prostate, and about 20 minutes for mesothelioma. The best DICE similarity coefficient index was obtained with the manual correction for: A (contours for prostate), A and M (contours for H&N), and M (contours for mesothelioma). CONCLUSIONS: From a clinical point of view, the automated contouring workflow was shown to be significantly shorter than the manual contouring process, even though manual correction of the VOIs is always needed. BioMed Central 2012-09-18 /pmc/articles/PMC3493511/ /pubmed/22989046 http://dx.doi.org/10.1186/1748-717X-7-160 Text en Copyright ©2012 La Macchia 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 La Macchia, Mariangela Fellin, Francesco Amichetti, Maurizio Cianchetti, Marco Gianolini, Stefano Paola, Vitali Lomax, Antony J Widesott, Lamberto Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer |
title | Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer |
title_full | Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer |
title_fullStr | Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer |
title_full_unstemmed | Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer |
title_short | Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer |
title_sort | systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3493511/ https://www.ncbi.nlm.nih.gov/pubmed/22989046 http://dx.doi.org/10.1186/1748-717X-7-160 |
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