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Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study
A vast majority of studies in the radiomics field are based on contours originating from radiotherapy planning. This kind of delineation (e.g. Gross Tumor Volume, GTV) is often larger than the true tumoral volume, sometimes including parts of other organs (e.g. trachea in Head and Neck, H&N stud...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881196/ https://www.ncbi.nlm.nih.gov/pubmed/35243026 http://dx.doi.org/10.1016/j.ctro.2022.01.003 |
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author | Fontaine, Pierre Andrearczyk, Vincent Oreiller, Valentin Abler, Daniel Castelli, Joel Acosta, Oscar De Crevoisier, Renaud Vallières, Martin Jreige, Mario Prior, John O. Depeursinge, Adrien |
author_facet | Fontaine, Pierre Andrearczyk, Vincent Oreiller, Valentin Abler, Daniel Castelli, Joel Acosta, Oscar De Crevoisier, Renaud Vallières, Martin Jreige, Mario Prior, John O. Depeursinge, Adrien |
author_sort | Fontaine, Pierre |
collection | PubMed |
description | A vast majority of studies in the radiomics field are based on contours originating from radiotherapy planning. This kind of delineation (e.g. Gross Tumor Volume, GTV) is often larger than the true tumoral volume, sometimes including parts of other organs (e.g. trachea in Head and Neck, H&N studies) and the impact of such over-segmentation was little investigated so far. In this paper, we propose to evaluate and compare the performance between models using two contour types: those from radiotherapy planning, and those specifically delineated for radiomics studies. For the latter, we modified the radiotherapy contours to fit the true tumoral volume. The two contour types were compared when predicting Progression-Free Survival (PFS) using Cox models based on radiomics features extracted from FluoroDeoxyGlucose-Positron Emission Tomography (FDG-PET) and CT images of 239 patients with oropharyngeal H&N cancer collected from five centers, the data from the 2020 HECKTOR challenge. Using Dedicated contours demonstrated better performance for predicting PFS, where Harell’s concordance indices of 0.61 and 0.69 were achieved for Radiotherapy and Dedicated contours, respectively. Using automatically Resegmented contours based on a fixed intensity range was associated with a C-index of 0.63. These results illustrate the importance of using clean dedicated contours that are close to the true tumoral volume in radiomics studies, even when tumor contours are already available from radiotherapy treatment planning |
format | Online Article Text |
id | pubmed-8881196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88811962022-03-02 Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study Fontaine, Pierre Andrearczyk, Vincent Oreiller, Valentin Abler, Daniel Castelli, Joel Acosta, Oscar De Crevoisier, Renaud Vallières, Martin Jreige, Mario Prior, John O. Depeursinge, Adrien Clin Transl Radiat Oncol Article A vast majority of studies in the radiomics field are based on contours originating from radiotherapy planning. This kind of delineation (e.g. Gross Tumor Volume, GTV) is often larger than the true tumoral volume, sometimes including parts of other organs (e.g. trachea in Head and Neck, H&N studies) and the impact of such over-segmentation was little investigated so far. In this paper, we propose to evaluate and compare the performance between models using two contour types: those from radiotherapy planning, and those specifically delineated for radiomics studies. For the latter, we modified the radiotherapy contours to fit the true tumoral volume. The two contour types were compared when predicting Progression-Free Survival (PFS) using Cox models based on radiomics features extracted from FluoroDeoxyGlucose-Positron Emission Tomography (FDG-PET) and CT images of 239 patients with oropharyngeal H&N cancer collected from five centers, the data from the 2020 HECKTOR challenge. Using Dedicated contours demonstrated better performance for predicting PFS, where Harell’s concordance indices of 0.61 and 0.69 were achieved for Radiotherapy and Dedicated contours, respectively. Using automatically Resegmented contours based on a fixed intensity range was associated with a C-index of 0.63. These results illustrate the importance of using clean dedicated contours that are close to the true tumoral volume in radiomics studies, even when tumor contours are already available from radiotherapy treatment planning Elsevier 2022-02-01 /pmc/articles/PMC8881196/ /pubmed/35243026 http://dx.doi.org/10.1016/j.ctro.2022.01.003 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Fontaine, Pierre Andrearczyk, Vincent Oreiller, Valentin Abler, Daniel Castelli, Joel Acosta, Oscar De Crevoisier, Renaud Vallières, Martin Jreige, Mario Prior, John O. Depeursinge, Adrien Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study |
title | Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study |
title_full | Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study |
title_fullStr | Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study |
title_full_unstemmed | Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study |
title_short | Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study |
title_sort | cleaning radiotherapy contours for radiomics studies, is it worth it? a head and neck cancer study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881196/ https://www.ncbi.nlm.nih.gov/pubmed/35243026 http://dx.doi.org/10.1016/j.ctro.2022.01.003 |
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