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Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT

BACKGROUND: This study compared manually delineated gross tumour volume (GTV) and automatically generated biological tumour volume (BTV) based on fluoro-deoxy-glucose (FDG) positron emission tomography (PET)/CT to assess the robustness of predefined PET algorithms for radiotherapy (RT) planning in r...

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Autores principales: Niyazi, Maximilian, Landrock, Sonja, Elsner, Andreas, Manapov, Farkhad, Hacker, Marcus, Belka, Claus, Ganswindt, Ute
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3722117/
https://www.ncbi.nlm.nih.gov/pubmed/23848981
http://dx.doi.org/10.1186/1748-717X-8-180
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author Niyazi, Maximilian
Landrock, Sonja
Elsner, Andreas
Manapov, Farkhad
Hacker, Marcus
Belka, Claus
Ganswindt, Ute
author_facet Niyazi, Maximilian
Landrock, Sonja
Elsner, Andreas
Manapov, Farkhad
Hacker, Marcus
Belka, Claus
Ganswindt, Ute
author_sort Niyazi, Maximilian
collection PubMed
description BACKGROUND: This study compared manually delineated gross tumour volume (GTV) and automatically generated biological tumour volume (BTV) based on fluoro-deoxy-glucose (FDG) positron emission tomography (PET)/CT to assess the robustness of predefined PET algorithms for radiotherapy (RT) planning in routine clinical practice. METHODS: RT-planning data from 20 consecutive patients (lung- (40%), oesophageal- (25%), gynaecological- (25%) and colorectal (10%) cancer) who had undergone FDG-PET/CT planning between 08/2010 and 09/2011 were retrospectively analysed, five of them underwent neoadjuvant chemotherapy before radiotherapy. In addition to manual GTV contouring, automated segmentation algorithms were applied–among these 38%, 42%, 47% and 50% SUV(max) as well as the PERCIST total lesion glycolysis (TLG) algorithm. Different ratios were calculated to assess the overlap of GTV and BTV including the conformity index and the ratio GTV included within the BTV. RESULTS: Median age of the patients was 66 years and median tumour SUV(max) 9.2. Median size of the GTVs defined by the radiation oncologist was 43.7 ml. Median conformity indices were between 30.0–37.8%. The highest amount of BTV within GTV was seen with the 38% SUV(max) algorithm (49.0%), the lowest with 50% SUV(max) (36.0%). Best agreement was obtained for oesophageal cancer patients with a conformity index of 56.4% and BTV within GTV ratio of 71.1%. CONCLUSIONS: At present there is only low concordance between manually derived GTVs and automatically segmented FDG-PET/CT based BTVs indicating the need for further research in order to achieve higher volumetric conformity and therefore to get access to the full potential of FDG-PET/CT for optimization of radiotherapy planning.
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spelling pubmed-37221172013-07-25 Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT Niyazi, Maximilian Landrock, Sonja Elsner, Andreas Manapov, Farkhad Hacker, Marcus Belka, Claus Ganswindt, Ute Radiat Oncol Research BACKGROUND: This study compared manually delineated gross tumour volume (GTV) and automatically generated biological tumour volume (BTV) based on fluoro-deoxy-glucose (FDG) positron emission tomography (PET)/CT to assess the robustness of predefined PET algorithms for radiotherapy (RT) planning in routine clinical practice. METHODS: RT-planning data from 20 consecutive patients (lung- (40%), oesophageal- (25%), gynaecological- (25%) and colorectal (10%) cancer) who had undergone FDG-PET/CT planning between 08/2010 and 09/2011 were retrospectively analysed, five of them underwent neoadjuvant chemotherapy before radiotherapy. In addition to manual GTV contouring, automated segmentation algorithms were applied–among these 38%, 42%, 47% and 50% SUV(max) as well as the PERCIST total lesion glycolysis (TLG) algorithm. Different ratios were calculated to assess the overlap of GTV and BTV including the conformity index and the ratio GTV included within the BTV. RESULTS: Median age of the patients was 66 years and median tumour SUV(max) 9.2. Median size of the GTVs defined by the radiation oncologist was 43.7 ml. Median conformity indices were between 30.0–37.8%. The highest amount of BTV within GTV was seen with the 38% SUV(max) algorithm (49.0%), the lowest with 50% SUV(max) (36.0%). Best agreement was obtained for oesophageal cancer patients with a conformity index of 56.4% and BTV within GTV ratio of 71.1%. CONCLUSIONS: At present there is only low concordance between manually derived GTVs and automatically segmented FDG-PET/CT based BTVs indicating the need for further research in order to achieve higher volumetric conformity and therefore to get access to the full potential of FDG-PET/CT for optimization of radiotherapy planning. BioMed Central 2013-07-12 /pmc/articles/PMC3722117/ /pubmed/23848981 http://dx.doi.org/10.1186/1748-717X-8-180 Text en Copyright © 2013 Niyazi 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
Niyazi, Maximilian
Landrock, Sonja
Elsner, Andreas
Manapov, Farkhad
Hacker, Marcus
Belka, Claus
Ganswindt, Ute
Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT
title Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT
title_full Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT
title_fullStr Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT
title_full_unstemmed Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT
title_short Automated biological target volume delineation for radiotherapy treatment planning using FDG-PET/CT
title_sort automated biological target volume delineation for radiotherapy treatment planning using fdg-pet/ct
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3722117/
https://www.ncbi.nlm.nih.gov/pubmed/23848981
http://dx.doi.org/10.1186/1748-717X-8-180
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