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Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region

BACKGROUND AND PURPOSE: Studies have demonstrated the potential of online adaptive radiotherapy (oART). However, routine use has been limited due to resource demanding solutions. This study reports on experiences with oART in the pelvic region using a novel cone-beam computed tomography (CBCT)-based...

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Autores principales: Sibolt, Patrik, Andersson, Lina M., Calmels, Lucie, Sjöström, David, Bjelkengren, Ulf, Geertsen, Poul, Behrens, Claus F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057957/
https://www.ncbi.nlm.nih.gov/pubmed/33898770
http://dx.doi.org/10.1016/j.phro.2020.12.004
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author Sibolt, Patrik
Andersson, Lina M.
Calmels, Lucie
Sjöström, David
Bjelkengren, Ulf
Geertsen, Poul
Behrens, Claus F.
author_facet Sibolt, Patrik
Andersson, Lina M.
Calmels, Lucie
Sjöström, David
Bjelkengren, Ulf
Geertsen, Poul
Behrens, Claus F.
author_sort Sibolt, Patrik
collection PubMed
description BACKGROUND AND PURPOSE: Studies have demonstrated the potential of online adaptive radiotherapy (oART). However, routine use has been limited due to resource demanding solutions. This study reports on experiences with oART in the pelvic region using a novel cone-beam computed tomography (CBCT)-based, artificial intelligence (AI)-driven solution. MATERIAL AND METHODS: Automated pre-treatment planning for thirty-nine pelvic cases (bladder, rectum, anal, and prostate), and one hundred oART simulations were conducted in a pre-clinical release of Ethos (Varian Medical Systems, Palo Alto, CA). Plan quality, AI-segmentation accuracy, oART feasibility and an integrated calculation-based quality assurance solution were evaluated. Experiences from the first five clinical oART patients (three bladder, one rectum and one sarcoma) are reported. RESULTS: Auto-generated pre-treatment plans demonstrated similar planning target volume (PTV) coverage and organs at risk doses, compared to institution reference. More than 75% of AI-segmentations during simulated oART required none or minor editing and the adapted plan was superior in 88% of cases. Limitations in AI-segmentation correlated to cases where AI model training was lacking. The five first treated patients complied well with the median adaptive procedure duration of 17.6 min (from CBCT acceptance to treatment delivery start). The treated bladder patients demonstrated a 42% median primary PTV reduction, indicating a 24%-30% reduction in V(45Gy) to the bowel cavity, compared to non-ART. CONCLUSIONS: A novel commercial oART solution was demonstrated feasible for various pelvic sites. Clinically acceptable AI-segmentation and auto-planning enabled adaptation within reasonable timeslots. Possibilities for reduced PTVs observed for bladder cancer indicated potential for toxicity reductions.
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spelling pubmed-80579572021-04-23 Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region Sibolt, Patrik Andersson, Lina M. Calmels, Lucie Sjöström, David Bjelkengren, Ulf Geertsen, Poul Behrens, Claus F. Phys Imaging Radiat Oncol Original Research Article BACKGROUND AND PURPOSE: Studies have demonstrated the potential of online adaptive radiotherapy (oART). However, routine use has been limited due to resource demanding solutions. This study reports on experiences with oART in the pelvic region using a novel cone-beam computed tomography (CBCT)-based, artificial intelligence (AI)-driven solution. MATERIAL AND METHODS: Automated pre-treatment planning for thirty-nine pelvic cases (bladder, rectum, anal, and prostate), and one hundred oART simulations were conducted in a pre-clinical release of Ethos (Varian Medical Systems, Palo Alto, CA). Plan quality, AI-segmentation accuracy, oART feasibility and an integrated calculation-based quality assurance solution were evaluated. Experiences from the first five clinical oART patients (three bladder, one rectum and one sarcoma) are reported. RESULTS: Auto-generated pre-treatment plans demonstrated similar planning target volume (PTV) coverage and organs at risk doses, compared to institution reference. More than 75% of AI-segmentations during simulated oART required none or minor editing and the adapted plan was superior in 88% of cases. Limitations in AI-segmentation correlated to cases where AI model training was lacking. The five first treated patients complied well with the median adaptive procedure duration of 17.6 min (from CBCT acceptance to treatment delivery start). The treated bladder patients demonstrated a 42% median primary PTV reduction, indicating a 24%-30% reduction in V(45Gy) to the bowel cavity, compared to non-ART. CONCLUSIONS: A novel commercial oART solution was demonstrated feasible for various pelvic sites. Clinically acceptable AI-segmentation and auto-planning enabled adaptation within reasonable timeslots. Possibilities for reduced PTVs observed for bladder cancer indicated potential for toxicity reductions. Elsevier 2020-12-18 /pmc/articles/PMC8057957/ /pubmed/33898770 http://dx.doi.org/10.1016/j.phro.2020.12.004 Text en © 2020 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 Original Research Article
Sibolt, Patrik
Andersson, Lina M.
Calmels, Lucie
Sjöström, David
Bjelkengren, Ulf
Geertsen, Poul
Behrens, Claus F.
Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region
title Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region
title_full Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region
title_fullStr Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region
title_full_unstemmed Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region
title_short Clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region
title_sort clinical implementation of artificial intelligence-driven cone-beam computed tomography-guided online adaptive radiotherapy in the pelvic region
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057957/
https://www.ncbi.nlm.nih.gov/pubmed/33898770
http://dx.doi.org/10.1016/j.phro.2020.12.004
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