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Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application

BACKGROUND: Re-contouring of structures on consecutive planning computed tomography (CT) images for patients that exhibit anatomical changes is elaborate and may negatively impact the turn-around time if this is required for many patients. This study was therefore initiated to validate the accuracy...

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Autores principales: Ramadaan, Ihab S, Peick, Karsten, Hamilton, David A, Evans, Jamie, Iupati, Douglas, Nicholson, Anna, Greig, Lynne, Louwe, Robert J W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4465143/
https://www.ncbi.nlm.nih.gov/pubmed/25889772
http://dx.doi.org/10.1186/s13014-015-0372-1
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author Ramadaan, Ihab S
Peick, Karsten
Hamilton, David A
Evans, Jamie
Iupati, Douglas
Nicholson, Anna
Greig, Lynne
Louwe, Robert J W
author_facet Ramadaan, Ihab S
Peick, Karsten
Hamilton, David A
Evans, Jamie
Iupati, Douglas
Nicholson, Anna
Greig, Lynne
Louwe, Robert J W
author_sort Ramadaan, Ihab S
collection PubMed
description BACKGROUND: Re-contouring of structures on consecutive planning computed tomography (CT) images for patients that exhibit anatomical changes is elaborate and may negatively impact the turn-around time if this is required for many patients. This study was therefore initiated to validate the accuracy and usefulness of automatic contour propagation for head and neck cancer patients using SmartAdapt® which is the deformable image registration (DIR) application in Varian’s Eclipse™ treatment planning system. METHODS: CT images of eight head and neck cancer patients with multiple planning CTs were registered using SmartAdapt®. The contoured structures of target volumes and OARs of the primary planning CT were deformed accordingly and subsequently compared with a reference structure set being either: 1) a structure set independently contoured by the treating Radiation Oncologist (RO), or 2) the DIR-generated structure set after being reviewed and modified by the RO. RESULTS: Application of DIR offered a considerable time saving for ROs in delineation of structures on CTs that were acquired mid-treatment. Quantitative analysis showed that 84% of the volume of the DIR-generated structures overlapped with the independently re-contoured structures, while 94% of the volume overlapped with the DIR-generated structures after review by the RO. This apparent intra-observer variation was further investigated resulting in the identification of several causes. Qualitative analysis showed that 92% of the DIR-generated structures either need no or only minor modification during RO reviews. CONCLUSIONS: SmartAdapt is a powerful tool with sufficient accuracy that saves considerable time in re-contouring structures on re-CTs. However, careful review of the DIR-generated structures is mandatory, in particular in areas where tumour regression plays a role.
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spelling pubmed-44651432015-06-14 Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application Ramadaan, Ihab S Peick, Karsten Hamilton, David A Evans, Jamie Iupati, Douglas Nicholson, Anna Greig, Lynne Louwe, Robert J W Radiat Oncol Research BACKGROUND: Re-contouring of structures on consecutive planning computed tomography (CT) images for patients that exhibit anatomical changes is elaborate and may negatively impact the turn-around time if this is required for many patients. This study was therefore initiated to validate the accuracy and usefulness of automatic contour propagation for head and neck cancer patients using SmartAdapt® which is the deformable image registration (DIR) application in Varian’s Eclipse™ treatment planning system. METHODS: CT images of eight head and neck cancer patients with multiple planning CTs were registered using SmartAdapt®. The contoured structures of target volumes and OARs of the primary planning CT were deformed accordingly and subsequently compared with a reference structure set being either: 1) a structure set independently contoured by the treating Radiation Oncologist (RO), or 2) the DIR-generated structure set after being reviewed and modified by the RO. RESULTS: Application of DIR offered a considerable time saving for ROs in delineation of structures on CTs that were acquired mid-treatment. Quantitative analysis showed that 84% of the volume of the DIR-generated structures overlapped with the independently re-contoured structures, while 94% of the volume overlapped with the DIR-generated structures after review by the RO. This apparent intra-observer variation was further investigated resulting in the identification of several causes. Qualitative analysis showed that 92% of the DIR-generated structures either need no or only minor modification during RO reviews. CONCLUSIONS: SmartAdapt is a powerful tool with sufficient accuracy that saves considerable time in re-contouring structures on re-CTs. However, careful review of the DIR-generated structures is mandatory, in particular in areas where tumour regression plays a role. BioMed Central 2015-03-31 /pmc/articles/PMC4465143/ /pubmed/25889772 http://dx.doi.org/10.1186/s13014-015-0372-1 Text en © Ramadaan et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Ramadaan, Ihab S
Peick, Karsten
Hamilton, David A
Evans, Jamie
Iupati, Douglas
Nicholson, Anna
Greig, Lynne
Louwe, Robert J W
Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application
title Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application
title_full Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application
title_fullStr Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application
title_full_unstemmed Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application
title_short Validation of Varian’s SmartAdapt® deformable image registration algorithm for clinical application
title_sort validation of varian’s smartadapt® deformable image registration algorithm for clinical application
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4465143/
https://www.ncbi.nlm.nih.gov/pubmed/25889772
http://dx.doi.org/10.1186/s13014-015-0372-1
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