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Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software

PURPOSE: Increased use of Linac‐based stereotactic radiosurgery (SRS), which requires highly noncoplanar gantry trajectories, necessitates the development of efficient and accurate methods of collision detection during the treatment planning process. This work outlines the development and clinical i...

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Autores principales: Mann, Thomas D., Ploquin, Nicolas P., Gill, William R., Thind, Kundan S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6753734/
https://www.ncbi.nlm.nih.gov/pubmed/31282083
http://dx.doi.org/10.1002/acm2.12673
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author Mann, Thomas D.
Ploquin, Nicolas P.
Gill, William R.
Thind, Kundan S.
author_facet Mann, Thomas D.
Ploquin, Nicolas P.
Gill, William R.
Thind, Kundan S.
author_sort Mann, Thomas D.
collection PubMed
description PURPOSE: Increased use of Linac‐based stereotactic radiosurgery (SRS), which requires highly noncoplanar gantry trajectories, necessitates the development of efficient and accurate methods of collision detection during the treatment planning process. This work outlines the development and clinical implementation of a patient‐specific computed tomography (CT) contour‐based solution that utilizes Eclipse Scripting to ensure maximum integration with clinical workflow. METHODS: The collision detection application uses triangle mesh structures of the gantry and couch, in addition to the body contour of the patient taken during CT simulation, to virtually simulate patient treatments. Collision detection is performed using Binary Tree Hierarchy detection methods. Algorithm accuracy was first validated for simple cuboidal geometry using a calibration phantom and then extended to an anthropomorphic phantom simulation by comparing the measured minimum distance between structures to the predicted minimum distance for all allowable orientations. The collision space was tested at couch angles every 15° from 90 to 270 with the gantry incremented by 5° through the maximum trajectory. Receiver operating characteristic curve analysis was used to assess algorithm sensitivity and accuracy for predicting collision events. Following extensive validation, the application was implemented clinically for all SRS patients. RESULTS: The application was able to predict minimum distances between structures to within 3 cm. A safety margin of 1.5 cm was sufficient to achieve 100% sensitivity for all test cases. Accuracy obtained was 94.2% with the 5 cm clinical safety margin with 100% true positive collision detection. A total of 88 noncoplanar SRS patients have been currently tested using the application with one collision detected and no undetected collisions occurring. The average time for collision testing per patient was 2 min 58 s. CONCLUSIONS: A collision detection application utilizing patient CT contours was developed and successfully clinically implemented. This application allows collisions to be detected early during the planning process, avoiding patient delays and unnecessary resource utilization if detected during delivery.
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spelling pubmed-67537342019-09-23 Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software Mann, Thomas D. Ploquin, Nicolas P. Gill, William R. Thind, Kundan S. J Appl Clin Med Phys Radiation Oncology Physics PURPOSE: Increased use of Linac‐based stereotactic radiosurgery (SRS), which requires highly noncoplanar gantry trajectories, necessitates the development of efficient and accurate methods of collision detection during the treatment planning process. This work outlines the development and clinical implementation of a patient‐specific computed tomography (CT) contour‐based solution that utilizes Eclipse Scripting to ensure maximum integration with clinical workflow. METHODS: The collision detection application uses triangle mesh structures of the gantry and couch, in addition to the body contour of the patient taken during CT simulation, to virtually simulate patient treatments. Collision detection is performed using Binary Tree Hierarchy detection methods. Algorithm accuracy was first validated for simple cuboidal geometry using a calibration phantom and then extended to an anthropomorphic phantom simulation by comparing the measured minimum distance between structures to the predicted minimum distance for all allowable orientations. The collision space was tested at couch angles every 15° from 90 to 270 with the gantry incremented by 5° through the maximum trajectory. Receiver operating characteristic curve analysis was used to assess algorithm sensitivity and accuracy for predicting collision events. Following extensive validation, the application was implemented clinically for all SRS patients. RESULTS: The application was able to predict minimum distances between structures to within 3 cm. A safety margin of 1.5 cm was sufficient to achieve 100% sensitivity for all test cases. Accuracy obtained was 94.2% with the 5 cm clinical safety margin with 100% true positive collision detection. A total of 88 noncoplanar SRS patients have been currently tested using the application with one collision detected and no undetected collisions occurring. The average time for collision testing per patient was 2 min 58 s. CONCLUSIONS: A collision detection application utilizing patient CT contours was developed and successfully clinically implemented. This application allows collisions to be detected early during the planning process, avoiding patient delays and unnecessary resource utilization if detected during delivery. John Wiley and Sons Inc. 2019-07-07 /pmc/articles/PMC6753734/ /pubmed/31282083 http://dx.doi.org/10.1002/acm2.12673 Text en © 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Radiation Oncology Physics
Mann, Thomas D.
Ploquin, Nicolas P.
Gill, William R.
Thind, Kundan S.
Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software
title Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software
title_full Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software
title_fullStr Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software
title_full_unstemmed Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software
title_short Development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software
title_sort development and clinical implementation of eclipse scripting‐based automated patient‐specific collision avoidance software
topic Radiation Oncology Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6753734/
https://www.ncbi.nlm.nih.gov/pubmed/31282083
http://dx.doi.org/10.1002/acm2.12673
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