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A collision prediction framework for noncoplanar radiotherapy planning and delivery
PURPOSE: Noncoplanar radiotherapy can provide significant dosimetric benefits. However, clinical implementation of such techniques is not fully realized, partially due to the absence of a collision prediction tool integrated into the clinical workflow. In this work, the feasibility of developing a c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484832/ https://www.ncbi.nlm.nih.gov/pubmed/32559004 http://dx.doi.org/10.1002/acm2.12920 |
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author | Islam, Naveed Kilian‐Meneghin, Josh deBoer, Steven Podgorsak, Matthew |
author_facet | Islam, Naveed Kilian‐Meneghin, Josh deBoer, Steven Podgorsak, Matthew |
author_sort | Islam, Naveed |
collection | PubMed |
description | PURPOSE: Noncoplanar radiotherapy can provide significant dosimetric benefits. However, clinical implementation of such techniques is not fully realized, partially due to the absence of a collision prediction tool integrated into the clinical workflow. In this work, the feasibility of developing a collision prediction system (CPS) suitable for integration into clinical practice has been investigated. METHODS: The CPS is based on a geometric model of the Linear Accelerator (Linac), and patient morphology acquired at the simulator using a combination of the planning CT scan and 3‐D vision camera (Microsoft, Kinect) data. Physical dimensions of Linac components were taken to construct a geometric model. The Linac components include the treatment couch, gantry, and imaging devices. The treatment couch coordinates were determined based on a correspondence among the CT couch top, Linac couch, and the treatment isocenter location. A collision is predicted based on dot products between vectors denoting points in Linac components and patient morphology. Collision test cases were simulated with the CPS and experimentally verified using ArcCheck and Rando phantoms to simulate a patient. RESULTS: For 111 collision test cases, the sensitivity and specificity of the CPS model were calculated to be 0.95 and 1.00, respectively. The CPS predicted collision states that left conservative margins, as designed, relative to actual collision locations. The average difference between the predicted and measured collision states was 2.3 cm for lateral couch movements. The predicted couch rotational position for a collision between the gantry and a patient analog differed from actual values on average by 3.8°. The magnitude of these differences is sufficient to account for interfractional patient positioning variations during treatment. CONCLUSION: The feasibility of developing a CPS using geometric models and standard vector algebra has been investigated. This study outlines a framework for potential clinical implementation of a CPS for noncoplanar radiotherapy. |
format | Online Article Text |
id | pubmed-7484832 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74848322020-09-17 A collision prediction framework for noncoplanar radiotherapy planning and delivery Islam, Naveed Kilian‐Meneghin, Josh deBoer, Steven Podgorsak, Matthew J Appl Clin Med Phys Radiation Oncology Physics PURPOSE: Noncoplanar radiotherapy can provide significant dosimetric benefits. However, clinical implementation of such techniques is not fully realized, partially due to the absence of a collision prediction tool integrated into the clinical workflow. In this work, the feasibility of developing a collision prediction system (CPS) suitable for integration into clinical practice has been investigated. METHODS: The CPS is based on a geometric model of the Linear Accelerator (Linac), and patient morphology acquired at the simulator using a combination of the planning CT scan and 3‐D vision camera (Microsoft, Kinect) data. Physical dimensions of Linac components were taken to construct a geometric model. The Linac components include the treatment couch, gantry, and imaging devices. The treatment couch coordinates were determined based on a correspondence among the CT couch top, Linac couch, and the treatment isocenter location. A collision is predicted based on dot products between vectors denoting points in Linac components and patient morphology. Collision test cases were simulated with the CPS and experimentally verified using ArcCheck and Rando phantoms to simulate a patient. RESULTS: For 111 collision test cases, the sensitivity and specificity of the CPS model were calculated to be 0.95 and 1.00, respectively. The CPS predicted collision states that left conservative margins, as designed, relative to actual collision locations. The average difference between the predicted and measured collision states was 2.3 cm for lateral couch movements. The predicted couch rotational position for a collision between the gantry and a patient analog differed from actual values on average by 3.8°. The magnitude of these differences is sufficient to account for interfractional patient positioning variations during treatment. CONCLUSION: The feasibility of developing a CPS using geometric models and standard vector algebra has been investigated. This study outlines a framework for potential clinical implementation of a CPS for noncoplanar radiotherapy. John Wiley and Sons Inc. 2020-06-19 /pmc/articles/PMC7484832/ /pubmed/32559004 http://dx.doi.org/10.1002/acm2.12920 Text en © 2020 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 Islam, Naveed Kilian‐Meneghin, Josh deBoer, Steven Podgorsak, Matthew A collision prediction framework for noncoplanar radiotherapy planning and delivery |
title | A collision prediction framework for noncoplanar radiotherapy planning and delivery |
title_full | A collision prediction framework for noncoplanar radiotherapy planning and delivery |
title_fullStr | A collision prediction framework for noncoplanar radiotherapy planning and delivery |
title_full_unstemmed | A collision prediction framework for noncoplanar radiotherapy planning and delivery |
title_short | A collision prediction framework for noncoplanar radiotherapy planning and delivery |
title_sort | collision prediction framework for noncoplanar radiotherapy planning and delivery |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484832/ https://www.ncbi.nlm.nih.gov/pubmed/32559004 http://dx.doi.org/10.1002/acm2.12920 |
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