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Development of a Monte Carlo based robustness calculation and evaluation tool

BACKGROUND: Evaluating plan robustness is a key step in radiotherapy. PURPOSE: To develop a flexible Monte Carlo (MC)‐based robustness calculation and evaluation tool to assess and quantify dosimetric robustness of intensity‐modulated radiotherapy (IMRT) treatment plans by exploring the impact of sy...

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Autores principales: Loebner, Hannes A., Volken, Werner, Mueller, Silvan, Bertholet, Jenny, Mackeprang, Paul‐Henry, Guyer, Gian, Aebersold, Daniel M., Stampanoni, Marco F. M., Manser, Peter, Fix, Michael K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9545707/
https://www.ncbi.nlm.nih.gov/pubmed/35451087
http://dx.doi.org/10.1002/mp.15683
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author Loebner, Hannes A.
Volken, Werner
Mueller, Silvan
Bertholet, Jenny
Mackeprang, Paul‐Henry
Guyer, Gian
Aebersold, Daniel M.
Stampanoni, Marco F. M.
Manser, Peter
Fix, Michael K.
author_facet Loebner, Hannes A.
Volken, Werner
Mueller, Silvan
Bertholet, Jenny
Mackeprang, Paul‐Henry
Guyer, Gian
Aebersold, Daniel M.
Stampanoni, Marco F. M.
Manser, Peter
Fix, Michael K.
author_sort Loebner, Hannes A.
collection PubMed
description BACKGROUND: Evaluating plan robustness is a key step in radiotherapy. PURPOSE: To develop a flexible Monte Carlo (MC)‐based robustness calculation and evaluation tool to assess and quantify dosimetric robustness of intensity‐modulated radiotherapy (IMRT) treatment plans by exploring the impact of systematic and random uncertainties resulting from patient setup, patient anatomy changes, and mechanical limitations of machine components. METHODS: The robustness tool consists of two parts: the first part includes automated MC dose calculation of multiple user‐defined uncertainty scenarios to populate a robustness space. An uncertainty scenario is defined by a certain combination of uncertainties in patient setup, rigid intrafraction motion and in mechanical steering of the following machine components: angles of gantry, collimator, table‐yaw, table‐pitch, table‐roll, translational positions of jaws, multileaf‐collimator (MLC) banks, and single MLC leaves. The Swiss Monte Carlo Plan (SMCP) is integrated in this tool to serve as the backbone for the MC dose calculations incorporating the uncertainties. The calculated dose distributions serve as input for the second part of the tool, handling the quantitative evaluation of the dosimetric impact of the uncertainties. A graphical user interface (GUI) is developed to simultaneously evaluate the uncertainty scenarios according to user‐specified conditions based on dose‐volume histogram (DVH) parameters, fast and exact gamma analysis, and dose differences. Additionally, a robustness index (RI) is introduced with the aim to simultaneously evaluate and condense dosimetric robustness against multiple uncertainties into one number. The RI is defined as the ratio of scenarios passing the conditions on the dose distributions. Weighting of the scenarios in the robustness space is possible to consider their likelihood of occurrence. The robustness tool is applied on IMRT, a volumetric modulated arc therapy (VMAT), a dynamic trajectory radiotherapy (DTRT), and a dynamic mixed beam radiotherapy (DYMBER) plan for a brain case to evaluate the robustness to uncertainties of gantry‐, table‐, collimator angle, MLC, and intrafraction motion. Additionally, the robustness of the IMRT, VMAT, and DTRT plan against patient setup uncertainties are compared. The robustness tool is validated by Delta4 measurements for scenarios including all uncertainty types available. RESULTS: The robustness tool performs simultaneous calculation of uncertainty scenarios, and the GUI enables their fast evaluation. For all evaluated plans and uncertainties, the planning target volume (PTV) margin prevented major clinical target volume (CTV) coverage deterioration (maximum observed standard deviation of [Formula: see text] was 1.3 Gy). OARs close to the PTV experienced larger dosimetric deviations (maximum observed standard deviation of [Formula: see text] was 14.5 Gy). Robustness comparison by RI evaluation against patient setup uncertainties revealed better dosimetric robustness of the VMAT and DTRT plans as compared to the IMRT plan. Delta4 validation measurements agreed with calculations by >96% gamma‐passing rate (3% global/2 mm). CONCLUSIONS: The robustness tool was successfully implemented. Calculation and evaluation of uncertainty scenarios with the robustness tool were demonstrated on a brain case. Effects of patient and machine‐specific uncertainties and the combination thereof on the dose distribution are evaluated in a user‐friendly GUI to quantitatively assess and compare treatment plans and their robustness.
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spelling pubmed-95457072022-10-14 Development of a Monte Carlo based robustness calculation and evaluation tool Loebner, Hannes A. Volken, Werner Mueller, Silvan Bertholet, Jenny Mackeprang, Paul‐Henry Guyer, Gian Aebersold, Daniel M. Stampanoni, Marco F. M. Manser, Peter Fix, Michael K. Med Phys COMPUTATIONAL AND EXPERIMENTAL DOSIMETRY BACKGROUND: Evaluating plan robustness is a key step in radiotherapy. PURPOSE: To develop a flexible Monte Carlo (MC)‐based robustness calculation and evaluation tool to assess and quantify dosimetric robustness of intensity‐modulated radiotherapy (IMRT) treatment plans by exploring the impact of systematic and random uncertainties resulting from patient setup, patient anatomy changes, and mechanical limitations of machine components. METHODS: The robustness tool consists of two parts: the first part includes automated MC dose calculation of multiple user‐defined uncertainty scenarios to populate a robustness space. An uncertainty scenario is defined by a certain combination of uncertainties in patient setup, rigid intrafraction motion and in mechanical steering of the following machine components: angles of gantry, collimator, table‐yaw, table‐pitch, table‐roll, translational positions of jaws, multileaf‐collimator (MLC) banks, and single MLC leaves. The Swiss Monte Carlo Plan (SMCP) is integrated in this tool to serve as the backbone for the MC dose calculations incorporating the uncertainties. The calculated dose distributions serve as input for the second part of the tool, handling the quantitative evaluation of the dosimetric impact of the uncertainties. A graphical user interface (GUI) is developed to simultaneously evaluate the uncertainty scenarios according to user‐specified conditions based on dose‐volume histogram (DVH) parameters, fast and exact gamma analysis, and dose differences. Additionally, a robustness index (RI) is introduced with the aim to simultaneously evaluate and condense dosimetric robustness against multiple uncertainties into one number. The RI is defined as the ratio of scenarios passing the conditions on the dose distributions. Weighting of the scenarios in the robustness space is possible to consider their likelihood of occurrence. The robustness tool is applied on IMRT, a volumetric modulated arc therapy (VMAT), a dynamic trajectory radiotherapy (DTRT), and a dynamic mixed beam radiotherapy (DYMBER) plan for a brain case to evaluate the robustness to uncertainties of gantry‐, table‐, collimator angle, MLC, and intrafraction motion. Additionally, the robustness of the IMRT, VMAT, and DTRT plan against patient setup uncertainties are compared. The robustness tool is validated by Delta4 measurements for scenarios including all uncertainty types available. RESULTS: The robustness tool performs simultaneous calculation of uncertainty scenarios, and the GUI enables their fast evaluation. For all evaluated plans and uncertainties, the planning target volume (PTV) margin prevented major clinical target volume (CTV) coverage deterioration (maximum observed standard deviation of [Formula: see text] was 1.3 Gy). OARs close to the PTV experienced larger dosimetric deviations (maximum observed standard deviation of [Formula: see text] was 14.5 Gy). Robustness comparison by RI evaluation against patient setup uncertainties revealed better dosimetric robustness of the VMAT and DTRT plans as compared to the IMRT plan. Delta4 validation measurements agreed with calculations by >96% gamma‐passing rate (3% global/2 mm). CONCLUSIONS: The robustness tool was successfully implemented. Calculation and evaluation of uncertainty scenarios with the robustness tool were demonstrated on a brain case. Effects of patient and machine‐specific uncertainties and the combination thereof on the dose distribution are evaluated in a user‐friendly GUI to quantitatively assess and compare treatment plans and their robustness. John Wiley and Sons Inc. 2022-05-04 2022-07 /pmc/articles/PMC9545707/ /pubmed/35451087 http://dx.doi.org/10.1002/mp.15683 Text en © 2022 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle COMPUTATIONAL AND EXPERIMENTAL DOSIMETRY
Loebner, Hannes A.
Volken, Werner
Mueller, Silvan
Bertholet, Jenny
Mackeprang, Paul‐Henry
Guyer, Gian
Aebersold, Daniel M.
Stampanoni, Marco F. M.
Manser, Peter
Fix, Michael K.
Development of a Monte Carlo based robustness calculation and evaluation tool
title Development of a Monte Carlo based robustness calculation and evaluation tool
title_full Development of a Monte Carlo based robustness calculation and evaluation tool
title_fullStr Development of a Monte Carlo based robustness calculation and evaluation tool
title_full_unstemmed Development of a Monte Carlo based robustness calculation and evaluation tool
title_short Development of a Monte Carlo based robustness calculation and evaluation tool
title_sort development of a monte carlo based robustness calculation and evaluation tool
topic COMPUTATIONAL AND EXPERIMENTAL DOSIMETRY
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9545707/
https://www.ncbi.nlm.nih.gov/pubmed/35451087
http://dx.doi.org/10.1002/mp.15683
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