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Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution

INTRODUCTION: Aimed to develop a simple and robust volumetric modulated arc radiotherapy (VMAT) solution for comprehensive lymph node (CLN) breast cancer without increase in low‐dose wash. METHODS: Forty CLN‐breast patient data sets were utilised to develop a knowledge‐based planning (KBP) VMAT mode...

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Autores principales: Stanton, Cameron, Bell, Linda J., Le, Andrew, Griffiths, Brooke, Wu, Kenny, Adams, Jessica, Ambrose, Leigh, Andree‐Evarts, Denise, Porter, Brian, Bromley, Regina, van Gysen, Kirsten, Morgia, Marita, Lamoury, Gillian, Eade, Thomas, Booth, Jeremy T., Carroll, Susan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892431/
https://www.ncbi.nlm.nih.gov/pubmed/34387031
http://dx.doi.org/10.1002/jmrs.534
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author Stanton, Cameron
Bell, Linda J.
Le, Andrew
Griffiths, Brooke
Wu, Kenny
Adams, Jessica
Ambrose, Leigh
Andree‐Evarts, Denise
Porter, Brian
Bromley, Regina
van Gysen, Kirsten
Morgia, Marita
Lamoury, Gillian
Eade, Thomas
Booth, Jeremy T.
Carroll, Susan
author_facet Stanton, Cameron
Bell, Linda J.
Le, Andrew
Griffiths, Brooke
Wu, Kenny
Adams, Jessica
Ambrose, Leigh
Andree‐Evarts, Denise
Porter, Brian
Bromley, Regina
van Gysen, Kirsten
Morgia, Marita
Lamoury, Gillian
Eade, Thomas
Booth, Jeremy T.
Carroll, Susan
author_sort Stanton, Cameron
collection PubMed
description INTRODUCTION: Aimed to develop a simple and robust volumetric modulated arc radiotherapy (VMAT) solution for comprehensive lymph node (CLN) breast cancer without increase in low‐dose wash. METHODS: Forty CLN‐breast patient data sets were utilised to develop a knowledge‐based planning (KBP) VMAT model, which limits low‐dose wash using iterative learning and base‐tangential methods as benchmark. Another twenty data sets were employed to validate the model comparing KBP‐generated ipsilateral VMAT (ipsi‐VMAT) plans against the benchmarked hybrid (h)‐VMAT (departmental standard) and bowtie‐VMAT (published best practice) methods. Planning target volume (PTV), conformity/homogeneity index (CI/HI), organ‐at‐risk (OAR), remaining‐volume‐at‐risk (RVR) and blinded radiation oncologist (RO) plan preference were evaluated. RESULTS: Ipsi‐ and bowtie‐VMAT plans were dosimetrically equivalent, achieving greater nodal target coverage (P < 0.05) compared to h‐VMAT with minor reduction in breast coverage. CI was enhanced for a small reduction in breast HI with improved dose sparing to ipsilateral‐lung and humeral head (P < 0.05) at immaterial expense to spinal cord. Significantly, low‐dose wash to OARs and RVR were comparable between all plan types demonstrating a simple VMAT class solution robust to patient‐specific anatomic variation can be applied to CLN breast without need for complex beam modification (hybrid plans, avoidance sectors or other). This result was supported by blinded RO review. CONCLUSIONS: A simple and robust ipsilateral VMAT class solution for CLN breast generated using iterative KBP modelling can achieve clinically acceptable target coverage and OAR sparing without unwanted increase in low‐dose wash associated with increased second malignancy risk.
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spelling pubmed-88924312022-03-10 Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution Stanton, Cameron Bell, Linda J. Le, Andrew Griffiths, Brooke Wu, Kenny Adams, Jessica Ambrose, Leigh Andree‐Evarts, Denise Porter, Brian Bromley, Regina van Gysen, Kirsten Morgia, Marita Lamoury, Gillian Eade, Thomas Booth, Jeremy T. Carroll, Susan J Med Radiat Sci Original Articles INTRODUCTION: Aimed to develop a simple and robust volumetric modulated arc radiotherapy (VMAT) solution for comprehensive lymph node (CLN) breast cancer without increase in low‐dose wash. METHODS: Forty CLN‐breast patient data sets were utilised to develop a knowledge‐based planning (KBP) VMAT model, which limits low‐dose wash using iterative learning and base‐tangential methods as benchmark. Another twenty data sets were employed to validate the model comparing KBP‐generated ipsilateral VMAT (ipsi‐VMAT) plans against the benchmarked hybrid (h)‐VMAT (departmental standard) and bowtie‐VMAT (published best practice) methods. Planning target volume (PTV), conformity/homogeneity index (CI/HI), organ‐at‐risk (OAR), remaining‐volume‐at‐risk (RVR) and blinded radiation oncologist (RO) plan preference were evaluated. RESULTS: Ipsi‐ and bowtie‐VMAT plans were dosimetrically equivalent, achieving greater nodal target coverage (P < 0.05) compared to h‐VMAT with minor reduction in breast coverage. CI was enhanced for a small reduction in breast HI with improved dose sparing to ipsilateral‐lung and humeral head (P < 0.05) at immaterial expense to spinal cord. Significantly, low‐dose wash to OARs and RVR were comparable between all plan types demonstrating a simple VMAT class solution robust to patient‐specific anatomic variation can be applied to CLN breast without need for complex beam modification (hybrid plans, avoidance sectors or other). This result was supported by blinded RO review. CONCLUSIONS: A simple and robust ipsilateral VMAT class solution for CLN breast generated using iterative KBP modelling can achieve clinically acceptable target coverage and OAR sparing without unwanted increase in low‐dose wash associated with increased second malignancy risk. John Wiley and Sons Inc. 2021-08-12 2022-03 /pmc/articles/PMC8892431/ /pubmed/34387031 http://dx.doi.org/10.1002/jmrs.534 Text en © 2021 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology 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 Original Articles
Stanton, Cameron
Bell, Linda J.
Le, Andrew
Griffiths, Brooke
Wu, Kenny
Adams, Jessica
Ambrose, Leigh
Andree‐Evarts, Denise
Porter, Brian
Bromley, Regina
van Gysen, Kirsten
Morgia, Marita
Lamoury, Gillian
Eade, Thomas
Booth, Jeremy T.
Carroll, Susan
Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution
title Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution
title_full Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution
title_fullStr Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution
title_full_unstemmed Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution
title_short Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution
title_sort comprehensive nodal breast vmat: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8892431/
https://www.ncbi.nlm.nih.gov/pubmed/34387031
http://dx.doi.org/10.1002/jmrs.534
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