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

Autor: Cameron Stanton, Linda J. Bell, Andrew Le, Brooke Griffiths, Kenny Wu, Jessica Adams, Leigh Ambrose, Denise Andree‐Evarts, Brian Porter, Regina Bromley, Kirsten vanGysen, Marita Morgia, Gillian Lamoury, Thomas Eade, Jeremy T. Booth, Susan Carroll
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of Medical Radiation Sciences, Vol 69, Iss 1, Pp 85-97 (2022)
Druh dokumentu: article
ISSN: 2051-3909
2051-3895
DOI: 10.1002/jmrs.534
Popis: Abstract 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
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