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Characteristics of inverse gamma histograms.
Yu, Liting; Kairn, Tanya; Trapp, Jamie V; Crowe, Scott B.
  • Yu L; Royal Brisbane & Women's Hospital, Herston, 4029, Australia. Nancy.yu@health.qld.gov.au.
  • Kairn T; Queensland University of Technology, Brisbane, 4000, Australia. Nancy.yu@health.qld.gov.au.
  • Trapp JV; Royal Brisbane & Women's Hospital, Herston, 4029, Australia.
  • Crowe SB; Queensland University of Technology, Brisbane, 4000, Australia.
Phys Eng Sci Med ; 43(2): 659-664, 2020 Jun.
Article en En | MEDLINE | ID: mdl-32462506
ABSTRACT
This work explores the characteristics of the inverse gamma histogram and its potential use as part of the patient specific quality assurance (PSQA) program for volumetric modulated arc therapy (VMAT). ArcCheck measured dose files and TPS predicted dose files were imported and analysed using the in-house inverse gamma code developed in the Python package. Inverse gamma with fixed distance-to-agreement of 2 mm were calculated for 23 VMAT arcs. Dose difference histograms were plotted for six arbitrarily selected arcs with the 95th and 90th percentile values calculated. Dose difference histograms enabled visualisation of the dose difference distribution information. The 95th and 90th percentile values are equivalent to the dose difference criteria where the gamma pass rate is 95% and 90% respectively. These values can be used as a guide to assess plan acceptability, especially for plans that failed the initial gamma evaluation. The inverse gamma histograms are demonstrated to be a useful tool for plan evaluation in addition to the traditional gamma evaluation method. It contains dose difference or distance-to-agreement distribution information, which could be clinically useful for plan evaluation.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Rayos gamma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Rayos gamma Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2020 Tipo del documento: Article