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Converting Treatment Plans From Helical Tomotherapy to L-Shape Linac: Clinical Workflow and Dosimetric Evaluation.
Yuan, Zilong; Nair, Chithra Kumaran; Benedict, Stanley H; Valicenti, Richard K; Rao, Shyam; Fragoso, Ruben C; Wright, Cari; Qiu, Jianfeng; Rong, Yi.
Afiliação
  • Yuan Z; 1 Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA USA.
  • Nair CK; 2 Department of Radiology, Hubei Cancer Hospital, Hubei Key Laboratory of Medical Information Analysis & Tumor Diagnosis and Treatment, Wuhan, China.
  • Benedict SH; 1 Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA USA.
  • Valicenti RK; 1 Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA USA.
  • Rao S; 1 Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA USA.
  • Fragoso RC; 1 Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA USA.
  • Wright C; 1 Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA USA.
  • Qiu J; 1 Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA USA.
  • Rong Y; 3 Department of Radiology, Taishan Medical University, Tai'an, China.
Technol Cancer Res Treat ; 17: 1533033818785279, 2018 01 01.
Article em En | MEDLINE | ID: mdl-29986638
ABSTRACT
This work evaluated a commercial fallback planning workflow designed to provide cross-platform treatment planning and delivery. A total of 27 helical tomotherapy intensity-modulated radiotherapy plans covering 4 anatomical sites were selected, including 7 brain, 5 unilateral head and neck, 5 bilateral head and neck, 5 pelvis, and 5 prostate cases. All helical tomotherapy plans were converted to 7-field/9-field intensity-modulated radiotherapy and volumetric-modulated radiotherapy plans through fallback dose-mimicking algorithm using a 6-MV beam model. The planning target volume (PTV) coverage ( D1, D99, and homogeneity index) and organs at risk dose constraints were evaluated and compared. Overall, all 3 techniques resulted in relatively inferior target dose coverage compared to helical tomotherapy plans, with higher homogeneity index and maximum dose. The organs at risk dose ratio of fallback to helical tomotherapy plans covered a wide spectrum, from 0.87 to 1.11 on average for all sites, with fallback plans being superior for brain, pelvis, and prostate sites. The quality of fallback plans depends on the delivery technique, field numbers, and angles, as well as user selection of structures for organs at risk. In actual clinical scenario, fallback plans would typically be needed for 1 to 5 fractions of a treatment course in the event of machine breakdown. Our results suggested that <1% dose variance can be introduced in target coverage and/or organs at risk from fallback plans. The presented clinical workflow showed that the fallback plan generation typically takes 10 to 20 minutes per case. Fallback planning provides an expeditious and effective strategy for transferring patients cross platforms, and minimizing the untold risk of a patient missing treatment(s).
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Próstata / Planejamento da Radioterapia Assistida por Computador / Encéfalo / Radioterapia de Intensidade Modulada / Neoplasias Tipo de estudo: Etiology_studies Limite: Humans / Male Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Próstata / Planejamento da Radioterapia Assistida por Computador / Encéfalo / Radioterapia de Intensidade Modulada / Neoplasias Tipo de estudo: Etiology_studies Limite: Humans / Male Idioma: En Ano de publicação: 2018 Tipo de documento: Article