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Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow.
Meyer, P; Biston, M-C; Khamphan, C; Marghani, T; Mazurier, J; Bodez, V; Fezzani, L; Rigaud, P A; Sidorski, G; Simon, L; Robert, C.
Afiliação
  • Meyer P; Department of radiotherapy, Institut de Cancérologie Strasbourg Europe (ICANS), Strasbourg, France; ICUBE, CNRS UMR 7357, team IMAGES, Strasbourg, France. Electronic address: p.meyer@icans.eu.
  • Biston MC; Department of radiotherapy, Centre Léon Bérard (CLB), Lyon, France; CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, Villeurbanne, France.
  • Khamphan C; Department of medical physics, Institut du Cancer Avignon-Provence, Avignon, France.
  • Marghani T; Institut de radiothérapie Amethyst du Sud de l'Oise, Creil, France.
  • Mazurier J; Centre de radiothérapie Oncorad Garonne, Toulouse, France.
  • Bodez V; Department of medical physics, Institut du Cancer Avignon-Provence, Avignon, France.
  • Fezzani L; Institut de radiothérapie Amethyst du Sud de l'Oise, Creil, France.
  • Rigaud PA; Institut de radiothérapie Amethyst du Sud de l'Oise, Creil, France.
  • Sidorski G; Centre de radiothérapie Oncorad Garonne, Toulouse, France.
  • Simon L; Institut Claudius Regaud (ICR), Institut Universitaire du Cancer de Toulouse-Oncopole (IUCT-O), Toulouse, France; Centre de Recherches en Cancérologie de Toulouse (CRCT), Université de Toulouse, INSERM U1037, Toulouse, France.
  • Robert C; Université Paris-Saclay, Institut Gustave Roussy, INSERM, Radiothérapie Moléculaire et Innovation Thérapeutique, Villejuif, France; Department of Radiotherapy, Gustave Roussy, Villejuif, France.
Cancer Radiother ; 25(6-7): 617-622, 2021 Oct.
Article em En | MEDLINE | ID: mdl-34175222
Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topic in radiotherapy. Today, the first commercial automated treatment planning solutions are available and implemented in a growing number of clinical radiotherapy departments. It should be noted that these various commercial solutions are based on very different methods, implying a daily practice that varies from one center to another. It is likely that this change in planning practices is still in its infancy. Indeed, the rise of artificial intelligence methods, based in particular on deep learning, has recently revived research interest in this subject. The numerous articles currently being published announce a lasting and profound transformation of radiotherapy planning practices in the years to come. From this perspective, an evolution of initial training for clinical teams and the drafting of new quality assurance recommendations is desirable.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Planejamento da Radioterapia Assistida por Computador / Fluxo de Trabalho / Aprendizado Profundo Tipo de estudo: Etiology_studies / Guideline / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Planejamento da Radioterapia Assistida por Computador / Fluxo de Trabalho / Aprendizado Profundo Tipo de estudo: Etiology_studies / Guideline / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article