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Review and recommendations on deformable image registration uncertainties for radiotherapy applications.
Nenoff, Lena; Amstutz, Florian; Murr, Martina; Archibald-Heeren, Ben; Fusella, Marco; Hussein, Mohammad; Lechner, Wolfgang; Zhang, Ye; Sharp, Greg; Vasquez Osorio, Eliana.
Afiliação
  • Nenoff L; Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, United States of America.
  • Amstutz F; Harvard Medical School, Boston, MA, United States of America.
  • Murr M; OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden Germany.
  • Archibald-Heeren B; Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology-OncoRay, Dresden, Germany.
  • Fusella M; Department of Physics, ETH Zurich, Switzerland.
  • Hussein M; Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland.
  • Lechner W; Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern, Switzerland.
  • Zhang Y; Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany.
  • Sharp G; Icon Cancer Centres, Sydney, NSW, Australia.
  • Vasquez Osorio E; Department of Radiation Oncology, Abano Terme Hospital, Italy.
Phys Med Biol ; 68(24)2023 Dec 13.
Article em En | MEDLINE | ID: mdl-37972540
ABSTRACT
Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Planejamento da Radioterapia Assistida por Computador Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Planejamento da Radioterapia Assistida por Computador Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article