Prospective risk analysis of the online-adaptive artificial intelligence-driven workflow using the Ethos treatment system.

Journal: Zeitschrift fur medizinische Physik
Published Date: Dec 9, 2022

Abstract

PURPOSE: The recently introduced Varian Ethos system allows adjusting radiotherapy treatment plans to anatomical changes on a daily basis. The system uses artificial intelligence to speed up the process of creating adapted plans, comes with its own software solutions and requires a substantially different workflow. A detailed analysis of possible risks of the associated workflow is presented.

Authors

  • Sonja Wegener
    University of Wuerzburg, Department of Radiation Oncology, Wuerzburg, Germany. Electronic address: Wegener_S1@ukw.de.
  • Florian Exner
    University of Wuerzburg, Department of Radiation Oncology, Wuerzburg, Germany. Electronic address: Exner_F@ukw.de.
  • Stefan Weick
    University of Wuerzburg, Department of Radiation Oncology, Wuerzburg, Germany. Electronic address: Weick_S@ukw.de.
  • Silke Stark
    University of Wuerzburg, Department of Radiation Oncology, Wuerzburg, Germany. Electronic address: Stark_S@ukw.de.
  • Heike Hutzel
    University of Wuerzburg, Department of Radiation Oncology, Wuerzburg, Germany. Electronic address: Hutzel_H@ukw.de.
  • Paul Lutyj
    University of Wuerzburg, Department of Radiation Oncology, Wuerzburg, Germany. Electronic address: Lutyj_P@ukw.de.
  • Jörg Tamihardja
    University of Wuerzburg, Department of Radiation Oncology, Wuerzburg, Germany. Electronic address: Tamihardja_J@ukw.de.
  • Gary Razinskas
    University of Wuerzburg, Department of Radiation Oncology, Wuerzburg, Germany. Electronic address: Razinskas_G@ukw.de.

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