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Patient positioning and immobilization procedures for hybrid MR-Linac systems

  • Francesco Cuccia*
  • , Filippo Alongi
  • , Claus Belka
  • , Luca Boldrini
  • , Juliane Hörner-Rieber
  • , Helen McNair
  • , Michele Rigo
  • , Maartje Schoenmakers
  • , Maximilian Niyazi
  • , Judith Slagter
  • , Claudio Votta
  • , Stefanie Corradini
  • *Corresponding author for this work
  • IRCCS Ospedale Sacro Cuore Don Calabria
  • University of Brescia
  • Ludwig Maximilian University of Munich
  • Fondazione Policlinico Universitario Agostino Gemelli IRCCS
  • Heidelberg University 
  • Royal Marsden NHS Foundation Trust
  • University Medical Center Utrecht
  • Amsterdam UMC

Research output: Contribution to journalReview articleAcademicpeer-review

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Abstract

Hybrid magnetic resonance (MR)-guided linear accelerators represent a new horizon in the field of radiation oncology. By harnessing the favorable combination of on-board MR-imaging with the possibility to daily recalculate the treatment plan based on real-time anatomy, the accuracy in target and organs-at-risk identification is expected to be improved, with the aim to provide the best tailored treatment. To date, two main MR-linac hybrid machines are available, Elekta Unity and Viewray MRIdian. Of note, compared to conventional linacs, these devices raise practical issues due to the positioning phase for the need to include the coil in the immobilization procedure and in order to perform the best reproducible positioning, also in light of the potentially longer treatment time. Given the relative novelty of this technology, there are few literature data regarding the procedures and the workflows for patient positioning and immobilization for MR-guided daily adaptive radiotherapy. In the present narrative review, we resume the currently available literature and provide an overview of the positioning and setup procedures for all the anatomical districts for hybrid MR-linac systems.
Original languageEnglish
Article number183
JournalRadiation oncology (London, England)
Volume16
Issue number1
DOIs
Publication statusPublished - 1 Dec 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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