Results of 2023 survey on the use of synthetic computed tomography for magnetic resonance Imaging-only radiotherapy: Current status and future steps

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • M. Fusella - , Abano Terme Hospital (Autor:in)
  • E. Alvarez Andres - , OncoRay - Nationales Zentrum für Strahlenforschung in der Onkologie, Klinik und Poliklinik für Strahlentherapie und Radioonkologie, Universitätsklinikum Carl Gustav Carus Dresden (Autor:in)
  • F. Villegas - , Karolinska Institutet (Autor:in)
  • L. Milan - , Ente Ospedaliero Cantonale (EOC) (Autor:in)
  • T. M. Janssen - , Netherlands Cancer Institute (Autor:in)
  • R. Dal Bello - , Universität Zürich (Autor:in)
  • C. Garibaldi - , IRCCS Istituto Europeo di Oncologia - Milano (Autor:in)
  • L. Placidi - , Fondazione Policlinico Universitario Agostino Gemelli IRCCS (Autor:in)
  • D. Cusumano - , Mater Olbia Hospital (MOH) (Autor:in)

Abstract

Background and purpose: The emergence of synthetic CT (sCT) in MR-guided radiotherapy (MRgRT) represents a significant advancement, supporting MR-only workflows and online treatment adaptation. However, the lack of consensus guidelines has led to varied practices. This study reports results from a 2023 ESTRO survey aimed at defining current practices in sCT development and use. Materials and methods: An survey was distributed to ESTRO members, including 98 questions across four sections on sCT algorithm generation and usage. By June 2023, 100 centers participated. The survey revealed diverse clinical experiences and roles, with primary sCT use in the pelvis (60%), brain (15%), abdomen (11%), thorax (8%), and head-and-neck (6%). sCT was mostly used for conventional fractionation treatments (68%), photon SBRT (40%), and palliative cases (28%), with limited use in proton therapy (4%). Results: Conditional GANs and GANs were the most used neural network architectures, operating mainly on 1.5 T and 3 T MRI images. Less than half used paired images for training, and only 20% performed image selection. Key MR image quality parameters included magnetic field homogeneity and spatial integrity. Half of the respondents lacked a dedicated sCT-QA program, and many did not apply sanitychecks before calculation. Selection strategies included age, weight, and metal artifacts. A strong consensus (95%) emerged for vendor neutral guidelines. Conclusion: The survey highlights the need for expert-based, vendor-neutral guidelines to standardize sCT tools, metrics, and clinical protocols, ensuring effective sCT use in MR-guided radiotherapy.

Details

OriginalspracheEnglisch
Aufsatznummer100652
FachzeitschriftPhysics and imaging in radiation oncology
Jahrgang32
PublikationsstatusVeröffentlicht - Okt. 2024
Peer-Review-StatusJa

Schlagworte

Schlagwörter

  • Artificial intelligence, Clinical implementation, Deep learning, MR-only planning, MR-only radiotherapy, Survey, Synthetic CT