Evaluation of daily online contour adaptation by radiation therapists for prostate cancer treatment on an MRI-guided linear accelerator-Reference-Cited by-同舟云学术

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Evaluation of daily online contour adaptation by radiation therapists for prostate cancer treatment on an MRI-guided linear accelerator

Published:2021-03 Issue: Volume:27 Page:50-56
ISSN:2405-6308
Container-title:Clinical and Translational Radiation Oncology
language:en
Short-container-title:Clinical and Translational Radiation Oncology

Author:

Willigenburg Thomas,de Muinck Keizer Daan M.,Peters Max,Claes An,Lagendijk Jan J.W.,de Boer Hans C.J.,van der Voort van Zyp Jochem R.N.

Funder

ZonMw

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Oncology

Reference20 articles.

1. First patients treated with a 1.5 T MRI-Linac: clinical proof of concept of a high-precision, high-field MRI guided radiotherapy treatment;Raaymakers;Phys Med Biol,2017

2. Feasibility of stereotactic radiotherapy using a 1.5 T MR-linac: Multi-fraction treatment of pelvic lymph node oligometastases;Werensteijn-Honingh;Radiother Oncol,2019

3. The Magnetic Resonance Imaging–Linac System;Lagendijk;Semin Radiat Oncol,2014

4. Adaptive radiotherapy: The Elekta Unity MR-linac concept;Winkel;Clin Transl Radiat Oncol,2019

5. Magnetic Resonance Imaging-Guided Adaptive Radiation Therapy: A “Game Changer” for Prostate Treatment?;Pathmanathan;Int J Radiat Oncol Biol Phys,2018

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1. The Radiation Therapist profession through the lens of new technology: A practice development paper based on the ESTRO Radiation Therapist Workshops;Technical Innovations & Patient Support in Radiation Oncology;2024-06

2. Advanced practice in radiotherapy across Europe: stakeholders’ perceptions of implementation and evolution;Radiography;2024-05

3. Deep‐learning‐based joint rigid and deformable contour propagation for magnetic resonance imaging‐guided prostate radiotherapy;Medical Physics;2024-02-26

4. Magnetic resonance guided adaptive post prostatectomy radiotherapy: Accumulated dose comparison of different workflows;Journal of Applied Clinical Medical Physics;2024-02-23

5. Deep learning application for abdominal organs segmentation on 0.35 T MR-Linac images;Frontiers in Oncology;2024-01-08

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