Evidence map›Paper›PMID 33386620›Full record

ArticleMedical physics2021

Task group 284 report: magnetic resonance imaging simulation in radiotherapy: considerations for clinical implementation, optimization, and quality assurance.

Carri K Glide-Hurst, Eric S Paulson, Kiaran McGee, Neelam Tyagi, Yanle Hu, James Balter, John Bayouth

Abstract read
In one paragraph

Article in Medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

73 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. AAPM-RSS Medical Physics Practice Guideline 9.b: SRS-SBRT.Journal of applied clinical medical physics · 2025
    Guideline
  2. Guideline
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Biologically adaptive radiation oncology in oligometastatic and oligoprogressive disease: MR- and CBCT-guided adaptation, molecular imaging, dose painting, biomarkers, and AI.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Evaluation of QUASAR Insight Phantom for daily imaging QA of MRgRT linacs.Journal of applied clinical medical physics · 2026
    Article
  18. Review
  19. Article
  20. Article

13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Carri K Glide-HurstDepartment of Human Oncology, University of Wisconsin-Madison, Madison, WI, 53792, USA.
Eric S PaulsonDepartment of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA.
Kiaran McGeeDepartment of Diagnostic Radiology, Mayo Clinic, Rochester, MN, 55905, USA.
Neelam TyagiMedical Physics Department, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA.
Yanle HuDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, 85054, USA.
James BalterDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, 48109, USA.
John BayouthDepartment of Human Oncology, University of Wisconsin-Madison, Madison, WI, 53792, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Development of Anatomical Patient Models to Facilitate MR-only Treatment PlanningR01CA204189 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI GLIDE-HURST, CARRI KAYE · 2016 to 2020
$1.5M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA204189NCI NIH HHS R01CA204189
6 · The paper itself

Abstract

The use of dedicated magnetic resonance simulation (MR-SIM) platforms in Radiation Oncology has expanded rapidly, introducing new equipment and functionality with the overall goal of improving the accuracy of radiation treatment planning. However, this emerging technology presents a new set of challenges that need to be addressed for safe and effective MR-SIM implementation. The major objectives of this report are to provide recommendations for commercially available MR simulators, including initial equipment selection, siting, acceptance testing, quality assurance, optimization of dedicated radiation therapy specific MR-SIM workflows, patient-specific considerations, safety, and staffing. Major contributions include guidance on motion and distortion management as well as MRI coil configurations to accommodate patients immobilized in the treatment position. Examples of optimized protocols and checklists for QA programs are provided. While the recommendations provided here are minimum requirements, emerging areas and unmet needs are also highlighted for future development.

Indexed as

Radiation OncologyRadiotherapy, Image-GuidedComputer SimulationHumansMagnetic Resonance ImagingRadiotherapy Planning, Computer-Assistedmagnetic resonance simulationMR-SIMquality assuranceradiotherapy

Identifiers

PMID33386620
PMCPMC8761371

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.