Evidence map›Paper›PMID 35880651›Full record

ArticleJournal of applied clinical medical physics2022

Development of a vendor neutral MRI distortion quality assurance workflow.

Amy Walker, Phillip Chlap, Trent Causer, Faisal Mahmood, Jarryd Buckley, Lois Holloway

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Evaluation of QUASAR Insight Phantom for daily imaging QA of MRgRT linacs.Journal of applied clinical medical physics · 2026
    Article
  3. Article
  4. Development of a vendor neutral MRI distortion quality assurance workflow.Journal of applied clinical medical physics · 2022
    Article
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

6 authors.

Amy WalkerLiverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.
Phillip ChlapLiverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.
Trent CauserCentre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia.
Faisal MahmoodLaboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark.
Jarryd BuckleyLiverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.
Lois HollowayLiverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the utilization of magnetic resonance (MR) imaging in radiotherapy increasing, routine quality assurance (QA) of these systems is necessary. The assessment of geometric distortion in images used for radiotherapy treatment planning needs to be quantified and monitored over time. This work presents an adaptable methodology for performing routine QA for systematic MRI geometric distortion. A software tool and compatible protocol (designed to work with any CT and MR compatible phantom on any scanner) were developed to quantify geometric distortion via deformable image registration. The MR image is deformed to the CT, generating a deformation field, which is sampled, quantifying geometric distortion as a function of distance from scanner isocenter. Configurability of the QA tool was tested, and results compared to those provided from commercial solutions. Registration accuracy was investigated by repeating the deformable registration step on the initial deformed MR image to define regions with residual distortions. The geometric distortion of four clinical systems was quantified using the customisable QA method presented. Maximum measured distortions varied from 2.2 to 19.4 mm (image parameter and sampling volume dependent). The workflow was successfully customized for different phantom configurations and volunteer imaging studies. Comparison to a vendor supplied solution showed good agreement in regions where the two procedures were sampling the same imaging volume. On a large field of view phantom across various scanners, the QA tool accurately quantified geometric distortions within 17-22 cm from scanner isocenter. Beyond these regions, the geometric integrity of images in clinical applications should be considered with a higher degree of uncertainty due to increased gradient nonlinearity and B

Indexed as

Magnetic Resonance ImagingRadiation OncologyHumansImage Processing, Computer-AssistedPhantoms, ImagingSoftwareWorkflowdistortionMRIphantomsquality assurance

Identifiers

PMID35880651
PMCPMC9588272

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Registered trials

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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.