Evidence map›Paper›PMID 36411857›Full record

ArticlePhysics and imaging in radiation oncology2022

The impact of a metal artefact reduction algorithm on treatment planning for patients undergoing radiotherapy of the pelvis.

John King, Shona Whittam, David Smith, Bashar Al-Qaisieh

Open access · goldAbstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 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
0.7field-weighted citation impact, top 36% of its field
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, 8 citations in OpenAlex.

  1. Review
  2. Practical considerations for handling implants in proton therapy.Journal of applied clinical medical physics · 2025
    Article
  3. Article
  4. 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

4 authors at 1 institution in 1 country.

John KingLeeds Cancer Centre, St James's University Hospital, Bexley Wing, Beckett St, Leeds LS97FT, United Kingdom.
Shona WhittamLeeds Cancer Centre, St James's University Hospital, Bexley Wing, Beckett St, Leeds LS97FT, United Kingdom.
David SmithLeeds Cancer Centre, St James's University Hospital, Bexley Wing, Beckett St, Leeds LS97FT, United Kingdom.
Bashar Al-QaisiehLeeds Cancer Centre, St James's University Hospital, Bexley Wing, Beckett St, Leeds LS97FT, United Kingdom.
St James's University Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: Metallic implants cause artefacts in computed tomography (CT) images and can introduce significant errors to structure visualisation and dosimetric calculation within the radiotherapy planning process. This study evaluated an orthopaedic metal artefact reduction algorithm and its effect on the CT number, image noise, structure delineation, and treatment dose. Methods: Raw CT data were reconstructed using standard filtered back projection and an artefact reduction algorithm to create 'standard' and 'corrected' images. A phantom containing tissue-mimicking inserts and two titanium plugs was imaged. The average CT number was compared to baseline data acquired without metal inserts. Data from 11 pelvic external beam radiotherapy (EBRT) patients with bi- or uni-lateral hip implants were retrospectively analysed. The clinically used treatment plans were re-computed on the corrected images. A prostate-mimicking phantom containing metal 'implants' was imaged, and 11 observers contoured both reconstructions. Results: The artefact reduction algorithm improved the CT number in those areas most affected by metal artefacts and decreased noise by 19 % (P =.04) Changes in dose distributions on corrected images compared to those calculated using the current clinical protocol were clinically insignificant. Volumes contoured on the corrected phantom images had larger Dice coefficients than those contoured on the standard images (P =.001), as well as a 36 % lower standard deviation in volumes. Conclusion: This study demonstrates that the metal artefact reduction software reduces the error in CT numbers, can improve delineation accuracy, and can reduce inter-observer variability. It has the potential to streamline the planning pathway and improve treatment planning accuracy.

Indexed as

Artefact reductionComputed tomographyPelvis radiotherapyRadiotherapy

Identifiers

PMID36411857
PMCPMC9674537
OpenAlexW4308783247

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.