Evidence map›Paper›PMID 38424642›Full record

ArticleRadiation oncology (London, England)2024

Contouring practices and artefact management within a synthetic CT-based radiotherapy workflow for the central nervous system.

Elia Rossi, Sevgi Emin, Michael Gubanski, Giovanna Gagliardi, Mattias Hedman, Fernanda Villegas

Open access · goldAbstract read
In one paragraph

Article in Radiation oncology (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 40% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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 at 2 institutions in 1 country.

Elia RossiDepartment of Radiation Oncology, Karolinska University Hospital, Solna, Sweden.
Sevgi EminRadiotherapy Physics and Engineering, Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Solna, Sweden.
Michael GubanskiDepartment of Radiation Oncology, Karolinska University Hospital, Solna, Sweden.
Giovanna GagliardiRadiotherapy Physics and Engineering, Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Solna, Sweden.
Mattias HedmanDepartment of Radiation Oncology, Karolinska University Hospital, Solna, Sweden.
Fernanda VillegasRadiotherapy Physics and Engineering, Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Solna, Sweden. fernanda.villegasnavarro@ki.se.
Karolinska University Hospital · SEKarolinska Institutet · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe incorporation of magnetic resonance (MR) imaging in radiotherapy (RT) workflows improves contouring precision, yet it introduces geometrical uncertainties when registered with computed tomography (CT) scans. Synthetic CT (sCT) images could minimize these uncertainties and streamline the RT workflow. This study aims to compare the contouring capabilities of sCT images with conventional CT-based/MR-assisted RT workflows, with an emphasis on managing artefacts caused by surgical fixation devices (SFDs).

methodsThe study comprised a commissioning cohort of 100 patients with cranial tumors treated using a conventional CT-based/MR-assisted RT workflow and a validation cohort of 30 patients with grade IV glioblastomas treated using an MR-only workflow. A CE-marked artificial-intelligence-based sCT product was utilized. The delineation accuracy comparison was performed using dice similarity coefficient (DSC) and average Hausdorff distance (AHD). Artefacts within the commissioning cohort were visually inspected, classified and an estimation of thickness was derived using Hausdorff distance (HD). For the validation cohort, boolean operators were used to extract artefact volumes adjacent to the target and contrasted to the planning treatment volume.

resultsThe combination of high DSC (0.94) and low AHD (0.04 mm) indicates equal target delineation capacity between sCT images and conventional CT scans. However, the results for organs at risk delineation were less consistent, likely because of voxel size differences between sCT images and CT scans and absence of standardized delineation routines. Artefacts observed in sCT images appeared as enhancements of cranial bone. When close to the target, they could affect its definition. Therefore, in the validation cohort the clinical target volume (CTV) was expanded towards the bone by 3.5 mm, as estimated by HD analysis. Subsequent analysis on cone-beam CT scans showed that the CTV adjustment was enough to provide acceptable target coverage.

conclusionThe tested sCT product performed on par with conventional CT in terms of contouring capability. Additionally, this study provides both the first comprehensive classification of metal artefacts on a sCT product and a novel method to assess the clinical impact of artefacts caused by SFDs on target delineation. This methodology encourages similar analysis for other sCT products.

Indexed as

ArtifactsRadiotherapy Planning, Computer-AssistedCentral Nervous SystemHumansMagnetic Resonance ImagingTomography, X-Ray ComputedWorkflowContouring processMetal artefactsMR-onlyRadiation therapySynthetic-CT

Identifiers

PMID38424642
PMCPMC11320867
OpenAlexW4392284322

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.