Evidence map›Paper›PMID 32860571›Full record

ArticleJournal of neuro-oncology2020

Glioma consensus contouring recommendations from a MR-Linac International Consortium Research Group and evaluation of a CT-MRI and MRI-only workflow.

Chia-Lin Tseng, James Stewart, Gillian Whitfield, Joost J C Verhoeff, Joseph Bovi, Hany Soliman, Caroline Chung, Sten Myrehaug, Mikki Campbell, Eshetu G Atenafu and 5 more

Registry-linked trialAbstract readConsensus Statement
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neuro-oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06492486 (Glioma Adaptive Radiotherapy With Development of an Artificial Intelligence Workflow), which is not on this map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 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.

NCT06492486 phase2recruitingnot on this mapstarted 2026, after this paper: background citation

Glioma Adaptive Radiotherapy With Development of an Artificial Intelligence Workflow

TypeinterventionalSponsorTata Memorial CentreRan2026 to 2028Enrolled60ConditionsDiffuse Glioma, Glioblastoma, Adaptive Radiotherapy, Artificial IntelligenceArmsAdaptive radiotherapy
3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

15 authors.

Chia-Lin TsengDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada. chia-lin.tseng@sunnybrook.ca.ORCID http://orcid.org/0000-0002-3700-0886
James StewartDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Gillian WhitfieldManchester Academic Health Science Centre, University of Manchester, The Christie NHS Foundation Trust, Manchester, UK.
Joost J C VerhoeffDepartment of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
Joseph BoviDepartment of Radiation Oncology, Froedtert Memorial Lutheran Hospital, Milwaukee, WI, USA.
Hany SolimanDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Caroline ChungDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Sten MyrehaugDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Mikki CampbellDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Eshetu G AtenafuDepartments of Biostatistics, University Health Network, University of Toronto, Toronto, ON, Canada.
Chinthaka HeynDepartment of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
Sunit DasDivision of Neurosurgery, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.
James PerryDepartment of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
Mark RuschinDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Arjun SahgalDepartment of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis study proposes contouring recommendations for radiation treatment planning target volumes and organs-at-risk (OARs) for both low grade and high grade gliomas.

methodsTen cases consisting of 5 glioblastomas and 5 grade II or III gliomas, including their respective gross tumor volume (GTV), clinical target volume (CTV), and OARs were each contoured by 6 experienced neuro-radiation oncologists from 5 international institutions. Each case was first contoured using only MRI sequences (MRI-only), and then re-contoured with the addition of a fused planning CT (CT-MRI). The level of agreement among all contours was assessed using simultaneous truth and performance level estimation (STAPLE) with the kappa statistic and Dice similarity coefficient.

resultsA high level of agreement was observed between the GTV and CTV contours in the MRI-only workflow with a mean kappa of 0.88 and 0.89, respectively, with no statistically significant differences compared to the CT-MRI workflow (p = 0.88 and p = 0.82 for GTV and CTV, respectively). Agreement in cochlea contours improved from a mean kappa of 0.39 to 0.41, to 0.69 to 0.71 with the addition of CT information (p < 0.0001 for both cochleae). Substantial to near perfect level of agreement was observed in all other contoured OARs with a mean kappa range of 0.60 to 0.90 in both MRI-only and CT-MRI workflows.

conclusionsConsensus contouring recommendations for low grade and high grade gliomas were established using the results from the consensus STAPLE contours, which will serve as a basis for further study and clinical trials by the MR-Linac Consortium.

Indexed as

GlioblastomaMagnetic Resonance ImagingPractice Patterns, Physicians'Radiotherapy Planning, Computer-AssistedTomography, X-Ray ComputedBrachytherapyFollow-Up StudiesHumansParticle AcceleratorsPrognosisProspective StudiesRetrospective StudiesTumor BurdenWorkflowConsensus contouring recommendationsGliomaMR-linacOrgans-at-riskRadiotherapy

Identifiers

PMID32860571
PMCPMC7541359

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Registered trials

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.