Evidence map›Paper›PMID 33587967›Full record

ArticleRadiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology2021

Evaluation of interim MRI changes during limited-field radiation therapy for glioblastoma and implications for treatment planning.

Comron Hassanzadeh, Soumon Rudra, Sirui Ma, Randall Brenneman, Yi Huang, Lauren Henke, Christopher Abraham, Jian Campian, Christina Tsien, Jiayi Huang

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2021. 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 26% 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.

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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Performance ofBMC medical imaging · 2022
    Article
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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

10 authors at 1 institution in 2 countries.

Comron HassanzadehDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
Soumon RudraDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
Sirui MaDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
Randall BrennemanDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
Yi HuangDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
Lauren HenkeDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
Christopher AbrahamDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
Jian CampianDepartment of Medicine, Oncology Division, Washington University School of Medicine, St. Louis, United States.
Christina TsienDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
Jiayi HuangDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, United States. Electronic address: Jiayi.huang@wustl.edu.
Washington University in St. Louis · US

Funding

Washington University Center for Cellular ImagingP30CA091842 · NCI · WASHINGTON UNIVERSITY · PI AIMEE S JAMES · 2001 to 2026
$128.0M
WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
NCATS NIH HHS UL1 TR000448NCATS NIH HHS UL1 TR002345NCI NIH HHS P30 CA091842
6 · The paper itself

Abstract

background and purposeConsensus for defining gross tumor volume (GTV) and clinical target volume (CTV) for limited-field radiation therapy (LFRT) of GBM are not well established. We leveraged a department MRI simulator to image patients before and during LFRT to address these questions. MATERIALS AND

methodsSupratentorial GBM patients receiving LFRT (46 Gy + boost to 60 Gy) underwent baseline MRI (MRI1) and interim MRI during RT (MRI2). GTV1 was defined as T1 enhancement + surgical cavity on MRI1 without routine inclusion of T2 abnormality (unless tumor did not enhance). The initial CTV margin was 15 mm from GTV1, and the boost CTV margin was 5-7 mm. The GTV1 characteristics were categorized into three groups: identical T1 and T2 abnormality (Group A), T1 only with larger T2 abnormality not included (Group B), and T2 abnormality when tumor lacked enhancement (Group C). GTV2 was contoured on MRI2 and compared with GTV1 plus 5-15 mm expansions.

resultsAmong 120 patients treated from 2014-2019, 29 patients (24%) underwent replanning based on MRI2. On MRI2, 84% of GTV2 were covered by GTV1 + 5 mm, 93% by GTV1 + 7 mm, and 98% by GTV1 + 15 mm. On MRI1, 43% of GTV1 could be categorized into Group A, 39% Group B, and 18% Group C. Group B's patterns of failure, local control, or progression-free survival were similar to Group A/C.

conclusionsInitial CTV margin of 15 mm followed by a boost CTV margin of 7 mm is a reasonable approach for LFRT of GBM. Omitting routine inclusion of T2 abnormality from GTV delineation may not jeopardize disease control.

Indexed as

Brain NeoplasmsGlioblastomaHumansMagnetic Resonance ImagingRadiotherapy Planning, Computer-AssistedChemoradiationGlioblastomaInterim MRILimited field RTPattern of failure

Identifiers

PMID33587967
PMCPMC8289483
OpenAlexW3130552008

What OpenQuestion holds

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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.