Evidence map›Paper›PMID 26203067›Full record

ReviewNeuro-oncology2015

Intratumoral heterogeneity in glioblastoma: don't forget the peritumoral brain zone.

Jean-Michel Lemée, Anne Clavreul, Philippe Menei

3 registry-linked trialsAbstract readReview
In one paragraph

Review in Neuro-oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 170 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
170citing papers in PubMed, 2 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.

NCT03542409 early_phase1completednot on this mapstarted 2017, after this paper: background citation

Assessment of Safety and Feasibility of Preoperative and Intraoperative Image-Guided Resection of Gliomas and Tumor Region-Specific Biomarker Correlation

TypeinterventionalSponsorUniversity of UtahRan2017 to 2025Enrolled53ConditionsBrain Tumor AdultArmsMR Perfusion Scan, 2HG Spectroscopy Scan, Standard of Care Intraoperative MRI
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
NCT07703761 recruitingnot on this mapstarted 2026, after this paper: background citation

AI-driven Processing and Analysis of Glioma Imaging Data EUCAIM Database Contribution by the Italian Brain Glioma Initiative Italian Title: Elaborazione ed Analisi Supportata Dall'Intelligenza Artificiale di Immagini di Risonanza Magnetica di Gliomi Cerebrali

TypeobservationalSponsorUniversità degli Studi di TrentoRan2026 to 2031Enrolled700ConditionsGlioma, Glioma (Diagnosis)ArmsAI-driven analysis of brain MRI data for early, non-invasive detection, segmentation, and histological characterization of gliomas using retrospective clinical and imaging records.
3 · Its place in the literature

Who cites it

170 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Imaging-Based Algorithm for the Local Grading of Glioma.AJNR. American journal of neuroradiology · 2020
    Trial
  6. Trial
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Radiomics-based differentiation between glioblastoma and primary central nervous system lymphoma: CT vs MRI.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Article

110 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Jean-Michel LeméeDepartment of Neurosurgery, University Hospital of Angers, Angers, France (J.-M.L., A.C., P.M.); INSERM U1066, "Micro- et nano-médecine biomimétiques", Angers, France (J.-M.L., A.C., P.M.).
Anne ClavreulDepartment of Neurosurgery, University Hospital of Angers, Angers, France (J.-M.L., A.C., P.M.); INSERM U1066, "Micro- et nano-médecine biomimétiques", Angers, France (J.-M.L., A.C., P.M.).
Philippe MeneiDepartment of Neurosurgery, University Hospital of Angers, Angers, France (J.-M.L., A.C., P.M.); INSERM U1066, "Micro- et nano-médecine biomimétiques", Angers, France (J.-M.L., A.C., P.M.).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma (GB) is the most frequent and aggressive primary tumor of the central nervous system. Prognosis remains poor despite ongoing progress. In cases where the gadolinium-enhanced portion of the GB is completely resected, 90% of recurrences occur at the margin of surgical resection in the macroscopically normal peritumoral brain zone (PBZ). Intratumoral heterogeneity in GB is currently a hot topic in neuro-oncology, and the GB PBZ may be involved in this phenomenon. Indeed, this region, which possesses specific properties, has been less studied than the core of the GB tumor. The high rate of local recurrence in the PBZ and the limited success of targeted therapies against GB demonstrate the need for a better understanding of the PBZ. We present here a review of the literature on the GB PBZ, focusing on its radiological, cellular, and molecular characteristics. We discuss how intraoperative analysis of the PBZ is important for the optimization of surgical resection and the development of targeted therapies against GB.

Indexed as

Biomarkers, TumorBrain NeoplasmsGlioblastomaHumansNanocapsulesNeoplasm Recurrence, LocalBiomarkers, TumorNanocapsulesglioblastomahistologyomicsperitumoral brain zoneradiologytargeted therapies

Identifiers

PMID26203067
PMCPMC4578587

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.