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Related Experiment Video

Updated: Dec 25, 2025

Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections
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Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections

Published on: July 31, 2017

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Quantifying eloquent locations for glioblastoma surgery using resection probability maps.

Domenique M J Müller1, Pierre A Robe2, Hilko Ardon3

  • 11Brain Tumor Center & Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands.

Journal of Neurosurgery
|April 4, 2020
PubMed

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Summary

New metrics, expected residual tumor volume (eRV) and expected resectability index (eRI), better predict glioblastoma surgical outcomes and survival than traditional eloquence grading. These indices can aid preoperative decision-making for neurosurgeons.

Area of Science:

  • Neurosurgery
  • Oncology
  • Medical Imaging

Background:

  • Surgical decisions for glioblastoma (GBM) often rely on the presumed functional significance of tumor location.
  • Predicting surgical outcomes in GBM remains challenging, impacting patient prognosis and treatment strategies.

Purpose of the Study:

  • To introduce and evaluate novel quantitative metrics: expected residual tumor volume (eRV) and expected resectability index (eRI).
  • To determine the diagnostic accuracy of eRV and eRI in predicting biopsy decisions, extent of resection (EOR), functional outcomes, and survival in glioblastoma patients.
  • To compare the predictive performance of eRV and eRI against traditional tumor location eloquence grades (EGs).

Main Methods:

  • Utilized preoperative MRI scans from 915 first-time glioblastoma patients across 12 hospitals (2012-2013).
Keywords:
extent of resectiongliomaneurosurgeryoncologyreproducibility of resultsresidual volume

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  • Calculated eRV using resection probability maps and eRI based on tumor volume.
  • Assessed resectability via observed EOR and residual volume, functional outcome using Karnofsky Performance Scale, and survival.
  • Employed receiver operating characteristic curves and multivariable logistic regression for analysis, comparing eRV and eRI against EGs.

    • Main Results:

    • The eRV and eRI demonstrated superior accuracy over EGs in predicting biopsy decisions and achieving high EORs (≥80%, 90%, 98%).
    • Both eRV and eRI better predicted low observed residual volumes (<10 ml, <5 ml, <1 ml) compared to EGs.
    • While eRV, eRI, and EG showed low accuracy for predicting functional outcome changes, higher eRV and lower eRI strongly correlated with shorter survival, independent of other prognostic factors.

    Conclusions:

    • The expected residual tumor volume (eRV) and expected resectability index (eRI) are valuable preoperative tools for glioblastoma surgery.
    • These novel indices offer improved prediction of biopsy decisions, resectability, and patient survival compared to traditional eloquence grading.
    • eRV and eRI can potentially enhance surgical decision-making and patient management in glioblastoma treatment.