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Surgical resection of malignant gliomas—role in optimizing patient outcome

Abstract

Malignant gliomas represent one of the most devastating human diseases. Primary treatment of these tumours involves surgery to achieve tumour debulking, followed by a multimodal regimen of radiotherapy and chemotherapy. Survival time in patients with malignant glioma has modestly increased in recent years owing to advances in surgical and intraoperative imaging techniques, as well as the systematic implementation of randomized trial-based protocols and biomarker-based stratification of patients. The role and importance of several clinical and molecular factors—such as age, Karnofsky score, and genetic and epigenetic status—that have predictive value with regard to postsurgical outcome has also been identified. By contrast, the effect of the extent of glioma resection on patient outcome has received little attention, with an 'all or nothing' approach to tumour removal still taken in surgical practice. Recent studies, however, reveal that maximal possible cytoreduction without incurring neurological deficits has critical prognostic value for patient outcome and survival. Here, we evaluate state-of-the-art surgical procedures that are used in management of malignant glioma, with a focus on assessment criteria and value of tumour reduction. We highlight key surgical factors that enable optimization of adjuvant treatment to enhance patient quality of life and improve life expectancy.

Key Points

  • For patients with malignant glioma, maximal possible tumour resection (maximal surgical outcome) is critical to improve prognosis

  • Objective preoperative and postoperative tumour volumetric methods and centre-independent validated assessment criteria should be implemented as part of the standard glioma management procedure

  • Intraoperative or delayed postoperative MRI is presently the gold standard to evaluate success of malignant glioma resection

  • Intraoperative imaging techniques enable surgeons to increase the extent of tumour resection, and can be used to quantify the success of tumour removal in an unbiased manner

  • In future, patients will be stratified for inclusion in clinical trials for resection on the basis of functional tumour grading, surgical outcome (extent of tumour resection) and individual genetic characteristics

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Figure 1: Treatment algorithm for patients with glioma.
Figure 2: Functional grading and imaging of malignant gliomas and surgical planning.
Figure 3: The tumour zone model.

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Acknowledgements

We thank all members of our neuro-oncology laboratory team for continuous support and clinical and experimental data discussion. The Tumorzentrum Erlangen-Nürnberg, particularly P. Karl and S. Petsch, are acknowledged for continuous collaboration and clinical data exchange. K. Friedlein is gratefully acknowledged for initial comorbidity analysis. We further thank P. Grummich for functional imaging, F. Bittner for digital artwork, and J. Halstead (Syngenta, Basel, Switzerland) for helpful comments. N. Hore is gratefully acknowledged for editing and critical suggestions on the manuscript. This study was supported by the German Research Foundation (DFG Grant Ey94/2-1 awarded to I. Y. Eyüpoglu).

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All authors contributed equally to researching data for the article, discussion of the content, writing the article, and to review and editing of the manuscript before submission.

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Correspondence to Ilker Y. Eyüpoglu.

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Eyüpoglu, I., Buchfelder, M. & Savaskan, N. Surgical resection of malignant gliomas—role in optimizing patient outcome. Nat Rev Neurol 9, 141–151 (2013). https://doi.org/10.1038/nrneurol.2012.279

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