title: Predicting surgical outcome in patients with glioblastoma multiforme using pre-operative magnetic resonance imaging: development and preliminary validation of a grading system.
abstract: The lack of a simple, objective and reproducible system to describe glioblastoma multiforme (GBM) represents a major limitation in comparative effectiveness research. The objectives of this study were therefore to develop such a grading system and to validate it on patients who underwent surgical resection. A systematic review of the literature was performed to identify features on pre-operative magnetic resonance imaging (MRI) that predict the surgical outcome of patients with GBM. In all, the five most important features of GBM on pre-operative MRI were as follows: periventricular or deep location, corpus callosum or bilateral location, eloquent location, size and associated oedema. These were then used to develop a grading system. To validate this grading system, a retrospective cohort study of all adult patients with supratentorial GBM who underwent surgical resection between the 1 January 2014 and the 31 June 2015 was performed. There was a substantial agreement between the two neurosurgeons grading GBM (Cohen's κ was 0.625; standard error 0.066). High-complexity lesions were significantly less likely to result in complete resection of contrast-enhancing tumour than low-complexity lesions (50.0 versus 3.4%; p = 0.0007). The proposed grading system may allow for the standardised communication of anatomical features of GBM identified on pre-operative MRI.
authors.affiliation: The Hamlyn Centre, Institute of Global Health Innovation, Imperial College, London, UK. hani.marcus10@imperial.ac.uk.|Department of Neurosurgery, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK. hani.marcus10@imperial.ac.uk.|Clinical Research Fellow and Specialty Registrar in Neurosurgery, Hamlyn Centre, Imperial College London and Imperial College Healthcare NHS Trust, Paterson Building (Level 3), Praed Street, London, W2 1NY, UK. hani.marcus10@imperial.ac.uk.
authors.forename: Hani J
authors.initials: HJ
authors.lastname: Marcus
authors.affiliation: Department of Medicine, Imperial College, London, UK.
authors.forename: Sophie
authors.initials: S
authors.lastname: Williams
authors.affiliation: The Hamlyn Centre, Institute of Global Health Innovation, Imperial College, London, UK.
authors.forename: Archie
authors.initials: A
authors.lastname: Hughes-Hallett
authors.affiliation: Department of Neurosurgery, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
authors.forename: Sophie J
authors.initials: SJ
authors.lastname: Camp
authors.affiliation: Department of Neurosurgery, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
authors.forename: Dipankar
authors.initials: D
authors.lastname: Nandi
authors.affiliation: Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, UCLH Foundation Trust, London, UK.
authors.forename: Lewis
authors.initials: L
authors.lastname: Thorne
mesh_terms: D000368:Aged; D005260:Female; D005909:Glioblastoma / Q000000981:diagnostic imaging* / Q000473:pathology / Q000601:surgery*; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D015173:Supratentorial Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology / Q000601:surgery*; D016896:Treatment Outcome
keywords: Complications; Glioblastoma multiforme; Magnetic resonance imaging; Resection; Surgical outcome