Imperial College London
Alternate

DrDipankarNandi

Faculty of Medicine, Department of Brain Sciences

Professor of Practice (Neurosurgery)
 
 
 
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Contact

 

+44 (0)20 3311 1182d.nandi

 
 
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Location

 

Lab BlockCharing Cross Campus

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Summary

 

Publications

Citation

BibTex format

@article{Marcus:2017:10.1007/s10143-017-0817-0,
author = {Marcus, HJ and Williams, S and Hughes-Hallett, A and Camp, SJ and Nandi, D and Thorne, L},
doi = {10.1007/s10143-017-0817-0},
journal = {Neurosurgical Review},
pages = {621--631},
title = {Predicting surgical outcome in patients with glioblastoma multiforme using pre-operative magnetic resonance imaging: development and preliminary validation of a grading system.},
url = {http://dx.doi.org/10.1007/s10143-017-0817-0},
volume = {40},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Marcus,HJ
AU  - Williams,S
AU  - Hughes-Hallett,A
AU  - Camp,SJ
AU  - Nandi,D
AU  - Thorne,L
DO  - 10.1007/s10143-017-0817-0
EP  - 631
PY  - 2017///
SN  - 1437-2320
SP  - 621
TI  - Predicting surgical outcome in patients with glioblastoma multiforme using pre-operative magnetic resonance imaging: development and preliminary validation of a grading system.
T2  - Neurosurgical Review
UR  - http://dx.doi.org/10.1007/s10143-017-0817-0
UR  - http://hdl.handle.net/10044/1/45615
VL  - 40
ER  -
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