Sidpra, J;
Marcus, AP;
Löbel, U;
Toescu, SM;
Yecies, D;
Grant, G;
Yeom, K;
... Mankad, K; + view all
(2022)
Improved prediction of postoperative paediatric cerebellar mutism syndrome using an artificial neural network.
Neuro-Oncology Advances
, Article vdac003. 10.1093/noajnl/vdac003.
(In press).
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Abstract
BACKGROUND: Postoperative paediatric cerebellar mutism syndrome (pCMS) is a common but severe complication which may arise following the resection of posterior fossa tumours in children. Two previous studies have aimed to preoperatively predict pCMS, with varying results. In this work, we examine the generalisation of these models and determine if pCMS can be predicted more accurately using an artificial neural network (ANN). METHODS: An overview of reviews was performed to identify risk factors for pCMS, and a retrospective dataset collected as per these defined risk factors from children undergoing resection of primary posterior fossa tumours. The ANN was trained on this dataset and its performance evaluated in comparison to logistic regression and other predictive indices via analysis of receiver operator characteristic curves. Area under the curve (AUC) and accuracy were calculated and compared using a Wilcoxon signed rank test, with p<0.05 considered statistically significant. RESULTS: 204 children were included, of whom 80 developed pCMS. The performance of the ANN (AUC 0.949; accuracy 90.9%) exceeded that of logistic regression (p<0.05) and both external models (p<0.001). CONCLUSION: Using an ANN, we show improved prediction of pCMS in comparison to previous models and conventional methods.
| Type: | Article |
|---|---|
| Title: | Improved prediction of postoperative paediatric cerebellar mutism syndrome using an artificial neural network |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/noajnl/vdac003 |
| Publisher version: | https://doi.org/10.1093/noajnl/vdac003 |
| Language: | English |
| Additional information: | © The Author(s) 2022. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
| Keywords: | Artificial neural network, complications, magnetic resonance imaging, post-operative paediatric cerebellar mutism syndrome, posterior fossa tumour |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10141901 |
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