Cortical resting motor threshold difference in asleep-awake craniotomy for motor eloquent gliomas: WHO grading influences motor pathway excitability

Author:

Pescador Ana M12,Lavrador José P1,Baamonde Alba D12,Soumpasis Christos1,Ghimire Prajwal13ORCID,Mosquera José D S12,Fiandeiro Carlos4,Jones Holly4,Gosavi Smita4,Lejarde Arjel2,Lawson Emily2,Murace Sian2,Gullan Richard1,Ashkan Keyoumars1,Bhangoo Ranjeev1,Vergani Francesco1

Affiliation:

1. Department of Neurosurgery, King’s College Hospital NHS Foundation Trust , Denmark Hill, London SE5 9RS , United Kingdom

2. Department of Clinical Neurophysiology, King’s College Hospital NHS Foundation Trust , Denmark Hill, London SE5 9RS , United Kingdom

3. School of Biomedical Engineering and Imaging Sciences, King’s College London , London , United Kingdom

4. Department of Anesthesia, King’s College Hospital NHS Foundation Trust , London , United Kingdom

Abstract

Abstract Developing neurophysiological tools to predict WHO tumor grade can empower the treating teams for a better surgical decision-making process. A total of 38 patients with supratentorial diffuse gliomas underwent an asleep-awake-sedated craniotomies for tumor removal with intraoperative neuromonitoring. The resting motor threshold was calculated for different train stimulation paradigms during awake and asleep phases. Receiver operating characteristic analysis and Bayesian regression models were performed to analyze the prediction of tumor grading based on the resting motor threshold differences. Significant positive spearman correlations were observed between resting motor threshold excitability difference and WHO tumor grade for train stimulation paradigms of 5 (R = 0.54, P = 0.00063), 4 (R = 0.49, P = 0.002), 3 (R = 0.51, P = 0.001), and 2 pulses (R = 0.54, P = 0.0007). Kruskal–Wallis analysis of the median revealed a positive significant difference between the median of excitability difference and WHO tumor grade in all paradigms. Receiver operating characteristic analysis showed 3 mA difference as the best predictor of high-grade glioma across different patterns of motor pathway stimulation. Bayesian regression found that an excitability difference above 3 mA would indicate a 75.8% probability of a glioma being high grade. Our results suggest that cortical motor excitability difference between the asleep and awake phases in glioma surgery could correlate with tumor grade.

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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