A Prewarning Signalling in Motor Evoked Potentials Monitoring for Insular Glioma Surgery: A Preliminary Study

Area of Science:

• Neurosurgery
• Neurophysiology
• Oncology

Background:

• Insular gliomas present significant surgical challenges.
• Intraoperative neurophysiological monitoring (INM) aids surgical resection, but current methods like Motor Evoked Potential (MEP) reduction >50% often signal deficits too late.
• There is a critical need for earlier indicators to optimize surgical decision-making.

Purpose of the Study:

• To identify pre-warning signals (PWS) that anticipate Motor Evoked Potential (MEP) drops during insular glioma surgery.
• To compare the predictive accuracy of PWS with existing warning signs (WS) for postoperative motor deficits.
• To enhance the reliability of intraoperative monitoring for insular tumor resection.

Main Methods:

• Retrospective analysis of clinical, surgical, and neurophysiological data from 30 patients with insular tumors.
• Utilized Fourier transform and dynamic time warping (DTW) to analyze MEP signals.
• Applied logistic regression to identify PWS and compare its efficacy against traditional WS.

Main Results:

• A logistic regression model achieved 91.45% accuracy in identifying a PWS that anticipates MEP drops >50%.
• PWS demonstrated comparable sensitivity (83.3%) and negative predictive value (93.8%) to WS for predicting MEP drops and correlating with outcomes.
• PWS showed superior specificity (62.5%) and positive predictive value (35.7%) in predicting motor deficits compared to WS.

Conclusions:

• The identified pre-warning signal (PWS) is a reliable predictor of motor outcomes in insular glioma surgery.
• PWS offers more accurate and timely identification of intraoperative monitoring variations than traditional warning signs (WS).
• This preliminary data suggests PWS can optimize surgical management and improve patient prognoses.