Publication: Electrical stimulation-based nerve location prediction for cranial nerve VII localization in acoustic neuroma surgery
Issued Date
2018-06-01
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21623279
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2-s2.0-85046341787
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Mahidol University
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SCOPUS
Bibliographic Citation
Brain and Behavior. Vol.8, No.6 (2018)
Suggested Citation
Dilok Puanhvuan, Sorayouth Chumnanvej, Yodchanan Wongsawat Electrical stimulation-based nerve location prediction for cranial nerve VII localization in acoustic neuroma surgery. Brain and Behavior. Vol.8, No.6 (2018). doi:10.1002/brb3.981 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/47263
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Title
Electrical stimulation-based nerve location prediction for cranial nerve VII localization in acoustic neuroma surgery
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Abstract
© 2018 The Authors. Brain and Behavior published by Wiley Periodicals, Inc. Introduction: Cranial nerve (CN) VII localization is a critical step during acoustic neuroma surgery because the nerve is generally hidden due to the tumor mass. The patient can suffer from Bell's palsy if the nerve is accidentally damaged during tumor removal. Surgeons localize CN VII by exploring the target area with a stimulus probe. Compound muscle action potentials (CMAPs) are elicited when the probe locates the nerve. However, false positives and false negatives are possible due to unpredictable tissue impedance in the operative area. Moreover, a single CMAP amplitude is not correlated with probe-to-nerve distance. Objectives: This paper presents a new modality for nerve localization. The probe-to-nerve distance is predicted by the proposed nerve location prediction model. Methods: Input features are extracted from CMAP responses, tissue impedance, and stimulus current. The tissue impedance is calculated from the estimated resistance and capacitance of the tissue equivalent circuit. In this study, experiments were conducted in animals. A frog's sciatic nerve and gastrocnemius were used to represent CN VII and facial muscle in humans, respectively. Gelatin (2.8%) was used as a mock material to mimic an acoustic neuroma. The %NaCl applied to the mock material was used to emulate uncontrollable impedance of tissue in the operative area. Results: The 10-fold cross-validation results revealed an average prediction accuracy of 86.71% and an average predicted error of 0.76 mm compared with the measurement data. Conclusion: The proposed nerve location prediction model could predict the probe-to-nerve distance across various impedances of the mock material.