Cranial and peripheral biopotentials are routinely utilized to evaluate neurophysiologic integrity of both cranial and peripheral nerves during various surgical procedures. Intraoperative neurophysiological monitoring (IONM) provides outcome-sensitive, real-time metrics of neural transmission integrity, such as somatosensory evoked potential amplitude and latency. Such measures dynamically guide surgical procedures and reduce the risk of post-operative disabilities and complications. IONM has found widespread use in surgical interventions involving the brain and spinal cord for a range of disorders, including forms of cancer with CNS involvement. However, cerebral and peripheral biopotentials are very low level (down to sub-microvolt) signals that are highly susceptible to contamination by an array of electrically powered devices in the operating room (OR), such as the anesthesia machine, warming devices and especially, electrosurgical units (ESUs). Electromagnetic and electrostatic interference, both in the low frequency range (primarily 50-60 Hz) and radio frequency (RF) range limits and complicates signal acquisition and interpretation. In practice, the start of surgical procedures is often delayed and procedures can be interrupted due interference problems. ESU activation obliterates biopotential signal recordings. Interruption of evoked potential averaging sequences requires restart. Conventional methods of noise reduction, such as """"""""notch"""""""" filtering for line frequency noise, are often ineffective and impose various compromises of signal integrity, such as amplitude reduction and phase-shifting due to proximity to the signal frequency range. """"""""Baseline restore"""""""" techniques are useful in minimizing recovery time from ESU activation and other transients, but do not address the problem of signal loss at all. An advanced Intraoperative Neuromonitoring (aIONM) System is proposed that will achieve a very high level of immunity to both electrostatic and electromagnetic sources. Effectively, the aIONM system will reduce all forms of electrical interference in the OR environment to negligible levels, permitting uninterrupted recording of cerebral and peripheral biopotentials, even during ESU activation and without signal integrity compromise. The aIONM will introduce an analog electronic technology to IONM that enables noise-free biopotential signal acquisition in the presence of high and unbalanced electrode impedances for both cup and needle-type electrodes. Setup time for clinical and experimental protocols will be reduced to the time required to apply electrodes. It will eliminate scalp site preparation. Importantly, surgical procedures will not be delayed, interrupted or otherwise compromised due to interfernce in the OR. The aIONM will introduce a fundamentally newhardware architecture integrating acomplete,low power computerand LCD display. TheaIONM willprovide a full complement of monitoring and stimulation functions, replacing both portable and """"""""workstation"""""""" intraoperative monitors. Multimodal wireless connectivity and other features will further extend its utility for comprehensive IONM. The specific goal of Phase I is to evaluate key system performance elements in both benchtop tests and intraoperatively in human subjects at two independent, university-based centers.

Public Health Relevance

The proposed system would find application in routine clinical and experimental acquisition of intraoperative biopotentials. The very high tolerance of the proposed Advanced Intraoperative Neuromonitoring System (aIONM) for high and unbalanced electrode impedances in electrically noisy operating room environments will substantially improve the ability to monitor critical neurophysiological functions during surgical procedures. The aIONM will eliminate intraoperative monitoring disruptions due to electrical noise and thus increase the level of care. Further, the IBMS will also achieve a much higher benefit:cost ratio than existing technologies. ? ? ?

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
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Special Emphasis Panel (ZRG1-BDCN-E (10))
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Hicks, Ramona R
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Neurocomp Systems, Inc.
Santa Ana
United States
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