Automatic detection of burst suppression

Caffeine reverses the unconsciousness produced by light anesthesia in the continued presence of isoflurane in rats

Currently no drugs are employed clinically to reverse the unconsciousness induced by general anesthetics. Our previous studies showed that caffeine, when given near the end of an anesthesia session, accelerated emergence from isoflurane anesthesia, likely caused by caffeine’s ability to elevate intracellular cAMP levels and to block adenosine receptors. These earlier studies showed that caffeine did not rouse either rats or humans from deep anesthesia (≥ 1 minimum alveolar concentration, MAC). In this current crossover study, we examined whether caffeine reversed the unconsciousness produced by light anesthesia (< 1 MAC) in the continued presence of isoflurane. The primary endpoint of this study was to measure isoflurane levels at the time of recovery of righting reflex, which was a proxy for consciousness. Rats were deeply anesthetized with 2% isoflurane (~1.5 MAC) for 20 minutes. Subsequently, isoflurane was reduced to 1.2% for 10 minutes, then by 0.2% every 10 min; animals were monitored until the recovery of righting reflex occurred, in the continued presence of isoflurane. Respiration rate, heart rate and electroencephalogram (EEG) were monitored. Our results show that caffeine-treated rats recovered their righting reflex at a significantly higher inspired isoflurane concentration, corresponding to light anesthesia, than the same rats treated with saline (control). Respiration rate and heart rate increased initially after caffeine injection but were then unchanged for the rest of the anesthesia session. Deep anesthesia is correlated with burst suppression in EEG recordings. Our data showed that caffeine transiently reduced the burst suppression time produced by deep anesthesia, suggesting that caffeine altered neuronal circuit function but not to a point where it caused arousal. In contrast, under light anesthesia, caffeine shifted the EEG power to high frequency beta and gamma bands. These data suggest that caffeine may represent a clinically viable drug to reverse the unconsciousness produced by light anesthesia.

Design, implementation, and evaluation of a physiological closed-loop control device for medically-induced coma

Concerns regarding reliability and safety, as well as uncertainties about what constitutes adequate performance evaluation, have impeded the clinical translation of PCLC devices. We describe an attempt to address these challenges through design, implementation, and evaluation of a PCLC device for delivering medically-induced coma, with the intention to eventually conduct a clinical trial. This device works by automatically adjusting the infusion rate of propofol - a general anesthetic - in response to an electroencephalogram (EEG) pattern called burst suppression. We also designed and implemented a computational patient model which interfaces with hardware and produces realistic EEG signals in response to propofol infusion. The computational patient model is used in hardware-in-the-loop studies to evaluate the behavior of our PCLC device under realistic perturbations. Finally, we have tested the performance of our PCLC device in rodents. Results from these studies suggest that closed-loop control of medically-induced coma in humans is feasible and robust. Consequently, our work produced a PCLC device and relevant pre-clinical evidence in support of a pilot clinical trial.

Continuous Intraoperative Monitoring of Temporal Lobe Epilepsy Surgery

BACKGROUND/AIMS

The monitoring of interictal epileptiform discharge rates (IEDRs) all along anterior temporal lobe resections (ATLRs) has never been reported. Here the effect of ATLR on continuous IEDR monitoring is described.

METHODS

IEDRs computed automatically during entire interventions were recorded in 34 patients (38.2%, 13/34 depth; 61.8%, 21/34 scalp electrodes only). Monitorings were invalidated when burst suppression occurred or if initial IEDRs were <5.

RESULTS

Monitoring was successful for 69.2% (9/13) of the patients with depth recordings and for 4.8% (1/21) of the patients with scalp recordings. Burst suppressions precluded it in 30.8% (4/13) of the depth and in 57.1% (12/21) of the scalp recordings. Initial IEDRs were <5 for 38.1% (8/21) of the scalp recordings. Significant IEDR decreases were observed in 8/10 patients with successful monitoring. These decreases started with resection of the superior temporal gyrus. IEDRs decreased further with amygdalohippocampectomy in 3/5 patients. At the 12-month follow-up, all patients with IEDR decreases remained seizure free; both patients without did not.

CONCLUSION

IEDR monitoring was possible with depth, but not with scalp electrodes. IEDR decreases started with resection of the superior temporal gyrus. A larger patient cohort is necessary to confirm the high predictive values of IEDR monitoring that could become a tool for surgery customization.

Spatial variation in automated burst suppression detection in pharmacologically induced coma

Burst suppression is actively studied as a control signal to guide anesthetic dosing in patients undergoing medically induced coma. The ability to automatically identify periods of EEG suppression and compactly summarize the depth of coma using the burst suppression probability (BSP) is crucial to effective and safe monitoring and control of medical coma. Current literature however does not explicitly account for the potential variation in burst suppression parameters across different scalp locations. In this study we analyzed standard 19-channel EEG recordings from 8 patients with refractory status epilepticus who underwent pharmacologically induced burst suppression as medical treatment for refractory seizures. We found that although burst suppression is generally considered a global phenomenon, BSP obtained using a previously validated algorithm varies systematically across different channels. A global representation of information from individual channels is proposed that takes into account the burst suppression characteristics recorded at multiple electrodes. BSP computed from this representative burst suppression pattern may be more resilient to noise and a better representation of the brain state of patients. Multichannel data integration may enhance the reliability of estimates of the depth of medical coma.