Investigation of data-driven optical neuromonitoring approach during general anesthesia with sevoflurane

Comparison of cerebral metabolic rate of oxygen, blood flow, and bispectral index under general anesthesia

SIGNIFICANCE

The optical measurement of cerebral oxygen metabolism was evaluated.

AIM

Compare optically derived cerebral signals to the electroencephalographic bispectral index (BIS) sensors to monitor propofol-induced anesthesia during surgery.

APPROACH

Relative cerebral metabolic rate of oxygen ( rCMRO 2 ) and blood flow (rCBF) were measured by time-resolved and diffuse correlation spectroscopies. Changes were tested against the relative BIS (rBIS) ones. The synchronism in the changes was also assessed by the R-Pearson correlation.

RESULTS

In 23 measurements, optically derived signals showed significant changes in agreement with rBIS: during propofol induction, rBIS decreased by 67% [interquartile ranges (IQR) 62% to 71%], rCMRO 2 by 33% (IQR 18% to 46%), and rCBF by 28% (IQR 10% to 37%). During recovery, a significant increase was observed for rBIS (48%, IQR 38% to 55%), rCMRO 2 (29%, IQR 17% to 39%), and rCBF (30%, IQR 10% to 44%). The significance and direction of the changes subject-by-subject were tested: the coupling between the rBIS, rCMRO 2 , and rCBF was witnessed in the majority of the cases (14/18 and 12/18 for rCBF and 19/21 and 13/18 for rCMRO 2 in the initial and final part, respectively). These changes were also correlated in time ( R > 0.69 to R = 1 , p - values < 0.05 ).

CONCLUSIONS

Optics can reliably monitor rCMRO 2 in such conditions.

Near Infrared Spectroscopy for High-Temporal Resolution Cerebral Physiome Characterization in TBI: A Narrative Review of Techniques, Applications, and Future Directions

Multimodal monitoring has been gaining traction in the critical care of patients following traumatic brain injury (TBI). Through providing a deeper understanding of the individual patient's comprehensive physiologic state, or "physiome," following injury, these methods hold the promise of improving personalized care and advancing precision medicine. One of the modalities being explored in TBI care is near-infrared spectroscopy (NIRS), given it's non-invasive nature and ability to interrogate microvascular and tissue oxygen metabolism. In this narrative review, we begin by discussing the principles of NIRS technology, including spatially, frequency, and time-resolved variants. Subsequently, the applications of NIRS in various phases of clinical care following TBI are explored. These applications include the pre-hospital, intraoperative, neurocritical care, and outpatient/rehabilitation setting. The utility of NIRS to predict functional outcomes and evaluate dysfunctional cerebrovascular reactivity is also discussed. Finally, future applications and potential advancements in NIRS-based physiologic monitoring of TBI patients are presented, with a description of the potential integration with other omics biomarkers.

Monitoring anesthesia using simultaneous functional Near Infrared Spectroscopy and Electroencephalography

OBJECTIVE

This study aims to understand the neural and hemodynamic responses during general anesthesia in order to develop a comprehensive multimodal anesthesia depth monitor using simultaneous functional Near Infrared Spectroscopy (fNIRS) and Electroencephalogram (EEG).

METHODS

37 adults and 17 children were monitored with simultaneous fNIRS and EEG, during the complete general anesthesia process. The coupling of fNIRS signals with neuronal signals (EEG) was calculated. Measures of complexity (sample entropy) and phase difference were also quantified from fNIRS signals to identify unique fNIRS based biomarkers of general anesthesia.

RESULTS

A significant decrease in the complexity and power of fNIRS signals characterize the anesthesia maintenance phase. Furthermore, responses to anesthesia vary between adults and children in terms of neurovascular coupling and frontal EEG alpha power.

CONCLUSIONS

This study shows that fNIRS signals could reliably quantify the underlying neuronal activity under general anesthesia and clearly distinguish the different phases throughout the procedure in adults and children (with less accuracy).

SIGNIFICANCE

A multimodal approach incorporating the specific differences between age groups, provides a reliable measure of anesthesia depth.

Clinical Correlation of Intraoperative Neuromonitoring in 319 Individuals Undergoing Posterior Decompression and Fixation of Spine

STUDY DESIGN

This was a prospective study.

OBJECTIVES

To correlate improvement in motor evoked potential (MEP) during spine surgery with postoperative clinical improvement.

MATERIALS AND METHODS

Three hundred fifty-three patients operated for posterior spinal decompression and fixation surgeries were prospectively selected and followed up. Patients who underwent lumbar, dorsal, and cervical surgeries were grouped into-group A, B, and C, respectively. Intraoperative neuromonitoring was done using MEP with free-running electromyography. Improvements in MEP scores were calculated in percentage. Similarly, postoperative improvement in Oswestry disability index (ODI) and visual analog scale (VAS) scores at 3 months were calculated in percentage. Improvements in MEP scores were correlated with clinical improvement using the Spearman ρ test and the r value was calculated to find out the association.

RESULTS

Of 353 patients, 319 (250-group A, 38-group B, and 31-group C) were included for the study. VAS and ODI improved significantly from preoperative 8.5±0.8 and 62.9±14.5, to postoperative 2.3±1.1 and 15.9±11.5, respectively, in the entire group. Average preoperative MEP were 127.8±191.0 mV on the right side and 132.3±206.6 mV on the left side, which significantly improved to 163.7±231.2 mV (P=0.0001) and 155.2±219.6 mV (P=0.0001), respectively, showing 157.0% and 178.5% improvement. Correlating MEP improvement with postoperative improvement in ODI showed poor correlation (r=0.088 right and 0.030 left sides). Similarly, correlating MEP improvement with improvement in VAS showed r=0.110 on the right and -0.023 on the left side suggesting poor correlation. Postoperative neurological complications (0.56%) were found in 2 patients in the form of screw malpositioning.

CONCLUSIONS

Intraoperative neuromonitoring showed significant improvement during posterior decompression and fixation surgery, and reduction in postoperative neurological complication. The study also exhibited significant postoperative clinical improvement. However, improvement in MEP did not correlate with postoperative clinical improvement suggesting that it has no predictive role.

Artificial Intelligence: A New Tool in Operating Room Management. Role of Machine Learning Models in Operating Room Optimization

We conducted a systematic review of literature to better understand the role of new technologies in the perioperative period; in particular we focus on the administrative and managerial Operating Room (OR) perspective. Studies conducted on adult (≥ 18 years) patients between 2015 and February 2019 were deemed eligible. A total of 19 papers were included. Our review suggests that the use of Machine Learning (ML) in the field of OR organization has many potentials. Predictions of the surgical case duration were obtain with a good performance; their use could therefore allow a more precise scheduling, limiting waste of resources. ML is able to support even more complex models, which can coordinate multiple spaces simultaneously, as in the case of the post-anesthesia care unit and operating rooms. Types of Artificial Intelligence could also be used to limit another organizational problem, which has important economic repercussions: cancellation. Random Forest has proven effective in identifing surgeries with high risks of cancellation, allowing to plan preventive measures to reduce the cancellation rate accordingly. In conclusion, although data in literature are still limited, we believe that ML has great potential in the field of OR organization; however, further studies are needed to assess the effective role of these new technologies in the perioperative medicine.

Monitoring the Depth of Anesthesia Through the Use of Cerebral Hemodynamic Measurements Based on Sample Entropy Algorithm

OBJECTIVE

The aim of this study is to explore the relationship between the depth of anesthesia and the cerebral hemodynamic variables during the complete anesthesia process.

METHODS

In this study, near-infrared spectroscopy signals were used to record eight kinds of cerebral hemodynamic variables, including left, right, proximal, distal deoxygenated (Hb) and oxygenated (HbO₂) hemoglobin concentration changes. Then, by measuring the complexity information of cerebral hemodynamic variables, the sample entropy was calculated as a new index of monitoring the depth of anesthesia.

RESULTS

By means of receiver operating characteristic curve analysis, the sample entropy approach was proved to effectively discriminate anesthesia maintenance and waking phases. The discriminatory ability of HbO₂ signals was stronger than that of Hb signals and the distal signals had weaker discrimination capability when compared with the proximal signals. In addition, there was statistical consistency between the bispectral index and sample entropy of cerebral hemodynamic variables during the complete anesthesia process. Moreover, the cerebral hemodynamic signals could not be interfered by clinical electrical devices.

CONCLUSION

The sample entropy of cerebral hemodynamic variables could be suitable as a new index for monitoring the depth of anesthesia.

SIGNIFICANCE

This study is very meaningful for developing new modality and decoding methods in perspective of anesthesia surveillance and may result in the anesthesia monitoring system with high performance.