Optical Neuroimaging to Discern Transitions in Anesthetic Depth from Systemic Hemodynamic Instability

Background: Reliable intraoperative monitoring of anesthesia depth is critical for patient safety, yet standard monitors can be confounded by systemic physiological changes. Non-invasive optical modalities that measure cerebral hemodynamics offer a promising approach, but their ability to differentiate brain neurovascular activity assessment versus changes due to systemic events requires validation. This study aims to explore the robustness of diffuse correlation (DCS) and near-infrared spectroscopy (NIRS) measures in differentiating changes in cerebral signals due to changes in anesthetic depth versus those resulting from alterations in systemic hemodynamics. Methods: A neonatal piglet model (N = 18) was used to assess anesthesia states and injury models creating systemic hemodynamic changes which may lead to instability in readings of hemodynamic responses and likely cause failure to detect the true anesthesia state. We continuously measured relative cerebral blood flow (rBFI), oxyhemoglobin (HbO), deoxyhemoglobin (HbR), and total hemoglobin (HbTotal) concentrations during three distinct conditions: (1) transition from deep to light anesthesia state in healthy piglets, (2) controlled hemorrhage, and (3) hypoxia induced under maintained deep anesthesia. Linear mixed-effects models were used to compare hemodynamic signatures across conditions. Results: Transition to light anesthesia was characterized by significant increases in rBFI (p.adj < 0.01), HbO (p.adj < 0.01), and HbTotal (p.adj < 0.05). Interaction analyses confirmed this distinct cerebral hemodynamic pattern was statistically different from the patterns of hemorrhagic shock (decreased rBFI, HbO, HbTotal) and hypoxic shock (decreased rBFI, HbO; increased HbR, HbTotal), with significant differences in trends (p.adj < 0.05). Optical biomarkers distinguished the transition to lighter anesthesia from early physiological changes during systemic insults, suggesting discriminative capability beyond severe shock states. Conclusions: These findings demonstrate that a DCS-NIRS system provides quantitative biomarkers capable of distinguishing changes in anesthetic depth from specific, controlled systemic insults causing subtle to severe hemodynamic instability, supporting its potential as a robust tool for improving intraoperative monitoring and patient safety.