On the utility of near-infrared spectroscopy-derived measures for assessing cerebrovascular autoregulation: results from an observational cohort study.

Cerebrovascular autoregulation maintains stable cerebral blood flow by counteracting slow changes in cerebral perfusion pressure (termed "slow waves"). Conventional assessment involves invasive techniques using intracranial pressure (ICP) or technically challenging cerebral blood flow velocity (FV) measurements. Near-infrared spectroscopy (NIRS) has emerged as a non-invasive alternative; however, its ability to accurately capture the slow-wave oscillations fundamental to cerebrovascular autoregulation remains uncertain. 412 h of simultaneous ICP, FV, NIRS, and arterial blood pressure (ABP) monitoring from 35 traumatic brain injury patients were explored. Coherence, gain, and Granger causality analyses were employed to assess whether NIRS adequately reflects slow waves in ABP, FV, or ICP to investigate whether NIRS is a suitable alternative for assessing the state of cerebrovascular autoregulation In this single-centre observational cohort study, 89 recordings from 35 moderate to severe traumatic brain injury (TBI) patients (totalling 412 h of artefact-free data) were analysed. Simultaneous high-resolution recordings of NIRS, ICP, FV, and arterial blood pressure (ABP) were acquired. Coherence and gain were computed across defined frequency bands (0.001-0.5 Hz), with a focus on the range most relevant to cerebrovascular autoregulation (0.005-0.05 Hz). Granger causality was used to explore directional relationships between physiological inputs (ABP, FV, ICP) and NIRS outputs (rSO2 and haemoglobin metrics). Haemoglobin-based NIRS metrics (total, oxy-, deoxy-, and delta haemoglobin) demonstrated significantly higher coherence and Granger causality with FV and ICP compared to rSO2 (p < 0.001, large effect sizes) capturing the slow-wave oscillations central to cerebrovascular autoregulation. In contrast, rSO₂ exhibited poor coherence and low causality, especially with ABP, likely due to device-specific post-processing and resolution limitations. NIRS derived haemoglobin metrics reliably capture slow-wave dynamics reflective of cerebrovascular autoregulation and reactivity, offering a non-invasive alternative to traditional methods. Conversely, rSO2 lacks sufficient temporal fidelity to detect these fluctuations under routine clinical conditions, limiting its utility for cerebrovascular autoregulation assessment.