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

ABSTRACT: 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.

SUBMITTER: Gomez A

PROVIDER: S-EPMC8602694 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Individualizing mean arterial blood pressure (MAP) based on cerebral blood flow (CBF) autoregulation monitoring during cardiopulmonary bypass (CPB) holds promise as a strategy to optimize organ perfusion. The purpose of this study was to evaluate the accuracy of cerebral autoregulation monitoring using microcirculatory flow measured with innovative ultrasound-tagged near-infrared spectroscopy (UT-NIRS) noninvasive technology compared with transcranial Doppler (TCD).Sixty-four patients undergoing CPB were monitored with TCD and UT-NIRS (CerOx™). The mean velocity index (Mx) was calculated as a moving, linear correlation coefficient between slow waves of TCD-measured CBF velocity and MAP. The cerebral flow velocity index (CFVx) was calculated as a similar coefficient between slow waves of cerebral flow index measured using UT-NIRS and MAP. When MAP is outside the autoregulation range, Mx is progressively more positive. Optimal blood pressure was defined as the MAP with the lowest Mx and CFVx. The right- and left-sided optimal MAP values were averaged to define the individual optimal MAP and were the variables used for analysis.The Mx for the left side was 0.31 ± 0.17 and for the right side was 0.32 ± 0.17. The mean CFVx for the left side was 0.33 ± 0.19 and for the right side was 0.35 ± 0.19. Time-averaged Mx and CFVx during CPB had a statistically significant "among-subject" correlation (r = 0.39; 95% confidence interval [CI], 0.22-0.53; P < 0.001) but had only a modest agreement within subjects (bias 0.03 ± 0.20; 95% prediction interval for the difference between Mx and CFVx, -0.37 to 0.42). The MAP with the lowest Mx and CFVx ("optimal blood pressure") was correlated (r = 0.71; 95% CI, 0.56-0.81; P < 0.0001) and was in modest within-subject agreement (bias -2.85 ± 8.54; 95% limits of agreement for MAP predicted by Mx and CFVx, -19.60 to 13.89). Coherence between ipsilateral middle CBF velocity and cerebral flow index values averaged 0.61 ± 0.07 (95% CI, 0.59-0.63).There was a statistically significant correlation and agreement between CBF autoregulation monitored by CerOx compared with TCD-based Mx.

Dataset Information

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

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