Ensuring signal quality of cerebral near infrared spectroscopy during continuous longterm monitoring.

BACKGROUND

Near infrared spectroscopy (NIRS) derived hemoglobin difference (HbD: oxygenated [HbO2] - reduced hemoglobin [Hb]) and total hemoglobin (HbT: HbO2+Hb) have been used as surrogate measures of cerebral blood flow and volume, respectively. Statistically, a lack of HbD-blood pressure (BP) or negative HbT-BP association is regarded as a state of intact cerebral pressure autoregulation (CPA). In contrast, a co-variation of HbD/HbT and systemic blood pressure (BP) in the same direction is thought of as a failure of CPA. If the quality of one (NIRS/BP) or both signals is compromised, the reliability of the results may be adversely affected. In this work, we develop an analytic approach to assess the quality of the NIRS signals.

NEW METHOD

Given that cardiac pulses cause hemodynamic changes that are transmitted through the peripheral vasculature, cerebral NIRS signals should exhibit cyclical changes at the pulse frequency. Therefore, we propose that an association between HbD/HbT and electrocardiogram (EKG) signals would be an indicator of NIRS quality. We demonstrate the application of this approach with data collected from six newborns undergoing therapeutic hypothermia for neonatal encephalopathy.

RESULTS

We observed an intermittent lack of association between NIRS signals and EKG data over the course of several hours of continuous records, indicating a loss in the strength in NIRS signals.

COMPARISON WITH EXISTING METHOD

Existing CPA characterization suffers from Type-II error which the current preprocessing approach can mitigate.

CONCLUSIONS

The proposed approach will allow for real-time assessment of NIRS signal quality that is essential for accurate CPA monitoring.