Significance: The critical closing pressure (CrCP) of cerebral circulation, as measured by diffuse correlation spectroscopy (DCS), is a promising biomarker of intracranial hypertension. However, CrCP techniques using DCS have not been assessed in gold standard experiments.Aim: CrCP is typically calculated by examining the variation of cerebral blood flow (CBF) during the cardiac cycle (with normal sinus rhythm). We compare this typical CrCP measurement with a gold standard obtained during the drops in arterial blood pressure (ABP) caused by rapid ventricular pacing (RVP) in patients undergoing invasive electrophysiologic procedures.Approach: Adults receiving electrophysiology procedures with planned ablation were enrolled for DCS CBF monitoring. CrCP was calculated from CBF and ABP data by three methods: (1) linear extrapolation of data during RVP (CrCPRVP; the gold standard); (2) linear extrapolation of data during regular heartbeats (CrCPLinear); and (3) fundamental harmonic Fourier filtering of data during regular heartbeats (CrCPFourier).Results: CBF monitoring was performed prior to and during 55 episodes of RVP in five adults. CrCPRVP and CrCPFourier demonstrated agreement (R = 0.66, slope = 1.05 (95%CI, 0.72 to 1.38). Agreement between CrCPRVP and CrCPLinear was worse; CrCPLinear was 8.2 ± 5.9 mmHg higher than CrCPRVP (mean ± SD; p < 0.001).Conclusions: Our results suggest that DCS-measured CrCP can be accurately acquired during normal sinus rhythm.
Monitoring critical closing pressure (CrCP) can be a useful and noninvasive measure of intracranial pressure (ICP), especially in patients with high risk factors for brain injury. We monitored five patients undergoing cardiac ablation procedures using diffuse correlation spectroscopy (DCS). We utilized the prolonged diastolic events that occur during this procedure to validate non-invasive measurements of CrCP with DCS. to estimate the gold standard CrCP during long diastolic events induced during the procedure and compared them to estimations from normal pressure and flow waveforms prior to each event.
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