Oscillometric techniques are the established standard for non-invasively determining blood pressure. Several algorithms exist for translating oscillometric cardiac waveforms to blood pressure values. These algorithms utilize features of the oscillometric blood pressure waveform to extract systolic and diastolic pressures. Though validated empirically, these features remain contested and are somewhat detached from physiology. The accuracy of current algorithms therefore varies on a patient-to-patient basis and especially declines in non-normotensive patients. We propose an alternative technique based on the assertion that, during cuff deflation following arm occlusion, reperfusion begins when cuff pressure equals systolic pressure. This reperfusion process manifests in relative oxyhemoglobin changes (∆HbO). We measure these changes via near-infrared spectroscopy (NIRS) and show that they produce a more accurate estimate of systolic pressure than existing oscillometric methods.
Intracranial pressure (ICP) measurements help monitor patient status following cerebral injury, and currently require implantation of an invasive pressure probe. The potential complications associated with this implantation have restricted the application of ICP measurements in less severe conditions. We propose a non-invasive alternative that derives features from the cardiac waveforms present in near-infrared spectroscopy (NIRS) measurements and inputs these features into a decision tree regressor to estimate ICP. We evaluated this method in nine subjects already fitted with invasive ICP sensors. The non-invasive nature of NIRS instrumentation eases the clinical adoption of this ICP estimation approach.
SignificanceIntracranial pressure (ICP) measurements are important for patient treatment but are invasive and prone to complications. Noninvasive ICP monitoring methods exist, but they suffer from poor accuracy, lack of generalizability, or high cost.AimWe previously showed that cerebral blood flow (CBF) cardiac waveforms measured with diffuse correlation spectroscopy can be used for noninvasive ICP monitoring. Here we extend the approach to cardiac waveforms measured with near-infrared spectroscopy (NIRS).ApproachChanges in hemoglobin concentrations were measured in eight nonhuman primates, in addition to invasive ICP, arterial blood pressure, and CBF changes. Features of average cardiac waveforms in hemoglobin and CBF signals were used to train a random forest (RF) regressor.ResultsThe RF regressor achieves a cross-validated ICP estimation of 0.937r2, 2.703-mmHg2 mean squared error (MSE), and 95% confidence interval (CI) of [ − 3.064 3.160 ] mmHg on oxyhemoglobin concentration changes; 0.946r2, 2.301-mmHg2 MSE, and 95% CI of [ − 2.841 2.866 ] mmHg on total hemoglobin concentration changes; and 0.963r2, 1.688 mmHg2 MSE, and 95% CI of [ − 2.450 2.397 ] mmHg on CBF changes.ConclusionsThis study provides a proof of concept for the use of NIRS in noninvasive ICP estimation.
Vascular impedance is a frequency dependent quantity relating a vascular compartment's flow dynamics to pressure changes. Although vascular impedance has been investigated in larger arteries using Doppler ultrasound, probing the smaller microvasculature using similar techniques is difficult due to their small cross-sectional area. However, recent developments using diffuse optics have enabled the possibility of measuring blood flow and volume in arterioles and other microvasculature. This research presents a method to estimate the arteriole impedance non-invasively using diffuse correlation spectroscopy (DCS) as well as near-infrared spectroscopy (NIRS).
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