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.
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