Effect of intracranial pressure on photoplethysmographic waveform in different cerebral perfusion territories: A computational study

Abstract

Background: Intracranial photoplethysmography (PPG) signals can be measured from extracranial sites using wearable sensors and may enable long-term non-invasive monitoring of intracranial pressure (ICP). However, it is still unknown if ICP changes can lead to waveform changes in intracranial PPG signals.Aim: To investigate the effect of ICP changes on the waveform of intracranial PPG signals of different cerebral perfusion territories.Methods: Based on lump-parameter Windkessel models, we developed a computational model consisting three interactive parts: cardiocerebral artery network, ICP model, and PPG model. We simulated ICP and PPG signals of three perfusion territories [anterior, middle, and posterior cerebral arteries (ACA, MCA, and PCA), all left side] in three ages (20, 40, and 60 years) and four intracranial capacitance conditions (normal, 20% decrease, 50% decrease, and 75% decrease). We calculated following PPG waveform features: maximum, minimum, mean, amplitude, min-to-max time, pulsatility index (PI), resistive index (RI), and max-to-mean ratio (MMR).Results: The simulated mean ICPs in normal condition were in the normal range (8.87–11.35 mm Hg), with larger PPG fluctuations in older subject and ACA/PCA territories. When intracranial capacitance decreased, the mean ICP increased above normal threshold (>20 mm Hg), with significant decreases in maximum, minimum, and mean; a minor decrease in amplitude; and no consistent change in min-to-max time, PI, RI, or MMR (maximal relative difference less than 2%) for PPG signals of all perfusion territories. There were significant effects of age and territory on all waveform features except age on mean.Conclusion: ICP values could significantly change the value-relevant (maximum, minimum, and amplitude) waveform features of PPG signals measured from different cerebral perfusion territories, with negligible effect on shape-relevant features (min-to-max time, PI, RI, and MMR). Age and measurement site could also significantly influence intracranial PPG waveform.

Implantable Intracranial Pressure Sensor with Continuous Bluetooth Transmission via Mobile Application

“…The benefits of this device include noninvasive means of measuring ICP and quick triage of patients presenting with acute conditions that may cause elevated ICP, such as trauma. Furthermore, the PPG device is sensitive to environmental factors such as ambient light, noise, and patient specific physiologic parameters, including body size and position, which may affect its reliability [ 19 , 20 ]. For example, the device relies on the arterial pressure to assess ICP; in certain pathologies such as subarachnoid hemorrhage (SAH) with sequela such as vasospasm, cerebral arterial compression may be a distinct physiological process not accurately reflecting ICPs due to disturbance in autoregulatory mechanisms.…”

Research on the Internal Flow Field of Left Atrial Appendage and Stroke Risk Assessment with Different Blood Models

“…Stroke can arise from multiple mechanisms wherein the local hemodynamic environment plays a pivotal role in embolism [ 38 ]. The transport of cardiogenic plaque (i.e., ‘red’ thrombi) depends on the mechanical properties of the cardio-cerebrovascular system [ 39 ]. Thus, future studies could simulate the cardio-cerebrovascular system by using low-dimensional models to obtain more reliable estimates on the risk of embolism and stroke.…”

A Real-Time Deep Learning Approach for Inferring Intracranial Pressure from Routinely Measured Extracranial Waveforms in the Intensive Care Unit

“…Previous research suggested that ICP is regulated by the vascular system, and signatures in electrical, blood pressure, and blood oxygenation waveforms have been associated with intracranial events [10]- [12]. Cerebral autoregulation may be impaired when ICP is elevated, leading to changes in blood flow, vasoreactivity, and oxygenation.…”