Assessment of cerebral autoregulation using time-domain cross-correlation analysis

Advanced Cross-Correlation Function Application to Identify Arterial Baroreflex Sensitivity Variations From Healthy to Diabetes Mellitus

Diabetes mellitus (DM) is a chronic disease characterized by elevated blood glucose levels, which leads over time to serious damage to the heart, blood vessels, eyes, kidneys, and nerves. DM is of two types–types 1 or 2. In type 1, there is a problem with insulin secretion, and in type 2–insulin resistance. About 463 million people worldwide have diabetes, and 80% of the majority live in low- and middle-income countries, and 1.5 million deaths are directly attributed to diabetes each year. Autonomic neuropathy (AN) is one of the common diabetic complications, leading to failure in blood pressure (BP) control and causing cardiovascular disease. Therefore, early detection of AN becomes crucial to optimize treatment. We propose an advanced cross-correlation function (ACCF) between BP and heart rate with suitable threshold parameters to analyze and detect early changes in baroreflex sensitivity (BRS) in DM with AN (DM+). We studied heart rate (HR) and systolic BP responses during tilt in 16 patients with diabetes mellitus only (DM−), 19 diabetes mellitus with autonomic dysfunction (DM+), and 10 healthy subjects. The ACCF analysis revealed that the healthy and DM groups had different filtered percentages of significant maximum cross-correlation function (CCF) value (p < 0.05), and the maximum CCF value after thresholds was significantly reduced during tilt in the DM+ group (p < 0.05). The maximum CCF index, a parameter for the phase between HR and BP, separated the healthy group from the DM groups (p < 0.05). Due to the maximum CCF index in DM groups being located in the positive range and significantly different from healthy ones, it could be speculated that BRS dysfunction in DM and AN could cause a phase change from lead to lag. ACCF could detect and separate DM+ from DM groups. This fact could represent an advantage of the ACCF algorithm. A common cross-correlation analysis was not easy to distinguish between DM− and DM+. This pilot study demonstrates that ACCF analysis with suitable threshold parameters could explore hidden changes in baroreflex control in DM+ and DM−. Furthermore, the superiority of this ACCF algorithm is useful in distinguishing whether AN is present or not in DM.

Hypertension and Stroke Cardiovascular Control Evaluation by Analyzing Blood Pressure, Cerebral Blood Flow, Blood Vessel Resistance and Baroreflex

Cardiovascular diseases have been the leading causes of mortality in Taiwan and the world at large for decades. The composition of cardiovascular and cerebrovascular systems is quite complicated. Therefore, it is difficult to detect or trace the related signs of cardiovascular and cerebrovascular diseases. The characteristics and changes in cardiopulmonary system disease can be used to track cardiovascular and cerebrovascular disease prevention and diagnosis. This can effectively reduce the occurrence of cardiovascular and cerebrovascular diseases. This study analyzes the variability in blood pressure, cerebral blood flow velocity and the interaction characteristics using linear and nonlinear approaches in stroke, hypertension and healthy groups to identify the differences in cardiovascular control in these groups. The results showed that the blood pressure and cerebral blood flow of stroke patients and hypertensive patients were significantly higher than those of healthy people (statistical differences (p < 0.05). The cerebrovascular resistance (CVR) shows that the CVR of hypertensive patients is higher than that of healthy people and stroke patients (p < 0.1), indicating that the cerebral vascular resistance of hypertensive patients is slightly higher. From the patient's blood flow and vascular characteristics, it can be observed that the cardiovascular system is different from those in healthy people. Baroreflex sensitivity (BRS) decreased in stroke patients (p < 0.05). Chaotic analysis revealed that the blood pressure disturbance in hypertensive patients has a higher chaotic behavior change and the difference in initial state sensitivity. Cross-correlation (CCF) analysis shows that as the course of healthy→hypertension→stroke progresses, the maximum CCF value decreases significantly (p < 0.05). That means that blood pressure and cerebral blood flow are gradually not well controlled by the self-regulation mechanism. In conclusion, cardiovascular control performance in hypertensive and stroke patients displays greater variation. This can be observed by the bio-signal analysis. This analysis could identify a measure for detecting and preventing the risk for hypertension and stroke in clinical practice. This is a pilot study to analyze cardiovascular control variation in healthy, hypertensive and stroke groups.

Comparisons of the Nonlinear Relationship of Cerebral Blood Flow Response and Cerebral Vasomotor Reactivity to Carbon Dioxide under Hyperventilation between Postural Orthostatic Tachycardia Syndrome Patients and Healthy Subjects

Postural orthostatic tachycardia syndrome (POTS) typically occurs in youths, and early accurate POTS diagnosis is challenging. A recent hypothesis suggests that upright cognitive impairment in POTS occurs because reduced cerebral blood flow velocity (CBFV) and cerebrovascular response to carbon dioxide (CO₂) are nonlinear during transient changes in end-tidal CO₂ (P_ETCO2). This novel study aimed to reveal the interaction between cerebral autoregulation and ventilatory control in POTS patients by using tilt table and hyperventilation to alter the CO₂ tension between 10 and 30 mmHg. The cerebral blood flow velocity (CBFV), partial pressure of end-tidal carbon dioxide (P_ETCO2), and other cardiopulmonary signals were recorded for POTS patients and two healthy groups including those aged >45 years (Healthy-Elder) and aged <45 years (Healthy-Youth) throughout the experiment. Two nonlinear regression functions, Models I and II, were applied to evaluate their CBFV-P_ETCO2 relationship and cerebral vasomotor reactivity (CVMR). Among the estimated parameters, the curve-fitting Model I for CBFV and CVMR responses to CO₂ for POTS patients demonstrated an observable dissimilarity in CBFV_max (p = 0.011), mid-P_ETCO2 (p = 0.013), and P_ETCO2 range (p = 0.023) compared with those of Healthy-Youth and in CBFV_max (p = 0.015) and CVMR_max compared with those of Healthy-Elder. With curve-fitting Model II for POTS patients, the fit parameters of curvilinear (p = 0.036) and P_ETCO2 level (p = 0.033) displayed significant difference in comparison with Healthy-Youth parameters; range of change (p = 0.042), P_ETCO2 level, and CBFV_max also displayed a significant difference in comparison with Healthy-Elder parameters. The results of this study contribute toward developing an early accurate diagnosis of impaired CBFV responses to CO₂ for POTS patients.

Changes of cerebral regional oxygen saturation during pneumoperitoneum and Trendelenburg position under propofol anesthesia: a prospective observational study

BACKGROUND

We evaluated the change of cerebral regional tissue oxygen saturation (rSO₂) along with the pneumoperitoneum and the Trendelenburg position. We also assessed the relationship between the change of rSO₂ and the changes of mean arterial blood pressure (MAP), heart rate (HR), arterial carbon dioxide tension (PaCO₂), arterial oxygen tension (PaO₂), or arterial oxygen saturation (SaO₂).

METHODS

Forty-one adult patients who underwent a robotic assisted endoscopic prostatic surgery under propofol and remifentanil anesthesia were involved in this study. During the surgery, a pneumoperitoneum was established using carbon dioxide. Measurements of rSO₂, MAP, HR, PaCO₂, PaO₂, and SaO₂ were performed before the pneumoperitoneum (baseline), every 5 min after the onset of pneumoperitoneum, before the Trendelenburg position. After the onset of the Trendelenburg position, rSO₂, MAP, HR were recorded at 5, 10, 20, 30, 45, and 60 min, and PaCO₂, PaO₂, and SaO₂ were measured at 10, 30, and 60 min.

RESULTS

Before the pneumoperitoneum, left and right rSO₂ were 67.9 ± 6.3% and 68.5 ± 7.0%. Ten minutes after the onset of pneumoperitoneum, significant increase in the rSO₂ was observed (left: 69.6 ± 5.9%, right: 70.6 ± 7.4%). During the Trendelenburg position, the rSO₂ increased initially and peaked at 5 min (left: 72.2 ± 6.5%, right: 73.1 ± 7.6%), then decreased. Multiple regression analysis showed that change of rSO₂ correlated with MAP and PaCO₂.

CONCLUSIONS

Pneumoperitoneum and the Trendelenburg position in robotic-assisted endoscopic prostatic surgery did not worsen cerebral oxygenation. Arterial blood pressure is the critical factor in cerebral oxygenation.

TRIAL REGISTRATION

Japan Primary Registries Network (JPRN); UMIN-CTR ID; UMIN000026227 (retrospectively registered).

Neural Vascular Mechanism for the Cerebral Blood Flow Autoregulation after Hemorrhagic Stroke

During the initial stages of hemorrhagic stroke, including intracerebral hemorrhage and subarachnoid hemorrhage, the reflex mechanisms are activated to protect cerebral perfusion, but secondary dysfunction of cerebral flow autoregulation will eventually reduce global cerebral blood flow and the delivery of metabolic substrates, leading to generalized cerebral ischemia, hypoxia, and ultimately, neuronal cell death. Cerebral blood flow is controlled by various regulatory mechanisms, including prevailing arterial pressure, intracranial pressure, arterial blood gases, neural activity, and metabolic demand. Evoked by the concept of vascular neural network, the unveiled neural vascular mechanism gains more and more attentions. Astrocyte, neuron, pericyte, endothelium, and so forth are formed as a communicate network to regulate with each other as well as the cerebral blood flow. However, the signaling molecules responsible for this communication between these new players and blood vessels are yet to be definitively confirmed. Recent evidence suggested the pivotal role of transcriptional mechanism, including but not limited to miRNA, lncRNA, exosome, and so forth, for the cerebral blood flow autoregulation. In the present review, we sought to summarize the hemodynamic changes and underline neural vascular mechanism for cerebral blood flow autoregulation in stroke-prone state and after hemorrhagic stroke and hopefully provide more systematic and innovative research interests for the pathophysiology and therapeutic strategies of hemorrhagic stroke.

Sympathetic regulation of the human cerebrovascular response to carbon dioxide

Although the cerebrovasculature is known to be exquisitely sensitive to CO2, there is no consensus on whether the sympathetic nervous system plays a role in regulating cerebrovascular responses to changes in arterial CO2. To address this question, we investigated human cerebrovascular CO2 reactivity in healthy participants randomly assigned to the α1-adrenoreceptor blockade group (9 participants; oral prazosin, 0.05 mg/kg) or the placebo control (9 participants) group. We recorded mean arterial blood pressure (MAP), heart rate (HR), mean middle cerebral artery flow velocity (MCAV mean), and partial pressure of end-tidal CO2 (PetCO2) during 5% CO2 inhalation and voluntary hyperventilation. CO2 reactivity was quantified as the slope of the linear relationship between breath-to-breath PetCO2 and the average MCAvmean within successive breathes after accounting for MAP as a covariate. Prazosin did not alter resting HR, PetCO2, MAP, or MCAV mean. The reduction in hypocapnic CO2 reactivity following prazosin (−0.48 ± 0.093 cm·s−1·mmHg−1) was greater compared with placebo (−0.19 ± 0.087 cm·s−1·mmHg−1; P < 0.05 for interaction). In contrast, the change in hypercapnic CO2 reactivity following prazosin (−0.23 cm·s−1·mmHg−1) was similar to placebo (−0.31 cm·s−1·mmHg−1; P = 0.50 for interaction). These data indicate that the sympathetic nervous system contributes to CO2 reactivity via α1-adrenoreceptors; blocking this pathway with prazosin reduces CO2 reactivity to hypocapnia but not hypercapnia.

Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes

Cerebral Flow Autoregulation (CFA) is the dynamic process by which cerebral blood flow is maintained within physiologically acceptable bounds during fluctuations of cerebral perfusion pressure. The distinction is made with “static” flow autoregulation under steady-state conditions of perfusion pressure, described by the celebrated “autoregulatory curve” with a homeostatic plateau. This paper studies the dynamic CFA during changes in perfusion pressure, which attains critical clinical importance in patients with stroke, traumatic brain injury and neurodegenerative disease with a cerebrovascular component. Mathematical and computational models have been used to advance our quantitative understanding of dynamic CFA and to elucidate the underlying physiological mechanisms by analyzing the relation between beat-to-beat data of mean arterial blood pressure (viewed as input) and mean cerebral blood flow velocity(viewed as output) of a putative CFA system. Although previous studies have shown that the dynamic CFA process is nonlinear, most modeling studies to date have been linear. It has also been shown that blood CO2 tension affects the CFA process. This paper presents a nonlinear modeling methodology that includes the dynamic effects of CO2 tension (or its surrogate, end-tidal CO2) as a second input and quantifies CFA from short data-records of healthy human subjects by use of the modeling concept of Principal Dynamic Modes (PDMs). The PDMs improve the robustness of the obtained nonlinear models and facilitate their physiological interpretation. The results demonstrate the importance of including the CO2 input in the dynamic CFA study and the utility of nonlinear models under hypercapnic or hypocapnic conditions.

Linear and nonlinear modeling of cerebral flow autoregulation using principal dynamic modes

Cerebral Flow Autoregulation (CFA) is the dynamic process by which cerebral blood flow is maintained within physiologically acceptable bounds during fluctuations of cerebral perfusion pressure. The distinction is made with “static” flow autoregulation under steady-state conditions of perfusion pressure, described by the celebrated “autoregulatory curve” with a homeostatic plateau. This paper studies the dynamic CFA during changes in perfusion pressure, which attains critical clinical importance in patients with stroke, traumatic brain injury and neurodegenerative disease with a cerebrovascular component. Mathematical and computational models have been used to advance our quantitative understanding of dynamic CFA and to elucidate the underlying physiological mechanisms by analyzing the relation between beat-to-beat data of mean arterial blood pressure (viewed as input) and mean cerebral blood flow velocity(viewed as output) of a putative CFA system. Although previous studies have shown that the dynamic CFA process is nonlinear, most modeling studies to date have been linear. It has also been shown that blood CO2 tension affects the CFA process. This paper presents a nonlinear modeling methodology that includes the dynamic effects of CO2 tension (or its surrogate, end-tidal CO2) as a second input and quantifies CFA from short data-records of healthy human subjects by use of the modeling concept of Principal Dynamic Modes (PDMs). The PDMs improve the robustness of the obtained nonlinear models and facilitate their physiological interpretation. The results demonstrate the importance of including the CO2 input in the dynamic CFA study and the utility of nonlinear models under hypercapnic or hypocapnic conditions.

Intraaortic Balloon Pump Counterpulsation and Cerebral Autoregulation: an observational study

Background

The use of Intra-aortic counterpulsation is a well established supportive therapy for patients in cardiac failure or after cardiac surgery. Blood pressure variations induced by counterpulsation are transmitted to the cerebral arteries, challenging cerebral autoregulatory mechanisms in order to maintain a stable cerebral blood flow. This study aims to assess the effects on cerebral autoregulation and variability of cerebral blood flow due to intra-aortic balloon pump and inflation ratio weaning.

Methods

Cerebral blood flow was measured using transcranial Doppler, in a convenience sample of twenty patients requiring balloon counterpulsation for refractory cardiogenic shock (N = 7) or a single inotrope to maintain mean arterial pressure following an elective placement of an intra-aortic balloon pump for cardiac surgery (N = 13). Simultaneous blood pressure at the aortic root was recorded via the intra-aortic balloon pump. Cerebral blood flow velocities were recorded for six minute intervals at a 1:1 balloon inflation-ratio (augmentation of all cardiac beats) and during progressive reductions of the inflation-ratio to 1:3 (augmentation of one every third cardiac beat). Real time comparisons of peak cerebral blood flow velocities with systolic blood pressure were performed using cross-correlation analysis. The primary endpoint was assessment of cerebral autoregulation using the time delay between the peak signals for cerebral blood flow velocity and systolic blood pressure, according to established criteria. The variability of cerebral blood flow was also assessed using non-linear statistics.

Results

During the 1:1 inflation-ratio, the mean time delay between aortic blood pressure and cerebral blood flow was -0.016 seconds (95% CI: -0.023,-0.011); during 1:3 inflation-ratio mean time delay was significantly longer at -0.010 seconds (95% CI: -0.016, -0.004, P < 0.0001). Finally, upon return to a 1:1 inflation-ratio, time delays recovered to those measured at baseline. During inflation-ratio reduction, cerebral blood flow irregularities reduced over time, whilst cerebral blood flow variability at end-diastole decreased in patients with cardiogenic shock.

Conclusions

Weaning counterpulsation from 1:1 to 1:3 inflation ratio leads to a progressive reduction in time delays between systolic blood pressure and peak cerebral blood flow velocities suggesting that although preserved, there is a significant delay in the establishment of cerebral autoregulatory mechanisms. In addition, cerebral blood flow irregularities (i.e. surrogate of flow adaptability) decrease and a loss of cerebral blood flow chaotic pattern occurs during the end-diastolic phase of each beat in patients with cardiogenic shock.

Transcranial Doppler assessment of cerebral autoregulation

Cerebral autoregulation describes the process by which cerebral blood flow is maintained despite fluctuations in cerebral perfusion pressure. The assessment of cerebral autoregulation is a key to the optimisation of cerebral perfusion pressure in patients with brain injury. This review evaluates the current evidence for transcranial Doppler in the assessment of cerebral autoregulation. The study of cerebral autoregulation classically assesses changes in cerebral perfusion pressure secondary to changes in systemic blood pressure. It is defined static autoregulation if blood pressure changes are progressive, thereby allowing a steady-state autoregulatory response to be completed. For sudden changes in blood pressure, the autoregulatory response is defined as dynamic. The static and dynamic components of cerebral autoregulation have been approached using linear mathematical models (models based in direct correlations). Over the past decade, demonstration of the nonstationary (the property of changing over time or space) behaviour of cerebral autoregulation has emphasised the benefit obtained in using nonlinear statistical models (models based on changeable functions), suggesting that these methods may improve the mathematical representation of cerebral autoregulation. Despite the multiple determinants involved in cerebral autoregulation, it appears feasible to reliably assess cerebral autoregulation through the combination of linear and nonlinear methods. Nonlinear methods appear attractive in the research setting, but the challenge is how to adopt these methods to the clinical setting.

Dynamic cerebral autoregulation assessment using chaotic analysis in diabetic autonomic neuropathy

Cerebral autoregulation (CA) was assessed by chaotic analysis based on mean arterial blood pressure (MABP) and mean cerebral blood flow velocity (MCBFV) in 19 diabetics with autonomic neuropathy (AN) and 11 age-matched normal subjects. MABP in diabetics dropped significantly in response to tilting (91.6 +/- 14.9 vs. 74.1 +/- 13.4 mmHg, P < 0.05). Valsalva ratio of heart rate was reduced in diabetics compared to normal (1.1 +/- 0.1 vs. 1.5 +/- 0.2, P < 0.05). It indicated AN affects the vasomotor tone of peripheral vessels and baroreflex. Nonlinear results showed higher correlation dimension values of MABP and MCBFV in diabetics compared to normal, especially MABP (3.7 +/- 2.3 vs. 2.0 +/- 0.8, P < 0.05). It indicated CA is more complicated in diabetics. The lower Lyapunov exponent and the higher Kolmogorov entropy values in diabetics indicated less predictable behavior and higher chaotic degree. This study suggests impaired autoregulation would be more chaotic and less predictable.

Combined transfer function analysis and modelling of cerebral autoregulation

The clinical importance of cerebral autoregulation has resulted in a significant body of literature that attempts both to model the underlying physiological processes and to estimate the mathematical relationships between clinically measurable variables, the most common of which are Arterial Blood Pressure and Cerebral Blood Flow Velocity. These approaches have, however, rarely been used together to interpret clinical data. A simple model of cerebral autoregulation is thus proposed here, based on a flow dependent feedback mechanism with gain and time constant that adjusts arterial compliance. Analysis of this model shows that it closely approximates a second order system for typical values of physiological parameters. The model parameters can be optimally estimated from available experimental data for the Impulse Response (IR), yielding physiologically reasonable values, although there is one free parameter that must be fixed. The effects of changes in feedback gain and time constant are found to be significant on the predicted IR and can thus be estimated robustly from experimental data. The effects of elevated baseline Intracranial Pressure (ICP) are found to be exactly equivalent to a reduced feedback gain, although the solution is much less sensitive to the former effect. A transfer function approach can be used to estimate autoregulation status clinically using a physiologically-based model, thus providing greater insight into the processes that govern cerebral autoregulation.

Time domain correlation analysis of heart rate variability in preterm neonates

BACKGROUND AND AIM

A fuller understanding of the neural control mechanisms of heart rate during the early stages of human development would be of great value to obstetric and neonatal management. In this paper, we investigate the correlation between heart rate variability (HRV) and other physiological parameters such as blood pressure and respiration in preterm neonates with the aim of developing a numerical model to explain and predict heart rate variability.

STUDY DESIGN AND SUBJECTS

All the required data are readily available for premature babies who are routinely monitored while being nursed in intensive care, and we have collected large data sets for a random group of such neonates. For the quantitative analysis of the data, we have developed a time domain correlation method, which has a number of advantages over the more commonly used power spectral analysis. We have been able to study the dynamics of the different frequency components of HRV by this method.

RESULTS

Highly correlated behaviour of the different HRV components, previously observed in our work on fetal HRV, is also present in the neonate, with similar characteristic time constants. Furthermore, the correlation of high-frequency (HF) oscillations of HRV with respiration and that of low-frequency (LF) oscillations of HRV with blood pressure are demonstrated on timescales of a single oscillation. In neonates receiving artificial ventilation, the correlation between HRV and respiration depends on the type of ventilation involved and assumes opposite polarities for the two main types of equipment currently in use.

CONCLUSION

We demonstrate that it is possible to analyse HRV quantitatively by calculating the relative gains and characteristic time constants for the correlated parameters and components.