Blood Flow Velocity Signals Research Articles

Quantitative analysis of similarity between cerebral arterial blood volume and intracranial pressure pulse waveforms during intracranial pressure plateau waves

IntroductionBoth intracranial pressure (ICP) and cerebral arterial blood volume (CaBV) have a pulsatile character related to the cardiac cycle. The evolution of the shape of ICP pulses under increasing ICP or decreasing intracranial compliance is well documented. Nevertheless, the exact origin of the alterations in the ICP morphology remains unclear. Research questionDoes ICP pulse waveform become similar to non-invasively estimated CaBV pulse during ICP plateau waves. Material and methodsA total of 15 plateau waves recorded in 15 traumatic brain injured patients were analyzed. CaBV pulse waveforms were calculated using global cerebral blood flow model from transcranial Doppler cerebral blood flow velocity (CBFV) signals. The difference index (DI) was used to quantify the similarity between ICP and CaBV waveforms. DI was calculated as the sum of absolute sample-by-sample differences between ICP and CaBV waveforms, representing the area between the pulses. ResultsICP increased (19.4 mm Hg [Q1–Q3: 18.2–23.4 mm Hg] vs. 42.7 mm Hg [Q1–Q3: 36.5–45.1 mm Hg], p < 0.001) while CBFV decreased (44.2 cm/s [Q1–Q3: 34.8–69.5 cm/s] vs. 32.9 cm/s [Q1–Q3: 24.7–68.2 cm/s], p = 0.002) during plateau waves. DI was smaller during the plateau waves (20.4 [Q1–Q3: 15.74–23.0]) compared to the baselines (26.3 [Q1–Q3: 24.2–34.7], p < 0.001). Discussion and conclusionThe area between corresponding ICP and CaBV pulse waveforms decreased during the plateau waves which suggests they became similar in shape. CaBV may play a significant role in determining the shape of ICP pulses during the plateau waves and might be a driving force in formulating ICP elevation.

Worse glycemic control is associated with an impaired arterial energy transfer pattern in elderly with diabetes

Abstract Background Worse glycaemic control is known to exacerbate endothelial insult, increasing macro- and microvascular complication risks in diabetes. Impaired intracranial haemodynamics have been frequently reported in patients with diabetes alongside with malperfusion causing structural abnormalities, and poor cognitive and cortical functionality (1-2).Assessment of the alterations in energy transfer characteristics derived from hemodynamic signals may provide novel mechanistic information about how worse glycaemic control may affect cerebrovascular perfusion. Wave reflection index(WRI) is a previously proposed measure of arterial energy transfer efficiency which reflects distal impedance mismatch(3-4). Purpose We aim to interrogate potential relationship between a worse glycaemic control and a less efficient arterial energy transfer, which could enhance our understanding of the cerebrovascular-cortical functional coupling on a mechanistic basis in elderly with diabetes. Methods Left middle cerebral artery wave intensity (WI) was computed with arterial blood pressure and flow velocity (transcranial Doppler) signal as previously described (WI = (dP/dt)*(dU/dt)) (Figure 1). Standard statistical tests were used to interrogate the relationship between glycated haemoglobin levels (HbA1c) and WI parameters. Results In 36 patients with diabetes mellitus type-2 (DM2) (mean age = 65.7 ± 8.8 years), backward compression wave intensity (BCWI) and wave reflection ratio (WRI= BCWI/FCWI) were significantly correlated with HbA1c levels before (rBCWI: 0.409 pBCWI:0.013; rWRI:0.345 pWRI:0.040) and after (rBCWI: 0.410 pBCWI:0.018, rWRI:0.351 pWRI:0.045) adjusting for age, sex and mean arterial pressure (Figure 2). Conclusion(s) In elderly patient with DM2, higher HbA1c values indicating worse glycaemic control are significantly correlated with altered cerebrovascular energy transfer characteristics as assessed by MCA wave intensity analysis. Continuous relationship between worse glycaemic control and higher wave reflection index (a measure of less efficient energy transfer in arterial system and distal impedance mismatch) may imply that the use of energy transfer related indices alongside with conventional hemodynamic indices may help providing a more comprehensive pathophysiological understanding about how cardiovascular risk factors interfere with perfusion.Computation of Wave IntensityMain Results

Brain blood flow pulse analysis may help to recognize individuals who suffer from hydrocephalus

BackgroundNormal pressure hydrocephalus (NPH) is often associated with altered cerebral blood flow. Recent research with the use of the ultrasonic method suggests specific changes in the shape of cardiac-related cerebral arterial blood volume (CaBV) pulses in NPH patients. Our study aims to provide a quantitative analysis of the shape of CaBV pulses, estimated based on transcranial Doppler ultrasonography (TCD) in NPH patients and healthy individuals.MethodsThe CaBV pulses were estimated using TCD cerebral blood flow velocity signals recorded from probable NPH adults and age-matched healthy individuals at rest. The shape of the CaBV pulses was compared to a triangular shape with 27 similarity parameters calculated for every reliable CaBV pulse and compared between patients and volunteers. The diagnostic accuracy of the most prominent parameter for NPH classification was evaluated using the area under the receiver operating characteristic curve (AUC).ResultsThe similarity parameters were calculated for 31 probable NPH patients (age: 59 years (IQR: 47, 67 years), 14 females) and 23 healthy volunteers (age: 54 years (IQR: 43, 61 years), 18 females). Eighteen of 27 parameters were different between healthy individuals and NPH patients (p < 0.05). The most prominent differences were found for the ascending slope of the CaBV pulse with the AUC equal to 0.87 (95% confidence interval: 0.77, 0.97, p < 0.001).ConclusionsThe findings suggest that in NPH, the ascending slope of the CaBV pulse had a slower rise, was more like a straight line, and generally was less convex than in volunteers. Prospective research is required to verify the clinical utility of these findings.

Abstract Number ‐ 244: Feasibility of Detecting Carotid Stenosis Microemboli Using Autonomous Robotic TCD at a Large Stroke Center

Introduction There is accumulating evidence that the presence of microembolic signals(MES) could be an independent risk factor and marker for future stroke or TIA. These signals detected by ultrasound represent small particles (platelets,plaque,fibrinogen) too small to cause a neurologic deficit, but can be a warning of a larger particle dislodging and blocking an intracranial artery. Transcranial doppler (TCD) studies are historically small. Few technicians have the specialized training to perform them and experienced users often have difficulty obtaining an adequate echogenic window. This study utilizes an autonomous robotic transcranial doppler (aTCD), driven by artificial intelligence to obtain and optimize the cerebral blood flow velocity signal. This tool makes data acquisition more efficient thus increasing analytical power through ease in obtaining larger sample sizes. This study focuses on the process of integrating such a tool. Complex vascular cases can utilize such a tool for patients on the borderline of needing a carotid stent or endarterectomy to help ensure the selection of optimal surgical candidates through better risk assessment methods. Methods NovaGuide™ 2 Intelligent Ultrasound (NovaSignal Corp. USA) was utilized to scan patients for microembolic signals that met our criteria. Our population consisted of male and female inpatients that were at least 18 years old at a single center with a CTA head and neck that revealed 50% or greater internal carotid artery stenosis for patients with neurological symptoms that could be associated with this artery. For patients that were asymptomatic with an incidental finding of internal carotid artery stenosis, we included 60% or greater stenosis. Stenosis was measured by NASCET criteria. If a patient received a stent or carotid endarterectomy during their hospitalization, a microembolic scan was obtained before and after their procedure if the initial scan was positive. Scans were performed for at least 30 minutes if the patient could tolerate this. Results Data collection is ongoing with a plan to scan 20 patients from July 2022 to October 2022, but the initial 12 patients revealed no MES which is contrary to the rate found in other studies. Potential confounders include antiplatelet and anticoagulation use as these were not delayed if clinically warranted. All cases were symptomatic and carotid stenosis ranged from 50% to 99%. A request for echo technician feedback is pending, but initial comments have revealed 30 minutes to be the maximum time feasible at our institution. Conclusions The aTCD has shown in a prospective study (NCT04604015) that data can be collected by non experts. Our study demonstrates that such a tool can be integrated into a large stroke center by echo technicians not formally trained in manual TCD. Utilization of technologies that allow for simplified data collection can help power larger TCD studies to explore its use as a risk utilization tool. This can help with selection of ideal surgical candidates for carotid stent and endarterectomy as an additional data point in their overall case. The significance of MES requires further investigation, but studies utilizing conventional TCD support MES being a risk factor for stroke and TIA.

Investigation of Cerebral Autoregulation Using Time-Frequency Transformations.

The authors carried out the study of the state of systemic and cerebral hemodynamics in normal conditions and in various neurosurgical pathologies using modern signal processing methods. The results characterize the condition for the mechanisms of cerebral circulation Institute of Computer Science and Control, Higher School of Cyber-Physical Systems and Control regulation, which allows for finding a solution to fundamental and specific clinical problems for the effective treatment of patients with various pathologies. The proposed method is based on the continuous wavelet transform of systemic arterial pressure and blood flow velocity signals in the middle cerebral artery recorded by non-invasive methods of photoplethysmography and transcranial doppler ultrasonography. The study of these signals in real-time in the frequency range of Mayer waves makes it possible to determine the cerebral autoregulation state in certain diseases before and after surgical interventions. The proposed method uses a cross-wavelet spectrum, which helps obtain wavelet coherence and a phase shift between the wavelet coefficients of systemic arterial pressure signals and blood flow velocity in the Mayer wave range. The obtained results enable comparing the proposed method with that based on the short-time Fourier transform. The comparison showed that the proposed method has higher sensitivity to changes in cerebral autoregulation and better localization of changes in time and frequency.

Comparison of different metrics of cerebral autoregulation in association with major morbidity and mortality after cardiac surgery

BackgroundCardiac surgery studies have established the clinical relevance of personalised arterial blood pressure management based on cerebral autoregulation. However, variabilities exist in autoregulation evaluation. We compared the association of several cerebral autoregulation metrics, calculated using different methods, with outcomes after cardiac surgery. MethodsAutoregulation was measured during cardiac surgery in 240 patients. Mean flow index and cerebral oximetry index were calculated as Pearson's correlations between mean arterial pressure (MAP) and transcranial Doppler blood flow velocity or near-infrared spectroscopy signals. The lower limit of autoregulation and optimal mean arterial pressure were identified using mean flow index and cerebral oximetry index. Regression models were used to examine associations of area under curve and duration of mean arterial pressure below thresholds with stroke, acute kidney injury (AKI), and major morbidity and mortality. ResultsBoth mean flow index and cerebral oximetry index identified the cerebral lower limit of autoregulation below which MAP was associated with a higher incidence of AKI and major morbidity and mortality. Based on magnitude and significance of the estimates in adjusted models, the area under curve of MAP < lower limit of autoregulation had the strongest association with AKI and major morbidity and mortality. The odds ratio for area under the curve of MAP < lower limit of autoregulation was 1.05 (95% confidence interval, 1.01–1.09), meaning every 1 mm Hg h increase of area under the curve was associated with an average increase in the odds of AKI by 5%. ConclusionsFor cardiac surgery patients, area under curve of MAP < lower limit of autoregulation using mean flow index or cerebral oximetry index had the strongest association with AKI and major morbidity and mortality. Trials are necessary to evaluate this target for MAP management.

Signal Conversion and Isolation Processing Technology Used in the Cerebrovascular Stroke Detector

By using Doppler sensor and pressure sensor, the cerebrovascular stroke detector can be used to measure the blood flow velocity and blood pressure of the carotid artery. In this study, a variety of signal conversion and isolation processing techniques are proposed for processing and feature extraction of the output signals from the sensors. Finally, effective signal output waveforms that can be used to evaluate the cerebrovascular hemodynamics index (CVHI) are obtained, and the sound signal outputs that can reflect the change characteristics of blood flow velocity and blood pressure signals are generated, which realizes the application functional requirements of the detector.

Cerebral Autoregulation Indices Are Not Interchangeable in Patients With Sepsis.

IntroductionDynamic cerebral autoregulation (dCA) is frequently altered in patients with sepsis and may be associated with sepsis-associated brain dysfunction. However, the optimal index to quantify dCA in patients with sepsis is currently unknown.ObjectiveTo assess the agreement between two validated dCA indices in patients with sepsis.MethodsRetrospective analysis of prospectively collected data in patients with sepsis; those with acute or chronic intracranial disease, arrhythmias, mechanical cardiac support, or history of supra-aortic vascular disease were excluded. Transcranial Doppler was performed on the right or left middle cerebral artery (MCA) with a 2-MHz probe, and MCA blood flow velocity (FV) and arterial pressure (BP) signals were simultaneously recorded. We calculated two indices of dCA: the mean flow index (Mxa), which is the Pearson correlation coefficient between BP and FV (MATLAB, MathWorks), and the autoregulation index (ARI), which is the transfer function analysis of spontaneous fluctuations in BP and FV (custom-written FORTRAN code). Impaired dCA was defined as Mxa >0.3 or ARI ≤ 4. The agreement between the two indices was assessed by Cohen's kappa coefficient.ResultsWe included 95 patients (age 64 ± 13 years old; male 74%); ARI was 4.38 [2.83–6.04] and Mxa was 0.32 [0.14–0.59], respectively. There was no correlation between ARI and Mxa (r = −0.08; p = 0.39). dCA was altered in 40 (42%) patients according to ARI and in 50 (53%) patients according to Mxa. ARI and Mxa were concordant in classifying 23 (24%) patients as having impaired dCA and 28 (29%) patients as having intact dCA. Cohen's kappa coefficient was 0.08, suggesting poor agreement. ARI was altered more frequently in patients on mechanical ventilation than others (27/52, 52% vs. 13/43, 30%, p = 0.04), whereas Mxa did not differ between those two groups. On the contrary, Mxa was altered more frequently in patients receiving sedatives than others (23/34, 68% vs. 27/61, 44%, p = 0.03), whereas ARI did not differ between these two groups.ConclusionsAgreement between ARI and Mxa in assessing dCA in patients with sepsis was poor. The identification of specific factors influencing the dCA analysis might lead to a better selection of the adequate cerebral autoregulation (CAR) index in critically ill patients with sepsis.

Artifact rejection and missing data imputation in cerebral blood flow velocity signals via trace norm minimization

Objective: Many physiological signals are degraded by significant corruptions that limit their usefulness. One example is cerebral blood flow velocity (CBFV) signals, measured by transcranial Doppler, which are susceptible to large errors from patient motion. In this paper, we propose a method to remove artifacts and impute sections of missing data in these signals. Approach: The method exploits the low-order dynamical relationship between CBFV, arterial blood pressure and, where available, intracranial pressure. It enhances the measured signals by fitting them to a low-order dynamical model, using convex regularization terms that improve robustness to large deviations and missing data. The method is based on a convex optimization formulation and utilizes recent work in trace norm approximation and subspace system identification. Main results: Simulations demonstrate that the method successfully removes real CBFV artifacts and can impute missing data with reasonable accuracy. Performance was improved when intracranial pressure data was available. Conclusion: The methods presented can be used by researchers to remove artifacts and estimate missing sections in CBFV signals. The general approach may be applied to other biomedical signal processing settings. Significance: This low-order dynamical approach has ongoing applications in noninvasive intracranial pressure estimation.

Determination of cerebral blood flow velocity and microembolic signals in essential thrombocytosis by transcranial doppler ultrasonography

ABSTRACT Objectives The goal of treatment in essential thrombocytosis (ET) is to prevent vascular complications such as thrombosis and hemorrhage. This study aimed to evaluate the risk of cerebrovascular microembolism in ET patients due to detection of microembolic signals (MES) and measure cerebral blood flow velocity (CBFV) by Transcranial Doppler (TCD) ultrasonography. Material and Methods In this prospective case-control study, forty patients with diagnosed ET and age and sex-matched forty healthy controls were examined by the TCD sonography. Results The ET group had a higher rate of MES (8/40) in the right MCA than that in the control group (none), as measured by TCD. Five patients had MES at the left MCA compared to that in no subjects in the control group. The comparison of the ET and control groups in terms of CBFV parameters showed significantly lower end-diastolic FV at the right MCA in the ET group compared to that in the control group (p < 0.05). On the other hand; both pulsatility and resistance indices in the right and left MCA and the ratios of systolic to diastolic blood flow rates in the right and left MCA were significantly higher in the ET group than that in the control group. Discussion This study revealed that MES seems to be more common in patients with ET despite treatment. We could suggest that ET patients should be monitored more closely to address the potential risk of developing a cerebrovascular disease, which can be estimated by detection MES and raised CBFV, combine antiplatelet therapies to standard treatments.

Clinical value of color Doppler ultrasound combined with serum CA153, CEA and TSGF detection in the diagnosis of breast cancer.

In the present retrospective study, the clinical value of color Doppler ultrasound combined with the detection of the serum tumor markers carbohydrate antigen 153 (CA153), carcinoembryonic antigen (CEA) and tumor specific growth factor (TSGF) as diagnostic tools for breast cancer was investigated. A total of 103 patients with breast cancer and 50 patients with benign breast lesions were enrolled in the study. All patients were examined by color Doppler ultrasonography. Electrochemiluminescence was used to measure the expression levels of CA153 and CEA, and chemical colorimetric assay for the measurement of TSGF expression. The differences in mass boundary, morphology, internal echo, calcification, peak blood flow velocity (Vmax), resistance index (RI), pulsatility index (PI) and blood flow signal classification between the two groups were statistically significant (P<0.05). The expression levels of CA153, CEA and TSGF in the serum of patients in the breast cancer group were significantly higher than those in the benign lesion group (P<0.01). In the breast cancer group, CA153, CEA and TSGF expression levels were significantly higher in patients with high-stage cancer and recurrence, compared with the patients with low-stage cancer and no recurrence. The sensitivity, accuracy and negative predictive value of the combined detection were significantly improved compared with those of the single tests (P<0.01). Color Doppler ultrasound combined with the detection of CA153, CEA and TSGF levels in the serum of patients can be used as an effective tool that can improve the accuracy of breast cancer diagnosis leading to early diagnosis and clinical intervention.

Algorithm for Reliable Detection of Pulse Onsets in Cerebral Blood Flow Velocity Signals.

Transcranial Doppler (TCD) ultrasound has been demonstrated to be a valuable tool for assessing cerebral hemodynamics via measurement of cerebral blood flow velocity (CBFV), with a number of established clinical indications. However, CBFV waveform analysis depends on reliable pulse onset detection, an inherently difficult task for CBFV signals acquired via TCD. We study the application of a new algorithm for CBFV pulse segmentation, which locates pulse onsets in a sequential manner using a moving difference filter and adaptive thresholding. The test data set used in this study consists of 92,012 annotated CBFV pulses, whose quality is representative of real world data. On this test set, the algorithm achieves a true positive rate of 99.998% (2 false negatives), positive predictive value of 99.998% (2 false positives), and mean temporal offset error of 6.10 ± 4.75 ms. We do note that in this context, the way in which true positives, false positives, and false negatives are defined caries some nuance, so care should be taken when drawing comparisons to other algorithms. Additionally, we find that 97.8% and 99.5% of onsets are detected within 10 and 30 ms, respectively, of the true onsets. The algorithm's performance in spite of the large degree of variation in signal quality and waveform morphology present in the test data suggests that it may serve as a valuable tool for the accurate and reliable identification of CBFV pulse onsets in neurocritical care settings.

Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability.

Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctuations in blood pressure and cerebral blood flow velocity signals, based on their usual methods of analysis. DCA methods were grouped into three broad categories, depending on output types: (1) transfer function analysis (TFA); (2) autoregulation index (ARI); and (3) correlation coefficient. Only TFA gain in the low frequency (LF) band showed good reproducibility in approximately half of the estimates of gain, defined as an intraclass correlation coefficient (ICC) of >0.6. None of the other DCA metrics had good reproducibility. For TFA-like and ARI-like methods, ICCs were lower than values obtained with surrogate data (p < 0.05). For TFA-like methods, ICCs were lower for the very LF band (gain 0.38 ± 0.057, phase 0.17 ± 0.13) than for LF band (gain 0.59 ± 0.078, phase 0.39 ± 0.11, p ≤ 0.001 for both gain and phase). For ARI-like methods, the mean ICC was 0.30 ± 0.12 and for the correlation methods 0.24 ± 0.23. Based on comparisons with ICC estimates obtained from surrogate data, we conclude that physiological variability or non-stationarity is likely to be the main reason for the poor reproducibility of DCA parameters.

Prediction of syncope with nonlinear dynamic analysis during head-up tilt in vasovagal syncope patients

To quantify the relationship between cerebral blood flow velocity and peripheral blood pressure during hypotension period, aiming to predict the brain hypotension before symptomatic occurrence. Twenty vasovagal syncope (VVS) patients who had a previous clinical history were selected in groups and 20 pair-matched control subjects underwent 70° tilt-up test. The subjects remained supine for 30 minutes before recordings when Doppler probes, electrodes and Finapres device were prepared. After continuous baseline recordings for 10 min, the subjects underwent head up tilt (HUT) test (70°), and were standing upright for 30 minutes or until syncope was imminent. For ethical reasons, the subjects were turned back to supine position immediately after SBP dropped to ≥20 mmHg, when their consciousness persisted. The point of syncope was synchronized for all the subjects by the point SBP reached the minima. Their beat-to-beat blood pressures (BP) were recorded continuously and bilateral middle cerebral artery (MCA) flow velocities were obtained with two 2 MHz Doppler probes from a transcranial Doppler ultrasonography (TCD) system. A nonlinear dynamic method--multimodal pressure flow (MMPF) analysis was introduced to access cerebral autoregulation during different time intervals. We introduced a new indicator--syncope index (SI), which was extracted from blood flow velocity (BFV) signal to evaluate the variation of cerebral vascular tension, and could reflect the deepness of dicrotic notch in BFV signal. Compared with the syncope index of the baseline value at the beginning of the tilt test, SI in VVS group showed significantly lower when the VVS occurred (0.16±0.10 vs.0.27±0.10,P<0.01),while there was no significant difference in syncope index between the control group at the end of the tilt test and the baseline value at the beginning of the tilt test. For those VVS patients, pulse index and resistance index had no significant change. Syncope index decreased significantly 3 minutes before the point of syncope (0.23±0.07 vs.0.29±0.07,P<0.01). Dynamic regulation is exhausted when vasovagal syncope occurred. Tension decrease of small vessels could have some relationship with loss of the cerebral autoregulation capability. The proposed syncope index could be a useful parameter in predicting syncope of VVS patients since it decreased significantly up to 3 minutes earlier from the point of syncope.

Impaired cerebral autoregulation is associated with brain dysfunction in patients with sepsis

BackgroundSepsis-associated brain dysfunction (SABD) is associated with high morbidity and mortality. The pathophysiology of SABD is multifactorial. One hypothesis is that impaired cerebral autoregulation (CAR) may result in brain hypoperfusion and neuronal damage leading to SABD.MethodsWe studied 100 adult patients with sepsis (July 2012–March 2017) (age = 62 [52–71] years; Acute Physiology and Chronic Health Evaluation II score on admission = 21 [15–26]). Exclusion criteria were acute or chronic intracranial disease, arrhythmias, extracorporeal membrane oxygenation, and known intra- or extracranial supra-aortic vessel disease. The site of infection was predominantly abdominal (46%) or pulmonary (28%). Transcranial Doppler was performed, insonating the left middle cerebral artery with a 2-MHz probe. Middle cerebral artery blood flow velocity (FV) and arterial blood pressure (ABP) signals were recorded simultaneously; Pearson’s correlation coefficient (mean flow index [Mxa]) between ABP and FV was calculated using MATLAB. Impaired CAR was defined as Mxa > 0.3.ResultsMxa was 0.29 [0.05–0.62]. CAR was impaired in 50 patients (50%). In a multiple linear regression analysis, low mean arterial pressure, history of chronic kidney disease and fungal infection were associated with high Mxa. SABD was diagnosed in 57 patients (57%). In a multivariable analysis, altered cerebral autoregulation, mechanical ventilation and history of vascular disease were independent predictors of SABD.ConclusionsCerebral autoregulation was altered in half of the patients with sepsis and was associated with the development of SABD. These findings support the concept that cerebral hypoxia could contribute to the development of SABD.

Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study

Objective: Different methods to calculate dynamic cerebral autoregulation (dCA) parameters are available. However, most of these methods demonstrate poor reproducibility that limit their reliability for clinical use. Inter-centre differences in study protocols, modelling approaches and default parameter settings have all led to a lack of standardisation and comparability between studies. We evaluated reproducibility of dCA parameters by assessing systematic errors in surrogate data resulting from different modelling techniques. Approach: Fourteen centres analysed 22 datasets consisting of two repeated physiological blood pressure measurements with surrogate cerebral blood flow velocity signals, generated using Tiecks curves (autoregulation index, ARI 0–9) and added noise. For reproducibility, dCA methods were grouped in three broad categories: 1. Transfer function analysis (TFA)-like output; 2. ARI-like output; 3. Correlation coefficient-like output. For all methods, reproducibility was determined by one-way intraclass correlation coefficient analysis (ICC). Main results: For TFA-like methods the mean (SD; [range]) ICC gain was 0.71 (0.10; [0.49–0.86]) and 0.80 (0.17; [0.36–0.94]) for VLF and LF (p = 0.003) respectively. For phase, ICC values were 0.53 (0.21; [0.09–0.80]) for VLF, and 0.92 (0.13; [0.44–1.00]) for LF (p < 0.001). Finally, ICC for ARI-like methods was equal to 0.84 (0.19; [0.41–0.94]), and for correlation-like methods, ICC was 0.21 (0.21; [0.056–0.35]). Significance: When applied to realistic surrogate data, free from the additional exogenous influences of physiological variability on cerebral blood flow, most methods of dCA modelling showed ICC values considerably higher than what has been reported for physiological data. This finding suggests that the poor reproducibility reported by previous studies may be mainly due to the inherent physiological variability of cerebral blood flow regulatory mechanisms rather than related to (stationary) random noise and the signal analysis methods.

Reproducibility of Transcranial Doppler ultrasound in the middle cerebral artery

BackgroundTranscranial Doppler ultrasound remains the only imaging modality that is capable of real-time measurements of blood flow velocity and microembolic signals in the cerebral circulation. We here assessed the repeatability and reproducibility of transcranial Doppler ultrasound in healthy volunteers and patients with symptomatic carotid artery stenosis.MethodsBetween March and August 2017, we recruited 20 healthy volunteers and 20 patients with symptomatic carotid artery stenosis. In a quiet temperature-controlled room, two 1-h transcranial Doppler measurements of blood flow velocities and microembolic signals were performed sequentially on the same day (within-day repeatability) and a third 7–14 days later (between-day reproducibility). Levels of agreement were assessed by interclass correlation co-efficient.ResultsIn healthy volunteers (31±9 years, 11 male), within-day repeatability of Doppler measurements were 0.880 (95% CI 0.726–0.950) for peak velocity, 0.867 (95% CI 0.700–0.945) for mean velocity, and 0.887 (95% CI 0.741–0.953) for end-diastolic velocity. Between-day reproducibility was similar but lower: 0.777 (95% CI 0.526–0.905), 0.795 (95% CI 0.558–0.913), and 0.674 (95% CI 0.349–0.856) respectively. In patients (72±11 years, 11 male), within-day repeatability of Doppler measurements were higher: 0.926 (95% CI 0.826–0.970) for peak velocity, 0.922 (95% CI 0.817–0.968) for mean velocity, and 0.868 (95% CI 0.701–0.945) for end-diastolic velocity. Similarly, between-day reproducibility revealed lower values: 0.800 (95% CI 0.567–0.915), 0.786 (95% CI 0.542–0.909), and 0.778 (95% CI 0.527–0.905) respectively. In both cohorts, the intra-observer Bland Altman analysis demonstrated acceptable mean measurement differences and limits of agreement between series of middle cerebral artery velocity measurements with very few outliers. In patients, the carotid stenoses were 30–40% (n = 9), 40–50% (n = 6), 50–70% (n = 3) and > 70% (n = 2).No spontaneous embolisation was detected in either of the groups.ConclusionsTranscranial Doppler generates reproducible data regarding the middle cerebral artery velocities. However, larger studies are needed to validate its clinical applicability.Trial registrationClinicalTrial.gov (ID NCT 03050567), retrospectively registered on 15/05/2017.

Design and Validation of an FPGA-Based Configurable Transcranial Doppler Neurofeedback System for Chronic Pain Patients.

Neurofeedback is a self-regulation technique that can be applied to learn to voluntarily control cerebral activity in specific brain regions. In this work, a Transcranial Doppler-based configurable neurofeedback system is proposed and described. The hardware configuration is based on the Red Pitaya board, which gives great flexibility and processing power to the system. The parameter to be trained can be selected between several temporal, spectral, or complexity features from the cerebral blood flow velocity signal in different vessels. As previous studies have found alterations in these parameters in chronic pain patients, the system could be applied to help them to voluntarily control these parameters. Two protocols based on different temporal lengths of the training periods have been proposed and tested with six healthy subjects that were randomly assigned to one of the protocols at the beginning of the procedure. For the purposes of the testing, the trained parameter was the mean cerebral blood flow velocity in the aggregated data from the two anterior cerebral arteries. Results show that, using the proposed neurofeedback system, the two groups of healthy volunteers can learn to self-regulate a parameter from their brain activity in a reduced number of training sessions.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions.

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions.

A Stochastic Delay Differential Model of Cerebral Autoregulation

Mathematical models of the cardiovascular system and of cerebral autoregulation (CAR) have been employed for several years in order to describe the time course of pressures and flows changes subsequent to postural changes. The assessment of the degree of efficiency of cerebral auto regulation has indeed importance in the prognosis of such conditions as cerebro-vascular accidents or Alzheimer. In the quest for a simple but realistic mathematical description of cardiovascular control, which may be fitted onto non-invasive experimental observations after postural changes, the present work proposes a first version of an empirical Stochastic Delay Differential Equations (SDDEs) model. The model consists of a total of four SDDEs and two ancillary algebraic equations, incorporates four distinct delayed controls from the brain onto different components of the circulation, and is able to accurately capture the time course of mean arterial pressure and cerebral blood flow velocity signals, reproducing observed auto-correlated error around the expected drift.