Transcranial Doppler Ultrasonography as a Diagnostic Tool for Cerebrovascular Disorders

Smartphone pupillometry for detection of cerebral vasospasm after aneurysmal subarachnoid hemorrhage

OBJECTIVES

Vasospasm is a complication of aneurysmal subarachnoid hemorrhage (aSAH) that can change the trajectory of recovery and is associated with morbidity and mortality. Earlier detection of vasospasm could improve patient outcomes. Our objective is to evaluate the accuracy of smartphone-based quantitative pupillometry in the detection of radiographic vasospasm and delayed cerebral ischemia (DCI) after aSAH.

MATERIALS AND METHODS

We prospectively collected pupillary light reflex (PLR) parameters from patients with aSAH admitted to a neurocritical care unit at a single hospital twice daily using quantitative smartphone pupillometry recordings. PLR parameters included: Maximum pupil diameter, minimum pupil diameter, percent change in pupil diameter, latency in beginning of pupil constriction to light, mean constriction velocity, maximum constriction velocity, and mean dilation velocity. Two-tailed t-tests for independent samples were performed to determine changes in average concurrent PLR parameter values between the following comparisons: (1) patients with and without radiographic vasospasm (defined by angiography with the need for endovascular intervention) and (2) patients with and without DCI.

RESULTS

49 subjects with aSAH underwent 323 total PLR recordings. For PLR recordings taken with (n=35) and without (n=241) radiographic vasospasm, significant differences were observed in MIN (35.0 ± 7.5 pixels with vasospasm versus 31.6 ± 6.2 pixels without; p=0.002). For PLR recordings taken with (n=43) and without (n=241) DCI, significant differences were observed in MAX (48.9 ± 14.3 pixels with DCI versus 42.5 ± 9.2 pixels without; p<0.001).

CONCLUSIONS

Quantitative smartphone pupillometry has the potential to be used to detect radiographic vasospasm and DCI after aSAH.

Intraoperative monitoring of the central and peripheral nervous systems: a narrative review

The central and peripheral nervous systems are the primary target organs during anaesthesia. At the time of the inception of the British Journal of Anaesthesia, monitoring of the central nervous system comprised clinical observation, which provided only limited information. During the 100 yr since then, and particularly in the past few decades, significant progress has been made, providing anaesthetists with tools to obtain real-time assessments of cerebral neurophysiology during surgical procedures. In this narrative review article, we discuss the rationale and uses of electroencephalography, evoked potentials, near-infrared spectroscopy, and transcranial Doppler ultrasonography for intraoperative monitoring of the central and peripheral nervous systems.

Harnessing Passive Pulsatile Shear Stress for Alzheimer's Disease Prevention and Intervention

 Alzheimer's disease (AD) affects more than 40 million people worldwide and is the leading cause of dementia. This disease is a challenge for both patients and caregivers and puts a significant strain on the global healthcare system. To address this issue, the Lancet Commission recommends focusing on reducing modifiable lifestyle risk factors such as hypertension, diabetes, and physical inactivity. Passive pulsatile shear stress (PPSS) interventions, which use devices like whole-body periodic acceleration, periodic acceleration along the Z-axis (pGz), and the Jogging Device, have shown significant systemic and cellular effects in preclinical and clinical models which address these modifiable risks factors. Based on this, we propose that PPSS could be a potential non-pharmacological and non-invasive preventive or therapeutic strategy for AD. We perform a comprehensive review of the biological basis based on all publications of PPSS using these devices and demonstrate their effects on the various aspects of AD. We draw from this comprehensive analysis to support our hypothesis. We then delve into the possible application of PPSS as an innovative intervention. We discuss how PPSS holds promise in ameliorating hypertension and diabetes while mitigating physical inactivity, potentially offering a holistic approach to AD prevention and management.

Transcranial Doppler ultrasonography in bacterial meningitis: A systematic review

PURPOSE

Bacterial meningitis remains a global threat due to its high mortality. It is estimated that >1.2 million cases of bacterial meningitis are reported annually. Intracranial vasculopathy is an important, under-documented complication, easily detected by transcranial Doppler (TCD) ultrasonography. Following the PRISMA Guidelines, we reviewed the utility of TCD in bacterial meningitis.

METHODS

This is a systematic review of observational studies on the use of TCD in patients with CSF-proven bacterial meningitis. Characteristic changes in TCD parameters along the course of the disease, correlation of TCD findings with neuroimaging, and functional outcomes were evaluated.

RESULTS

Nine studies were included with a total of 492 participants (mean age of 42). The most common TCD finding was intracranial arterial stenosis of the MCA (50%-82%) and ischemia (33%) was the predominant neuroimaging finding. The presence of an abnormal TCD finding increased the risk of poor outcomes as high as 70%.

CONCLUSIONS

Patients diagnosed with bacterial meningitis who underwent TCD show alterations in cerebral blood flow, correlating with imaging findings and poor outcomes. It aids in the diagnosis of its sequelae and can predict the prognosis of its outcome. TCD is a cost-effective, reliable modality for diagnosing vasculopathy associated with bacterial meningitis. It may prove useful in our armamentarium of management. Large prospective studies with long-term follow-up data may help establish the use of TCD in bacterial meningitis.

Overview of the Association Between the Pathophysiology, Types, and Management of Sickle Cell Disease and Stroke

Sickle cell disease (SCD) is a genetic blood disorder that affects hemoglobin and increases stroke risk, particularly in childhood. This review examines the pathophysiological association between SCD and stroke, the classification of stroke types, risk factors, diagnosis, management, prevention, and prognosis. A comprehensive literature search was conducted via PubMed, Scopus, and Cochrane databases. Relevant studies on SCD and stroke pathophysiology, classification, epidemiology, diagnosis, treatment, and prevention were identified. Sickle cell disease causes red blood cells to become rigid and sickle-shaped, obstructing blood vessels. Recurrent sickling alters cerebral blood flow and damages vessel walls, often leading to ischemic or hemorrhagic strokes (HS). These occur most frequently in childhood, with ischemic strokes (IS) being more common. Key risk factors include a prior transient ischemic attack (TIA), low hemoglobin, and a high leukocyte count. Neuroimaging is essential for diagnosis and determining stroke type. Primary prevention centers on blood transfusions and hydroxyurea for those at high risk. Acute treatment involves promptly restoring blood flow and managing complications. However, significant knowledge gaps remain regarding stroke mechanisms, optimizing screening protocols, and improving long-term outcomes. This review synthesizes current evidence on SCD and stroke to highlight opportunities for further research and standardizing care protocols across institutions. Ultimately, a holistic perspective is critical for mitigating the high risk of debilitating strokes in this vulnerable patient population.

Reproducibility and diurnal variation in middle cerebral artery blood velocity in healthy humans

NEW FINDINGS

What is the central question of this study? We sought to establish between-day reproducibility in estimates of middle cerebral artery blood velocity (MCAv) and cerebrovascular reactivity (CVR) in young, healthy male and female adults in tightly controlled experimental conditions. What is the main finding and its importance? Measures of MCAv assessed during morning, afternoon and evening hours are reproducible between days. There is diurnal variation in CVR, with values being highest during the evening compared with the morning. Greater diurnal variation in CVR is associated with more efficient sleep and greater nocturnal blood pressure dipping. These data enhance our understanding of modulators of MCAv and CVR.

ABSTRACT

Transcranial Doppler (TCD) is used to assess cerebral blood velocity (CBV) and cerebrovascular reactivity (CVR). Assessments of TCD reproducibility are limited, and few include multiple within-day measurements. We sought to establish reproducibility of CBV and CVR in healthy adults during three time periods (morning, afternoon and evening). We hypothesized that CBV and CVR measured at the same time of day are reproducible between days. We also hypothesized that CBV and CVR exhibit diurnal variation, with measurements being higher in the evening compared with morning/afternoon hours. Twelve adults [six male and six female, 27 years (95% CI, 22-31 years)] completed three measurements (morning, afternoon and evening) on two separate days in controlled conditions (e.g., meals, activity and sleep). Middle cerebral artery blood velocity (MCAv, TCD) was measured continuously at rest and during two CVR tests (end-expiratory apnoea and carbogen inhalation). Intraclass correlation coefficients for resting MCAv showed moderate to good reproducibility, which did not differ between morning, afternoon and evening (0.87, 0.56 and 0.67, respectively; P > 0.05). Intraclass correlation coefficients for peak MCAv during apnoea (0.80, 0.46 and 0.65, respectively; P > 0.05) and minute 2 of carbogen inhalation (0.81, 0.74 and 0.73, respectively; P > 0.05) were also not different from morning compared with afternoon/evening. Time of day had no effect on resting MCAv (F = 0.69, P = 0.51, ƞp 2  = 0.06) or the peak response to apnoea (F = 1.00, P = 0.39, ƞp 2  = 0.08); however, peak MCAv during carbogen breathing exhibited diurnal variation, with highest values in the evening (F = 3.41, P = 0.05, ƞp 2  = 0.24). Measures of CBV and CVR assessed via TCD during morning, afternoon and evening hours are reproducible between days. There is diurnal variation in the MCAv response to carbogen exposure, with CVR being highest during evening compared with morning hours.

Multimodal monitoring: practical recommendations (dos and don'ts) in challenging situations and uncertainty

With the advancements in modern medicine, new methods are being developed to monitor patients in the intensive care unit. Different modalities evaluate different aspects of the patient's physiology and clinical status. The complexity of these modalities often restricts their use to the realm of clinical research, thereby limiting their use in the real world. Understanding their salient features and their limitations can aid physicians in interpreting the concomitant information provided by multiple modalities to make informed decisions that may affect clinical care and outcomes. Here, we present a review of the commonly used methods in the neurological intensive care unit with practical recommendations for their use.

Transcranial Doppler analysis based on computer and artificial intelligence for acute cerebrovascular disease

Cerebrovascular disease refers to damage to brain tissue caused by impaired intracranial blood circulation. It usually presents clinically as an acute nonfatal event and is characterized by high morbidity, disability, and mortality. Transcranial Doppler (TCD) ultrasonography is a non-invasive method for the diagnosis of cerebrovascular disease that uses the Doppler effect to detect the hemodynamic and physiological parameters of the major intracranial basilar arteries. It can provide important hemodynamic information that cannot be measured by other diagnostic imaging techniques for cerebrovascular disease. And the result parameters of TCD ultrasonography such as blood flow velocity and beat index can reflect the type of cerebrovascular disease and serve as a basis to assist physicians in the treatment of cerebrovascular diseases. Artificial intelligence (AI) is a branch of computer science which is used in a wide range of applications in agriculture, communications, medicine, finance, and other fields. In recent years, there are much research devoted to the application of AI to TCD. The review and summary of related technologies is an important work to promote the development of this field, which can provide an intuitive technical summary for future researchers. In this paper, we first review the development, principles, and applications of TCD ultrasonography and other related knowledge, and briefly introduce the development of AI in the field of medicine and emergency medicine. Finally, we summarize in detail the applications and advantages of AI technology in TCD ultrasonography including the establishment of an examination system combining brain computer interface (BCI) and TCD ultrasonography, the classification and noise cancellation of TCD ultrasonography signals using AI algorithms, and the use of intelligent robots to assist physicians in TCD ultrasonography and discuss the prospects for the development of AI in TCD ultrasonography.

Development and Validation of Machine Learning Models to Classify Artery Stenosis for Automated Generating Ultrasound Report

Duplex ultrasonography (DUS) is a safe, non-invasive, and affordable primary screening tool to identify the vascular risk factors of stroke. The overall process of DUS examination involves a series of complex processes, such as identifying blood vessels, capturing the images of blood vessels, measuring the velocity of blood flow, and then physicians, according to the above information, determining the severity of artery stenosis for generating final ultrasound reports. Generation of transcranial doppler (TCD) and extracranial carotid doppler (ECCD) ultrasound reports involves a lot of manual review processes, which is time-consuming and makes it easy to make errors. Accurate classification of the severity of artery stenosis can provide an early opportunity for decision-making regarding the treatment of artery stenosis. Therefore, machine learning models were developed and validated for classifying artery stenosis severity based on hemodynamic features. This study collected data from all available cases and controlled at one academic teaching hospital in Taiwan between 1 June 2020, and 30 June 2020, from a university teaching hospital and reviewed all patients' medical records. Supervised machine learning models were developed to classify the severity of artery stenosis. The receiver operating characteristic curve, accuracy, sensitivity, specificity, and positive and negative predictive value were used for model performance evaluation. The performance of the random forest model was better compared to the logistic regression model. For ECCD reports, the accuracy of the random forest model to predict stenosis in various sites was between 0.85 and 1. For TCD reports, the overall accuracy of the random forest model to predict stenosis in various sites was between 0.67 and 0.86. The findings of our study suggest that a machine learning-based model accurately classifies artery stenosis, which indicates that the model has enormous potential to facilitate screening for artery stenosis.

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.