Comparison of arterial wave intensity analysis by pressure-velocity and diameter-velocity methods in a virtual population of adult subjects

Detecting heart failure from B-mode ultrasound characterization of arterial pulse waves

This study investigated the sensitivity and specificity of identifying heart failure with reduced ejection fraction (HFrEF) from measurements of the intensity and timing of arterial pulse waves. Previously validated methods combining ultrafast B-mode ultrasound, plane-wave transmission, singular value decomposition (SVD), and speckle tracking were used to characterize the compression and decompression ("S" and "D") waves occurring in early and late systole, respectively, in the carotid arteries of outpatients with left ventricular ejection fraction (LVEF) < 40%, determined by echocardiography, and signs and symptoms of heart failure, or with LVEF ≥ 50% and no signs or symptoms of heart failure. On average, the HFrEF group had significantly reduced S-wave intensity and energy, a greater interval between the R wave of the ECG and the S wave, a reduced interval between the S and D waves, and an increase in the S-wave shift (SWS), a novel metric that characterizes the shift in timing of the S wave away from the R wave of the ECG and toward the D wave (all P < 0.01). Receiver operating characteristics (ROCs) were used to quantify for the first time how well wave metrics classified individual participants. S-wave intensity and energy gave areas under the ROC of 0.76-0.83, the ECG-S-wave interval gave 0.85-0.88, and the S-wave shift gave 0.88-0.92. Hence the methods, which are simple to use and do not require complex interpretation, provide sensitive and specific identification of HFrEF. If similar results were obtained in primary care, they could form the basis of techniques for heart failure screening.NEW & NOTEWORTHY We show that heart failure with reduced ejection fraction can be detected with excellent sensitivity and specificity in individual patients by using B-mode ultrasound to detect altered pulse wave intensity and timing in the carotid artery.

Objective Evaluation of Stellate Ganglion Block Effects Using Ultrasound Wave Intensity Technology: A Study on Hemodynamics

Purpose

Emerging evidence suggests that although Horner's syndrome manifests observable facial changes, it may not comprehensively evaluate the hemodynamic alterations associated with stellate ganglion block (SGB). This study endeavors to systematically evaluate the influence of SGB on the elasticity and flow velocity of the common carotid artery (CCA) and brachial artery utilizing ultrasound wave intensity analysis (usWIA). Particularly, it focuses on patients necessitating monitoring for its effects on specific organs or regions.

Methods

Totally, we selected 33 patients, where only 31 patients (comprising 15 males and 16 females) were included between September 2020 to January 2022 after screening patients who require SGB treatment for painful disorders. The side on which the SGB was administered depended on the patient's painful side, 13 cases underwent left stellate ganglion block (LSGB), and 18 cases underwent right stellate ganglion block (RSGB). Wave intensity (WI) data were collected by usWIA on the CCA and brachial artery before the administration of SGB and after the manifestation of Horner's syndrome. We then compared the changes in these data pre- and post-SGB using SPSS 26.0.

Results

The results showed an increase in arterial compliance (AC) of the CCA and brachial artery on the blocked side after SGB (P < 0.05). In contrast, pressure-strain elastic modulus (EP) and arterial stiffness pulse wave velocity (PWVβ) decreased (for all P < 0.05). Furthermore, the minimum velocity (Vmin) of the CCA exhibited a significant increase (P < 0.01), while wave intensity pulse wave velocity (PWVwi) was significantly reduced (P < 0.01). In contrast, on the contralateral side of the CCA, EP and PWVβ increased after SGB (for all P < 0.05), while AC decreased (P < 0.05).

Conclusion

SGB has been observed to enhance the elasticity and blood flow velocity of arteries within its innervated areas. In clinical practice, usWIA can serve as an objective measurement tool for assessing the impact of SGB on arterial elasticity and flow velocity in specific organs or regions. Furthermore, unilateral SGB has been noted to diminish the arterial elasticity of the CCA on the contralateral side.

First blood: An efficient, hybrid one- and zero-dimensional, modular hemodynamic solver

Low-dimensional (1D or 0D) models can describe the whole human blood circulation, for example, 1D distributed parameter model for the arterial network and 0D concentrated models for the heart or other organs. This paper presents a combined 1D-0D solver, called first_blood, that solves the governing equations of fluid dynamics to model low-dimensional hemodynamic effects. An extended method of characteristics is applied here to solve the momentum, and mass conservation equations and the viscoelastic wall model equation, mimicking the material properties of arterial walls. The heart and the peripheral lumped models are solved with a general zero-dimensional (0D) nonlinear solver. The model topology can be modular, that is, first_blood can solve any 1D-0D hemodynamic model. To demonstrate the applicability of first_blood, the human arterial system, the heart and the peripherals are modelled using the solver. The simulation time of a heartbeat takes around 2 s, that is, first_blood requires only twice the real-time for the simulation using an average PC, which highlights the computational efficiency. The source code is available on GitHub, that is, it is open source. The model parameters are based on the literature suggestions and on the validation of output data to obtain physiologically relevant results.

Non-invasive Assessment by B-Mode Ultrasound of Arterial Pulse Wave Intensity and Its Reduction During Ventricular Dysfunction

Arterial pulse waves contain clinically useful information about cardiac performance, arterial stiffness and vessel tone. Here we describe a novel method for non-invasively assessing wave properties, based on measuring changes in blood flow velocity and arterial wall diameter during the cardiac cycle. Velocity and diameter were determined by tracking speckles in successive B-mode images acquired with an ultrafast scanner and plane-wave transmission. Blood speckle was separated from tissue by singular value decomposition and processed to correct biases in ultrasound imaging velocimetry. Results obtained in the rabbit aorta were compared with a conventional analysis based on blood velocity and pressure, employing measurements obtained with a clinical intra-arterial catheter system. This system had a poorer frequency response and greater lags but the pattern of net forward-traveling and backward-traveling waves was consistent between the two methods. Errors in wave speed were also similar in magnitude, and comparable reductions in wave intensity and delays in wave arrival were detected during ventricular dysfunction. The non-invasive method was applied to the carotid artery of a healthy human participant and gave a wave speed and patterns of wave intensity consistent with earlier measurements. The new system may have clinical utility in screening for heart failure.

Wave Intensity Analysis Combined With Machine Learning can Detect Impaired Stroke Volume in Simulations of Heart Failure

Heart failure is treatable, but in the United Kingdom, the 1-, 5- and 10-year mortality rates are 24.1, 54.5 and 75.5%, respectively. The poor prognosis reflects, in part, the lack of specific, simple and affordable diagnostic techniques; the disease is often advanced by the time a diagnosis is made. Previous studies have demonstrated that certain metrics derived from pressure-velocity-based wave intensity analysis are significantly altered in the presence of impaired heart performance when averaged over groups, but to date, no study has examined the diagnostic potential of wave intensity on an individual basis, and, additionally, the pressure waveform can only be obtained accurately using invasive methods, which has inhibited clinical adoption. Here, we investigate whether a new form of wave intensity based on noninvasive measurements of arterial diameter and velocity can detect impaired heart performance in an individual. To do so, we have generated a virtual population of two-thousand elderly subjects, modelling half as healthy controls and half with an impaired stroke volume. All metrics derived from the diameter-velocity-based wave intensity waveforms in the carotid, brachial and radial arteries showed significant crossover between groups-no one metric in any artery could reliably indicate whether a subject's stroke volume was normal or impaired. However, after applying machine learning to the metrics, we found that a support vector classifier could simultaneously achieve up to 99% recall and 95% precision. We conclude that noninvasive wave intensity analysis has significant potential to improve heart failure screening and diagnosis.