Blood Pressure Model Based on Hybrid Feature Convolution Neural Network in Promoting Rehabilitation of Patients with Hypertensive Intracerebral Hemorrhage

Objective. Accurate prediction of the rise of blood pressure is essential for the hypertensive intracerebral hemorrhage. This study uses the hybrid feature convolution neural network to establish the blood pressure model instead of the traditional method of pulse waves. Methods. The pulse waves of 100 patients were collected, and the pulse wave was decomposed into three bell wave compound forms to obtain the accurate pulse wave propagation time. Then, the mixed feature convolution neural network model ABP-net was proposed, which combined the pulse wave propagation time characteristics with the pulse wave waveform characteristics automatically extracted by one-dimensional convolution to predict the arterial blood pressure. Finally, according to the prediction results, 20 patients were treated before the high blood pressure appeared (model group), and another 20 patients with a daily fixed treatment scheme were selected as the control group. Results. In 80 training sets, compared with linear regression and the random forest method, the hybrid feature convolution neural network has higher accuracy in predicting blood pressure. In 20 test sets, the blood pressure error was eliminated within 5 mmHg. The total effective rate in the model group and the control group was 95.0% and 85.0%, respectively ( P = 0.035 ). After treatment, the scores of self-care ability of daily life and limb motor function in the model group were higher than those in the control group ( P < 0.05 ). There were 8 cases (13.6%) in the model group and 17 cases (28.3%) in the control group due to the recurrence of cerebrovascular accident ( P = 0.043 ). Conclusion. Drug treatment guided by a blood pressure model based on a hybrid feature convolution neural network for patients with hypertensive cerebral hemorrhage can significantly and smoothly reduce blood pressure, promote the health recovery, and reduce the occurrence of cerebrovascular accidents.

Simulation of pulse wave propagation using one-dimensional models of hemodynamics

The models of hemodynamics, corresponding to the inviscid, Newtonian, and non-Newtonian models, are compared. The models are constructed by the averaging of the hydrodynamic system on the vessel cross-section. For the inviscid case, the analytical solution of the problem for pulse propagation is obtained. As the result of the comparison, the deviations of the solutions for non-Newtonian models from the Newtonian and inviscid cases are demonstrated.

A proof of concept study for machine learning application to stenosis detection

This proof of concept (PoC) assesses the ability of machine learning (ML) classifiers to predict the presence of a stenosis in a three vessel arterial system consisting of the abdominal aorta bifurcating into the two common iliacs. A virtual patient database (VPD) is created using one-dimensional pulse wave propagation model of haemodynamics. Four different machine learning (ML) methods are used to train and test a series of classifiers—both binary and multiclass—to distinguish between healthy and unhealthy virtual patients (VPs) using different combinations of pressure and flow-rate measurements. It is found that the ML classifiers achieve specificities larger than 80% and sensitivities ranging from 50 to 75%. The most balanced classifier also achieves an area under the receiver operative characteristic curve of 0.75, outperforming approximately 20 methods used in clinical practice, and thus placing the method as moderately accurate. Other important observations from this study are that (i) few measurements can provide similar classification accuracies compared to the case when more/all the measurements are used; (ii) some measurements are more informative than others for classification; and (iii) a modification of standard methods can result in detection of not only the presence of stenosis, but also the stenosed vessel.

Hemodynamic Modeling of the Circle of Willis Reveals Unanticipated Functions during Cardiovascular Stress

The circle of Willis (CW) allows blood to be redistributed throughout the brain during local ischemia; however, it is unlikely that the anatomic persistence of the CW across mammalian species is driven by natural selection of individuals with resistance to cerebrovascular disease typically occurring in elderly humans. To determine the effects of communicating arteries (CoAs) in the CW on cerebral pulse wave propagation and blood flow velocity, we simulated young, active adult humans undergoing different states of cardiovascular stress (i.e., fear and aerobic exercise) using discrete transmission line segments with stress-adjusted cardiac output, peripheral resistance, and arterial compliance. Phase delays between vertebrobasilar and carotid pulses allowed bi-directional shunting through CoAs: both posteroanterior shunting prior to the peak of the pulse waveform and anteroposterior shunting after internal carotid pressure exceeded posterior cerebral pressure. Relative to an absent CW without intact CoAs, the complete CW blunted anterior pulse waveforms, although limited to 3% and 6% reductions in peak pressure and pulse pressure, respectively. Systolic rate of change in pressure (i.e., ∂P/∂t) was reduced 15-24% in the anterior vasculature and increased 23-41% in the posterior vasculature. Bi-directional shunting through posterior CoAs was amplified during cardiovascular stress and increased peak velocity by 25%, diastolic-to-systolic velocity range by 44%, and blood velocity acceleration by 134% in the vertebrobasilar arteries. This effect may facilitate stress-related increases in blood flow to the cerebellum (improving motor coordination) and reticular activating system (enhancing attention and focus) via a nitric oxide-dependent mechanism, thereby improving survival in fight-or-flight situations.

Early diagnosis of increased stiffness of great vessels in adolescents with functional pathology of vegetative genesis

40 adolescents aged 15–17 years with functional cardiovascular pathology of vegetative origin underwent a 24-hour blood pressure monitoring (using the oscillometric method BPLabVasotens, Peter Telegin LLC, Nizhny Novgorod) with an assessment of central blood pressure parameters and rigidity of the main arteries.The scientists found significantly higher values of central systolic pressure during the day and night hours in the group of adolescents with arterial hypertension (n=13) compared to adolescents with normal blood pressure (n=27). They determined significantly higher values of the pulse wave velocity both during 24 hours and in the day and night hours in the group with arterial hypertension compared to the group of adolescents with normal blood pressure. No differences were found in the parameters of the propagation time of the reflected pulse wave and the augmentation index. The time of the reflected pulse wave propagation was significantly lower at nighttime compared to the daytime. In the group with arterial hypertension, the rate of pulse wave propagation in the aorta correlated only with the values of diastolic pressure over 24 hours and diastolic pressure in the daytime. In the adolescents with normal blood pressure, the pulse wave velocity correlated with systolic and pulse blood pressure. The augmentation index in the group of adolescents with arterial hypertension correlated with diastolic pressure, in contrast to the group of adolescents with normal blood pressure, where such a correlation was not detected.

Modeling Pulse Wave Propagation Through a Stenotic Artery With Fluid Structure Interaction: A Validation Study Using Ultrasound Pulse Wave Imaging

Pulse wave imaging (PWI) is an ultrasound-based method that allows spatiotemporal mapping of the arterial pulse wave propagation, from which the local pulse wave velocity (PWV) can be derived. Recent reports indicate that PWI can help the assessment of atherosclerotic plaque composition and mechanical properties. However, the effect of the atherosclerotic plaque's geometry and mechanics on the arterial wall distension and local PWV remains unclear. In this study, we investigated the accuracy of a finite element (FE) fluid–structure interaction (FSI) approach to predict the velocity of a pulse wave propagating through a stenotic artery with an asymmetrical plaque, as quantified with PWI method. Experiments were designed to compare FE-FSI modeling of the pulse wave propagation through a stenotic artery against PWI obtained with manufactured phantom arteries made of polyvinyl alcohol (PVA) material. FSI-generated spatiotemporal maps were used to estimate PWV at the plaque region and compared it to the experimental results. Velocity of the pulse wave propagation and magnitude of the wall distension were correctly predicted with the FE analysis. In addition, findings indicate that a plaque with a high degree of stenosis (&gt;70%) attenuates the propagation of the pulse pressure wave. Results of this study support the validity of the FE-FSI methods to investigate the effect of arterial wall structural and mechanical properties on the pulse wave propagation. This modeling method can help to guide the optimization of PWI to characterize plaque properties and substantiate clinical findings.