Physics-constrained intraventricular vector flow mapping by color Doppler

Color Doppler by transthoracic echocardiography creates two-dimensional fan-shaped maps of blood velocities in the cardiac cavities. It is a one-component velocimetric technique since it only returns the velocity components parallel to the ultrasound beams. Intraventricular vector flow mapping (iVFM) is a method to recover the blood velocity vectors from the Doppler scalar fields in an echocardiographic three-chamber view. We improved our iVFM numerical scheme by imposing physical constraints. The iVFM consisted in minimizing regularized Doppler residuals subject to the condition that two fluid-dynamics constraints were satisfied, namely planar mass conservation, and free-slip boundary conditions. The optimization problem was solved by using the Lagrange multiplier method. A finite-difference discretization of the optimization problem, written in the polar coordinate system centered on the cardiac ultrasound probe, led to a sparse linear system. The single regularization parameter was determined automatically for non-supervision considerations. The physics-constrained method was validated using realistic intracardiac flow data from a patient-specific CFD (computational fluid dynamics) model. The numerical evaluations showed that the iVFM-derived velocity vectors were in very good agreement with the CFD-based original velocities, with relative errors ranged between 0.3 and 12%. We calculated two macroscopic measures of flow in the cardiac region of interest, the mean vorticity and mean stream function, and observed an excellent concordance between physics-constrained iVFM and CFD. The capability of physics-constrained iVFM was finally tested with in vivo color Doppler data acquired in patients routinely examined in the echocardiographic laboratory. The vortex that forms during the rapid filling was deciphered. The physics-constrained iVFM algorithm is ready for pilot clinical studies and is expected to have a significant clinical impact on the assessment of diastolic function.

751 Quantitative changes in intracardiac vortices between patients with different ventricular geometry

Aims Over the past decades growing evidence have demonstrated the promising role of intracardiac fluid-dynamics in evaluating cardiac performance. To investigate quantitative changes in vortices parameters in patients with different ventricular geometry. Methods and results We enrolled 50 consecutive patients with one of the following: LV concentric hypertrophy (CH), eccentric hypertrophy (EH), concentric remodelling, and normal LV geometry (CTRL). They underwent a complete echocardiographic examination with intracardiac fluid-dynamic analysis by Color Vector Flow Mapping (Hyperdoppler). The following parameters were obtained: vortex area (VA); vortex length (VL); and vortex depth (VD). Bland Altman Plot has been used to assess intra and inter-observer variability. Mean VD was higher in CR, CH, and EH compared to CTRL (P = 0.013, P = 0.001, and P = 0.022, respectively). Moreover, CH showed higher VL (P = 0.006) and larger VA (P = 0.012) compared to CTRL. A similar trend was noticed in EH patients, despite did not reach statistical significance (P = 0.21 and P = 0.07 for VA and VL, respectively). No significative differences in vortices parameters have been observed between CH and EH. Conclusions This is the first study providing quantitative echocardiographic parameters of vortex location and morphology in different LV geometries. Quantitative fluid-dynamic assessment was feasible and reliable in the whole population.

An Astrocyte-Flow Mapping on a Mesh-Based Communication Infrastructure to Defective Neurons Phagocytosis

In deploying the Internet of Things (IoT) and Internet of Medical Things (IoMT)-based applications and infrastructures, the researchers faced many sensors and their output’s values, which have transferred between service requesters and servers. Some case studies addressed the different methods and technologies, including machine learning algorithms, deep learning accelerators, Processing-In-Memory (PIM), and neuromorphic computing (NC) approaches to support the data processing complexity and communication between IoMT nodes. With inspiring human brain structure, some researchers tackled the challenges of rising IoT- and IoMT-based applications and neural structures’ simulation. A defective device has destructive effects on the performance and cost of the applications, and their detection is challenging for a communication infrastructure with many devices. We inspired astrocyte cells to map the flow (AFM) of the Internet of Medical Things onto mesh network processing elements (PEs), and detect the defective devices based on a phagocytosis model. This study focuses on an astrocyte’s cholesterol distribution into neurons and presents an algorithm that utilizes its pattern to distribute IoMT’s dataflow and detect the defective devices. We researched Alzheimer’s symptoms to understand astrocyte and phagocytosis functions against the disease and employ the vaccination COVID-19 dataset to define a set of task graphs. The study improves total runtime and energy by approximately 60.85% and 52.38% after implementing AFM, compared with before astrocyte-flow mapping, which helps IoMT’s infrastructure developers to provide healthcare services to the requesters with minimal cost and high accuracy.

Adaptive Identification and Application of Flow Mapping and Inverse Flow Mapping for Electrohydraulic Valves

Good estimation of flow mapping (FM) and inverse flow mapping (IFM) for electrohydraulic valves are important in automation of fluid power system. The purpose of this paper is to propose adaptive identification methods based on LSM, BPNN, RBFNN, GRNN, LSSVM and RLSM to estimate the uncertain structure and parameters in flow mapping and inverse flow mapping for electrohydraulic valves. In order to reduce the complexity and improve the identification performance, model structures derived from new algorithm are introduced. The above identification methods are applied to map the flow characteristic of an electrohydraulic valve. With the help of novel simulation architecture via OPC UA, the accuracy and efficiency of these algorithms could be verified. Some issues like invertibility of flow mapping are discussed. At last, places and suggestions to apply these methods are made.

Analysis of Left Ventricular Wall Shear Stress during Diastole in Normal Subjects by Vector Flow Mapping

Objective To observe the diastolic wall shear stress (WSS) pattern of the left ventricle (LV) by using vector flow mapping (VFM) in normal subjects. Methods A total of 371 healthy volunteers were recruited into this study and divided into four age groups. The LV WSS was measured at each diastolic phase, and the mapping of WSS was analyzed. Results Among groups I, II and III, The absolute value of WSS of Anterolateral，Inferoseptal and Anterospetal segments in phase D1；WSS values of inferolateral，Inferoseptal and Anterospetal segments in phase D4 all showed an increasing trend with age. In terms of gender differences, In most cases，women had greater diastolic WSS values compared to men. For each age group, the log-transformed WSS value appeared the increasing-decreasing-increasing trend from phase D1 to D4, with a peak value at the rapid filling phase.Multivariate backward stepwise linear regression analysis revealed that the certain segments log-transformed WSS was independently related to conventional parameters in evaluating diastolic function（mitral lateral E/e', septal E/e', mitral lateral e', septal e' and LAVI）.Conclusions In diastolic period, segmental LV WSS shows a regular variation phenomenon and has specific age- and gender-related patterns in different diastolic phases. The mapping of WSS may help identify the diastolic hemodynamic changes or diastolic function phase by phase.

The Use of Compression Sonoelastography in Multiparametric Ultrasound Examination in Cases of Benign Ovarian Formations

Properly diagnosed benign ovarian formations are a condition for appropriate treatment choice. Qualitative assessment of signs detected by multiparametric ultrasound, including compression elastography, is highly effective in the differential diagnosis of benign ovarian formations. Our study became especially relevant for women in the reproductive period since the correct diagnosis influenced the choice of surgical treatment in order to preserve the ovarian reserve. The detailed sonographic aspect of these formations in B-mode, Doppler mode and compression sonoelastography mode is analyzed in the article. Color Flow Mapping, power Doppler and pulsed wave Doppler were used to study blood vessels. Pulsed wave Doppler characterized blood flow quantitatively. Color Flow Mapping was used to determine vessels localization, and power Doppler was used to provide a detailed qualitative assessment of blood flow loci. Elastotype according to the Ueno scale as a qualitative feature and Strain Ratio (coefficient of deformation) as a quantitative indicator were determined for all types of benign ovarian formations. Serous and mucinous cystadenomas were found to belong to elastotypes 0 and I according to the Ueno scale, the papillary component of serous superficial papillomas was mapped as elastotype I and II, fibroids predominantly belonged to elastotype II and III, mature teratoma appertained to elastotypes IV and V. Quantitative coefficient of deformation for all benign ovarian formations ranged from 0.63 to 24.9. According to our results, ultrasound examination of ovarian formations is an accurate and highly informative method for stratification of risks in accordance with the O-RADS classification.

Loss of apical suction assessed by noninvasive pressure differences and twist in acute heart failure: a novel method using vector flow mapping

Background Early diastolic intraventricular pressure difference (IVPD) reflects left ventricular (LV) apical suction, and IVPD is closely related to cardiac function, especially LV twist. Vector Flow Mapping (VFM) allows visualization of regional pressure distribution and noninvasive quantification of IVPD. The purpose of the present study was to investigate if and how IVPDs are related to LV twist in a model of acute heart failure (HF). Methods In 15 open-chest dogs, HF was induced by intracoronary injection of microspheres. The HF model was classified into two groups based on the LV end-diastolic pressure (LVEDP) (group1: LVEDP<18 mmHg (n=10), group2: LVEDP≥18 mmHg (n=8)). Color Doppler images from apical long-axis views were acquired at baseline and during HF. From these images, pressure differences (ΔP) were calculated along the LV inflow tract throughout the cardiac cycle. For the purpose of this study, the differences between apex and base during isovolumic relaxation time (ΔPIRT) and rapid early inflow period (ΔPE) were used for analyses. Furthermore, apical and basal short axis high frame rate 2D images were acquired, and peak rotation and peak twist were analyzed. Results LVEDP was 7±9, 14±2, 21±3 mmHg for baseline, group1 HF, and group2 HF, respectively. Pressure differences (both ΔPIRT and ΔPE) were visibly changed by the increase of LVEDP (Figure), and the magnitude of ΔPIRT, ΔPE and peak twist decreased significantly with the severity of heart failure. There were significant relationships between pressure differences (ΔPIRT and ΔPE) and dP/dtmin, tau, EF and peak twist (Table). In multivariate analyses, tau and peak twist were independent predictors for ΔPIRT and peak twist was independent predictor for ΔPE. Conclusion VFM analysis is feasible to noninvasively assess the IVPDs in acute heart failure. The IVPDs are closely related to the twisting motion of the LV, and reflect loss of apical suction during severe HF. FUNDunding Acknowledgement Type of funding sources: None. VFM images of pressure differences Correlations of pressure differences