Estimation Of Pressure Gradient Research Articles

Back to Bernoulli: a simple formula for trans-stenotic pressure gradients and retrospective estimation of flow rates in cerebral venous disease

BackgroundVenous sinus stenosis can be associated with cerebrovascular disorders. Understanding the role of blood flow disturbances in these disorders is often hampered by the lack of patient-specific flow rates. Our...

Artificial Intelligence Techniques for the Hydrodynamic Characterization of Two-Phase Liquid–Gas Flows: An Overview and Bibliometric Analysis

Accurately and instantly estimating the hydrodynamic characteristics in two-phase liquid–gas flow is crucial for industries like oil, gas, and other multiphase flow sectors to reduce costs and emissions, boost efficiency, and enhance operational safety. This type of flow involves constant slippage between gas and liquid phases caused by a deformable interface, resulting in changes in gas volumetric fraction and the creation of structures known as flow patterns. Empirical and numerical methods used for prediction often result in significant inaccuracies during scale-up processes. Different methodologies based on artificial intelligence (AI) are currently being applied to predict hydrodynamic characteristics in two-phase liquid–gas flow, which was corroborated with the bibliometric analysis where AI techniques were found to have been applied in flow pattern recognition, volumetric fraction determination for each fluid, and pressure gradient estimation. The results revealed that a total of 178 keywords in 70 articles, 29 of which reached the threshold (machine learning, flow pattern, two-phase flow, artificial intelligence, and neural networks as the high predominance), were published mainly in Flow Measurement and Instrumentation. This journal has the highest number of published articles related to the studied topic, with nine articles. The most relevant author is Efteknari-Zadeh, E, from the Institute of Optics and Quantum Electronics.

Effect of field viscometer dial readings on the estimation of drilling fluid frictional pressure loss using Herschel–Bulkley model

The main objective of this study is to investigate how uncertainties in dial readings would affect the frictional pressure loss estimation of the flow of drilling fluid in drill pipe. In this study, a new calculation procedure for determination of frictional pressure loss using the Herschel–Bulkley model is presented and verified with experimental data. A Monte Carlo simulation study is conducted to investigate the sensitivity of each dial reading on the estimation of frictional pressure drop for different circulation velocities. The results show that for the low yield fluids, 1o dial reading error introduces more than 6% error to the frictional pressure gradient prediction, especially at low flow velocity. While the errors in dial readings result in much smaller error in pressure gradient estimation for fluids with high yield stress, typically less than 5%. In addition, the readings at lower rotational speeds, i.e., 3 and 6 RPM, have a significant effect on the estimation of the frictional pressure loss, especially for low flow velocity and low yield stress fluids. More importantly, the uncertainty in dial readings has less effect on the frictional pressure drop estimation at moderately high flow velocity. This research also emphasizes the importance of rheological model parameter estimation using all available dial readings with the assistance of computational tools to better capture the rheological response of drilling fluids for better hydraulic calculation.

Overload of the Right Ventricle in Patients with Pulmonary Embolism: Analysis of New Evaluation Criteria

INTRODUCTION: The increasing incidence of pulmonary embolism (PE) and high mortality from it necessitates development of new echocardiographic (EchoCG) criteria for assessing the severity of pressure and volume overload of the right ventricle (RV) in patients with PE.
 AIM: To perform critical analysis of the developed EchoCG criteria of overload of the right heart chambers in PE with the aim to determine severity of the course and outcomes of the disease.
 MATERIALS AND METHODS: The study included 428 patients with PE divided to 4 groups: group 1 42 patients with recorded death, group 2 51 patients with hemodynamically significant disease, group 3 193 hemodynamically stable patients with EchoCG signs of the overload of the right ventricle, group 4 142 patients with no identified symptoms. Comparison of the developed EchoCG criteria was conducted: the volume of tricuspid regurgitation, its ratio to the volume of the right atrium and the stroke volume of the heart, and also the pressure in the pulmonary trunk, the pressure gradient on the pulmonic valve and its ratio to the pressure gradient on the tricuspid valve in the studied groups with the determination of threshold values having diagnostic and prognostic significance.
 RESULTS: It was found that the level of the estimated pressure gradient on the pulmonic valve has statistically significant correlation with the hemodynamic significance of the course of the disease (r = 0.91, р 0.01) and fatal outcome (r = 0.99, р 0.01) and possesses high sensitivity (more than 92.7%) and specificity (more than 97.8%). This parameter is proved to be the most important prognostic EchCG criterion. To determine the expression of the RV dysfunction and the priority flow of blood from its cavity, the following parameters equivalent to EhcoCG, such as the ratio of pressure gradient on the pulmonic artery to the pressure gradient on the tricuspid valve and the ratio of the tricuspid regurgitation volume to the stroke volume, are also significant.
 CONCLUSION: Calculation of the pressure gradient on the pulmonic valve and its correlation with the pressure gradient on the tricuspid valve, just as the ratio of the volume of tricuspid regurgitation to the stroke volume can be reliable criteria for assessment of the hemodynamic significance of PE and predictors of its outcome.

4Dflow-VP-Net: A deep convolutional neural network for noninvasive estimation of relative pressures in stenotic flows from 4D flow MRI.

To estimate relative transvalvular pressure gradient (TVPG) noninvasively from 4D flow MRI. A novel deep learning-based approach is proposed to estimate pressure gradient across stenosis from four-dimensional flow MRI (4D flow MRI) velocities. A deep neural network 4D flow Velocity-to-Presure Network (4Dflow-VP-Net) was trained to learn the spatiotemporal relationship between velocities and pressure in stenotic vessels. Training data were simulated by computational fluid dynamics (CFD) for different pulsatile flow conditions under an aortic flow waveform. The network was tested to predict pressure from CFD-simulated velocity data, in vitro 4D flow MRI data, and in vivo 4D flow MRI data of patients with both moderate and severe aortic stenosis. TVPG derived from 4Dflow-VP-Net was compared to catheter-based pressure measurements for available flow rates, in vitro and Doppler echocardiography-based pressure measurement, in vivo. Relative pressures calculated by 4Dflow-VP-Net and in vitro pressure catheterization revealed strong correlation (r2 = 0.91). Correlations analysis of TVPG from reference CFD and 4Dflow-VP-Net for 450 simulated flow conditions showed strong correlation (r2 = 0.99). TVPG from in vitro MRI had a correlation coefficient of r2 = 0.98 with reference CFD. 4Dflow-VP-Net, applied to 4D flow MRI in 16 patients, showed comparable TVPG measurement with Doppler echocardiography (r2 = 0.85). Bland-Altman analysis of TVPG measurements showed mean bias and limits of agreement of -0.20 ± 2.07 mmHg and 0.19 ± 0.45 mmHg for CFD-simulated velocities and in vitro 4D flow velocities. In patients, overestimation of Doppler echocardiography relative to TVPG from 4Dflow-VP-Net (10.99 ± 6.77 mmHg) was observed. The proposed approach can predict relative pressure in both in vitro and in vivo 4D flow MRI of aortic stenotic patients with high fidelity.

Precise Estimation of Intravascular Pressure Gradients.

This study presents a method for noninvasive pressure gradient estimation, which allows the detection of small pressure differences with higher precision compared to invasive catheters. It combines a new method for estimating the temporal acceleration of the flowing blood with the Navier-Stokes equation. The acceleration estimation is based on a double cross-correlation approach, which is hypothesized to minimize the influence of noise. Data are acquired using a 256-element, 6.5-MHz GE L3-12-D linear array transducer connected to a Verasonics research scanner. A synthetic aperture (SA) interleaved sequence with 2 ×12 virtual sources evenly distributed over the aperture and permuted in emission order is used in combination with recursive imaging. This enables a temporal resolution between correlation frames equal to the pulse repetition time at a frame rate of half the pulse repetition frequency. The accuracy of the method is evaluated against a computational fluid dynamic simulation. Here, the estimated total pressure difference complies with the CFD reference pressure difference, which yields an R -square of 0.985 and an RMSE of 3.03 Pa. The precision of the method is tested on experimental data, measured on a carotid phantom of the common carotid artery. The volume profile used during measurement was set to mimic flow in the carotid artery with a peak flow rate of 12.9 mL/s. The experimental setup showed that the measured pressure difference changes from -59.4 to 31 Pa throughout a single pulse cycle. This was estimated with a precision of 5.44% (3.22 Pa) across ten pulse cycles. The method was also compared to invasive catheter measurements in a phantom with a 60% cross-sectional area reduction. The ultrasound method detected a maximum pressure difference of 72.3 Pa with a precision of 3.3% (2.22 Pa). The catheters measured a maximum pressure difference of 105 Pa with a precision of 11.2% (11.4 Pa). This was measured over the same constriction and with a peak flow rate of 12.9 mL/s. The double cross-correlation approach revealed no improvement compared to a normal differential operator. The method's strength, thus, lies primarily in the ultrasound sequence, which allows precise and accurate velocity estimations, at which acceleration and pressure differences can be acquired.

An LSM Based Strategy is Comparable to HVPG Measurement to Predict Further Events in Patients with Cirrhosis with Variceal Bleeding as Their Index Decompensation

Limited data exist on strategies other than hepatic venous pressure gradient (HVPG) estimation to predict future events in patients with cirrhosis presenting with variceal bleed (VB) but are otherwise compensated. We assessed whether liver stiffness measurement (LSM) during VB episode could accurately predict this risk. Consecutive patients with cirrhosis with VB as their index decompensation event underwent HVPG and LSM estimation during the VB episode in this prospective study. New onset further decompensation events (ascites, VB, encephalopathy) was assessed over follow-up. The performance characteristics of postbleed LSM were compared with model for end stage liver disease (MELD) score and HVPG to predict future decompensation and were cross-validated. Mean age of the cohort (n= 68) was 44.2 years and alcohol-related liver disease (55.9%) was the most common etiology. Over a median follow-up of 14 (9-18) months, 18(26.4%) patients developed further decompensation with ascites being the most common event. Patients with further decompensation had a higher median postbleed LSM [60.5kPa (53-70) vs. 25kPa (18-34), P < 0.001], HVPG [ 19mm Hg vs. 16mmHg, P= 0.005], and MELD score [ 12.5 (11-14.7) vs. 10 (8-12)P < 0.001]. The area under receiver-operator characteristics curve for postbleed LSM [0.928 (95%CI: 0.868-0.988)] was higher than both HVPG [0.733(0.601-0.865), P= 0.003] and MELD score [0.776(0.664-0.889), P= 0.019] to predict further decompensation. Optimism-corrected c-statistic using MELD and postbleed LSM was similar to a combination of HVPG, MELD, and postbleed LSM. Postbleed LSM is comparable to HVPG estimation in predicting further decompensation events in patients with otherwise compensated cirrhosis presenting with VB.

PRESSURE GRADIENT COMPUTATION FOR FOAMS WITH DIFFERENT GEOMETRIC PROPERTIES: BASED ON ANN AND SVR MACHINE LEARNING MODEL AND TRAINED BY CFD SIMULATIONS

In this research work, a combination of computational fluid dynamics (CFD) simulation and artificial intelligence (AI) methods are conducted to study the effects of geometric properties of aluminum foams on airflow and to compute and predict pressure gradients in foams with such varied geometric parameters as porosity (65-90&amp;#37;) and pore diameter (200-2000 &amp;mu;m). The 3D foam structures are created by the Laguerre-Voronoi tessellations method. Based on the CFD results, pressure gradient for 114 different foams can be calculated in terms of inlet flow velocity (in the range 0.1-8 m/s). Foam pressure gradient is found to increase with increasing inlet flow velocity but with decreasing pore diameter and porosity. Comparisons reveal that the results obtained in the present study for pressure gradient are consistent with the data reported in the literature. It is, therefore, concluded that CFD simulation is a useful tool for pressure gradient estimation in a variety of foam types. Unique simulations are, however, needed each time foam structural properties change, which entails significant increases in the associated computation costs. This drawback may, nonetheless, be at least partially addressed by taking advantage of soft computing methods such as machine learning (ML). Artificial neural network (ANN) and support vector regression (SVR) as subsets of AI are designed (models with input variables inlet velocity and the foam structural parameters: porosity, pore diameter, and strut diameter) and trained using CFD results to predict pressure gradients in a large number of foams. When applied to new foam samples, the ML models exhibit an acceptable performance in predicting pressure gradients. Using such provisions, the method can be effectively used for predicting pressure gradient in various porous media at minimum computation costs.

Assessment of the Performance of Non-invasive Criteria for the Evaluation of Clinically Significant Portal Hypertension in Patients with Compensated Advanced Chronic Liver Disease.

Assessment of clinically significant portal hypertension (CSPH) non-invasively using a combination of liver stiffness measurement (LSM) and platelet counts is proposed as an alternative to hepatic venous pressure gradient (HVPG) estimation. Utility of these criteria in compensated advanced chronic liver disease (cACLD) patients of different etiologies including nonalcoholic steatohepatitis (NASH) with BMI > 30kg/m2 was studied in a large cohort. Consecutive patients of cACLD with available anthropometric and laboratory details, LSM, and HVPG were included in a retrospective analysis. A LSM of ≥ 25kPa alone and LSM ≤ 15kPa plus platelets ≥ 150×109/L were evaluated as non-invasive rule-in and rule-out criteria for CSPH, respectively. The NASH-ANTICPATE model (composite of BMI, platelets, and LSM) was evaluated in patients with obese NASH. Patients with cACLD (n = 626) (mean age: 50.8 ± 12.4years, 74.2% males) with alcohol (ALD, 30.3%), NASH (26.4%), hepatitis C (HCV, 16.6%), hepatitis B (HBV,10.2%) etiology were included. The prevalence of CSPH was > 80% across all etiologies except in HBV (62.5%) and in obese non-NASH (71-72%). The rule-in criteria had a PPV > 90% for all etiologies except in HBV (80.8%). The rule-out criteria had a negative predictive value (NPV) of 65%, 53%, and 40% in ALD, HCV, and NASH, respectively. The NASH-ANTCIPATE model had specificity of 100% and NPV of 33% to detect CSPH in obese NASH (n = 62). LSM ≥ 25kPa predicted CSPH in most etiologies except HBV. A significant proportion of patients have CSPH despite satisfying the rule-out criteria. The NASH-ANTICIPATE model is specific but fails to exclude CSPH in nearly two-third patients with obesity and NASH. There is a need for precise disease-specific non-invasive models for detecting CSPH.

3D numerical and experimental modelling of multiphase flow through an annular geometry applied for cuttings transport

Accurate estimation of volume fraction and pressure gradient is considered indicating parameters of efficient cuttings transportation. It is vital, in this regard, to consider all parameters that can affect cuttings volume fraction and pressure drop during enrollment of the drilling process. The analysis was conducted based on the turbulent flow of a power-law fluid through an annular domain by employing the Finite Volume Method. In addition, dimensional relationships were developed with the Buckingham-π theorem. Before carrying out simulations, the numerical schemes were validated using actual measurements made with the flow loop system available in Texas A&M University at Qatar. The simulation results demonstrated the followings: (i) using a power-law type drilling fluid with a shear-thinning character would reduce energy consumption for an inclination greater than 45°; (ii) inclination angles from 45° to 60° would be least desirable for an effective cuttings transportation with a turbulent Ostwald-de Waele fluid.

Liver stiffness can predict decompensation and need for beta-blockers in compensated cirrhosis: a step beyond Baveno-VI criteria

Liver stiffness measurement (LSM) alone or its combination with platelet counts [Baveno-VI criteria (B6C)] is an important non-invasive tool to predict risk of clinical decompensation in patients with advanced compensated cirrhosis. We compared its utility to decide need for beta-blockers in this regard compared with hepatic venous pressure gradient (HVPG) estimation. Patients with compensated cirrhosis with available baseline HVPG and LSM were followed up over a median follow-up of 26 (IQR 7-55) months to determine onset of clinical decompensations. Optimal cut-off for LSM for predicting decompensations was identified and compared with HVPG of 10mmHg and B6C. Feasibility of initiating beta-blockers based on these strategies was assessed using decision curve analysis (DCA) at different threshold probabilities of rates of clinical decompensation. 626 patients (mean age: 50.8 ± 12.4years, 72.4% males) related to alcohol (30.3%), non-alcoholic steatohepatitis (26.4%), hepatitis C (16.6%), hepatitis B (10.2%) were included. Altogether, 132 (21.0%) patients developed clinical decompensation. The time-dependant area under curve over 5years for HVPG and LSM for predicting clinical decompensation was 0.716-0.742 and 0.709-0.784, respectively. A LSM of 22kPa (Sensitivity-88.6%/Specificity-51.8%) had a similar negative predictive value but a higher positive predictive value [37.9% (LSM) vs.30.9% (HVPG)vs.30.6% (B6C), p = 0.026 at 3years] for incident decompensations. On DCA, LSM-based strategy emerged superior for deciding beta-blocker initiation with 150, 47, and 18 additional patients meriting treatment identified over and above B6C and HVPG based strategy at 5%, 10%, 20% annual rates of clinical decompensation, respectively. Measurement of liver stiffness alone can be a useful alternative to B6C and HVPG in deciding need for beta-blockers to prevent decompensations in compensated cirrhosis.

Cardiovascular magnetic resonance-derived left ventricular intraventricular pressure gradients among patients with precapillary pulmonary hypertension.

Precapillary pulmonary hypertension (pPH) affects left ventricular (LV) function by ventricular interdependence. Since LV ejection fraction (EF) is commonly preserved, LV dysfunction should be assessed with more sensitive techniques. Left atrial (LA) strain and estimation of LV intraventricular pressure gradients (IVPG) may be valuable in detecting subtle changes in LV mechanics; however, the value of these techniques in pPH is unknown. Therefore, the aim of our study is to evaluate LA strain and LV-IVPGs from cardiovascular magnetic resonance (CMR) cines in pPH patients. In this cross-sectional study, 31 pPH patients and 22 healthy volunteers underwent CMR imaging. Feature-tracking LA strain was measured on four- and two-chamber cines. LV-IVPGs (from apex-base) are computed from a formulation using the myocardial movement and velocity of the reconstructed 3D-LV (derived from long-axis cines using feature-tracking). Systolic function, both LV EF and systolic ejection IVPG, was preserved in pPH patients. Compared to healthy volunteers, diastolic function was impaired in pPH patients, depicted by (i) lower LA reservoir (36 ± 7% vs. 26 ± 9%, P < 0.001) and conduit strain (26 ± 6% vs. 15 ± 8%, P < 0.001) and (ii) impaired diastolic suction (-9.1 ± 3.0 vs. ‒6.4 ± 4.4, P = 0.02) and E-wave decelerative IVPG (8.9 ± 2.6 vs. 5.7 ± 3.1, P < 0.001). Additionally, 11 pPH patients (35%) showed reversal of IVPG at systolic-diastolic transition compared to none of the healthy volunteers (P = 0.002). pPH impacts LV function by altering diastolic function, demonstrated by an impairment of LA phasic function and LV-IVPG analysis. These parameters could therefore potentially be used as early markers for LV functional decline in pPH patients.

Abstract 12899: CMR Derived Intraventricular Pressure Gradients Analysis Shows Impaired Left Ventricular Function in Precapillary Pulmonary Hypertension

Introduction: Precapillary pulmonary hypertension (pPH) predominantly harms the right ventricle. Still, due to ventricular interdependence, it also affects left ventricular (LV) function. Since LV ejection fraction (EF) is often preserved, more sensitive techniques may be better suited to detect LV dysfunction, such as LA strain or estimation of LV intraventricular pressure gradients (IVPG). However, the value of these techniques in pPH is still unknown. Hypothesis: Cardiovascular magnetic resonance (CMR) derived LA phasic function and LV-IVPG can detect LV dysfunction in pPH patients. Methods: pPH patients (n=31) and healthy controls (n=10), age- and sex-matched, underwent CMR imaging. LA phasic function and the LV-IVPG, calculating the pressure gradient between apex and base throughout the cardiac cycle, were analyzed using standard long-axis cines. Results: LV systolic function, both LVEF as well as the IVPG positive systolic ejection force, was preserved in pPH patients compared to healthy controls (p=0.90, p=0.08 resp.). However, diastolic function in pPH patients was impaired, depicted by 1. lower LA reservoir (patients vs. controls 26% ±9 vs. 37% ±7, p=0.001) and conduit strain (15% ±8 vs. 26% ±7, p=0.001), and 2. an impaired diastolic suction force, and decreased E-wave decelerative force, indicating a weaker passive filling in early to mid-diastole ( see Table ). Also, 11 pPH patients (35%) showed reversal of IVPG at systolic-diastolic transition, meaning that LV pressure temporarily exceeds LA pressure, whereas none of the healthy controls showed this pattern (p=0.04). Conclusions: pPH impacts LV function by altering diastolic function, demonstrated by an impairment of LA phasic function and LV-IVPG analysis. These parameters could therefore potentially be used as early markers for LV functional decline in pPH patients.

Uncertainty propagation and truncation errors in LPT kinematics

Lagrangian Particle Tracking (LPT) has become a near-standard approach for performing accurate 3D flow measurements, thanks notably to the technical breakthroughs brought by the Iterative Particle Reconstruction (IPR: Wieneke, 2013) and Shake-the-Box (STB: Schanz et.al, 2016) procedures. These decisive progresses have triggered a number of studies relative to the eduction of flow kinematics and dynamics based on particle trajectory analyses. Novara &amp; Scarano (2013), and others, focused on polynomial approximations of the trajectories, which analytically provide the material derivatives used to estimate pressure gradients. In particular, approximations based on second order polynomials fits of a small number of particle positions are used in commercially available softwares and among research teams as a straightforward solution to obtain the first and second order derivatives with a limited effect of the measurement noise. Additionally the analyses conducted during the 2020 LPT challenge (Leclaire, 2020 ; Sciacchitano, 2020) have addressed the performance of methodologies used by different groups with respect to second order trajectory fits for both multi-pulse and four-pulse (Novara et. al, 2016) LPT cases. On more advanced theoretical grounds, Geseman et. al (2016) have proposed the trackfit approach using penalized B-splines with considerations on the time-varying acceleration rate (i.e. jolt or jerk) and spectral content of noisy particle tracks

Comparison of stenosis models for usage in the estimation of pressure gradient across aortic coarctation.

Non-invasive estimation of the pressure gradient in cardiovascular stenosis has much clinical importance in assisting the diagnosis and treatment of stenotic diseases. In this research, a systematic comparison is conducted to investigate the accuracy of a group of stenosis models against the MRI- and catheter-measured patient data under the aortic coarctation condition. Eight analytical stenosis models, including six from the literature and two proposed in this study, are investigated to examine their prediction accuracy against the clinical data. The two improved models proposed in this study consider comprehensively the Poiseuille loss, the Bernoulli loss in its exact form, and the entrance effect, of the blood flow. Comparison of the results shows that one of the proposed models demonstrates a cycle-averaged mean prediction error of -0.15 ± 3.03mmHg, a peak-to-peak prediction error of -1.8 ± 6.89mmHg, which is the best among the models studied.

Accelerated Estimation of Pulmonary Artery Stenosis Pressure Gradients with Distributed Lumped Parameter Modeling vs. 3D CFD with Instantaneous Adaptive Mesh Refinement: Experimental Validation in Swine.

Branch pulmonary artery stenosis (PAS) commonly occurs in congenital heart disease and the pressure gradient over a stenotic PA lesion is an important marker for re-intervention. Image based computational fluid dynamics (CFD) has shown promise for non-invasively estimating pressure gradients but one limitation of CFD is long simulation times. The goal of this study was to compare accelerated predictions of PAS pressure gradients from 3D CFD with instantaneous adaptive mesh refinement (AMR) versus a recently developed 0D distributed lumped parameter CFD model. Predictions were then experimentally validated using a swine PAS model (n = 13). 3D CFD simulations with AMR improved efficiency by 5 times compared to fixed grid CFD simulations. 0D simulations further improved efficiency by 6 times compared to the 3D simulations with AMR. Both 0D and 3D simulations underestimated the pressure gradients measured by catheterization (-1.87 ± 4.20and -1.78 ± 3.70mmHg respectively). This was partially due to simulations neglecting the effects of a catheter in the stenosis. There was good agreement between 0D and 3D simulations (ICC 0.88 [0.66-0.96]) but only moderate agreement between simulations and experimental measurements (0D ICC 0.60 [0.11-0.86] and 3D ICC 0.66 [0.21-0.88]). Uncertainty assessment indicates that this was likely due to limited medical imaging resolution causing uncertainty in the segmented stenosis diameter in addition to uncertainty in the outlet resistances. This study showed that 0D lumped parameter models and 3D CFD with instantaneous AMR both improve the efficiency of hemodynamic modeling, but uncertainty from medical imaging resolution will limit the accuracy of pressure gradient estimations.

CTA-Based Non-invasive Estimation of Pressure Gradients Across a CoA: a Validation Against Cardiac Catheterisation.

Non-invasive estimation of pressure gradients across a coarctation of the aorta (CoA) can reduce the need for diagnostic cardiac catheterisation. We aimed to validate two novel computational strategies-target-value approaching (TVA) and target-value fixing (TVF)-together with unrefined Doppler estimates, and to compare their diagnostic performance in identifying critical pressure drops for 40 patients. Compared to catheterisation, no statistically significant difference was demonstrated with TVA (P= 0.086), in contrast to TVF (P= 0.005) and unrefined Doppler echocardiography (P< 0.001). TVA manifested the strongest correlation with catheterisation (r= 0.93), compared to TVF (r= 0.83) and echocardiography (r= 0.67) (all P <0.001). In discriminating pressure gradients greater than 20mmHg, TVA, TVF, and echocardiography had respective sensitivities of 0.92, 0.88, and 0.80; specificities of 0.93, 0.80, and 0.73; and AUCs of 0.96, 0.89, and 0.80. The TVA strategy may serve as an effective and easily implemented approach to be used in clinical management of patients with CoA. Graphical Abstract Central illustration. Pressure gradients estimated using Doppler echocardiography and two novel computational strategies (TVA and TVF) were compared with cardiac catheterisation for 40 patients. TVA and TVF utilised the CTA images to obtain the CoA anatomy and Doppler echocardiography velocimetry to obtain velocity data for the assignment of CFD boundary conditions.

Fluid-dynamic effect of pannus formation around the prosthetic heart valve: in vitro demonstration using a heart-mimic pulsatile pump and particle image velocimetry

The abnormal growth of tissue, called pannus, is frequently found in patients who have an implanted prosthetic heart valve. Its growth is related to the valve dysfunction and disturbed blood flow in the aorta. We performed in vitro experiments to demonstrate the effects of pannus formation on hemodynamics and valvular function. The results showed that the opening angle of the heart valve changes depending on the size and shape of the pannus. The circular pannus decreased the maximum opening angle of the heart valve. Although the opening motion of the valve was not affected by the semi-circular pannus, one of the valve leaflets obstructed by the semi-circular pannus had a closing dysfunction during the cardiac cycle, implying aortic insufficiency and regurgitation in the patients with this type of pannus formation. The experimentally measured pressure gradient and velocity-based transvalvular pressure gradient estimation increased with the growth of the pannus, although a discrepancy between the two estimations was observed.

A Novel Estimation Approach of Pressure Gradient and Haemodynamic Stresses as Indicators of Pathological Aortic Flow Using Subvoxel Modelling.

The flow downstream from aortic stenoses is characterised by the onset of shear-induced turbulence that leads to irreversible pressure losses. These extra losses represent an increased resistance that impacts cardiac efficiency. A novel approach is suggested in this study to accurately evaluate the pressure gradient profile along the aorta centreline using modelling of haemodynamic stress at scales that are smaller than the typical resolution achieved in experiments. We use benchmark data obtained from direct numerical simulation (DNS) along with results from in silico and in vitro three-dimensional particle tracking velocimetry (3D-PTV) at three voxel sizes, namely 750 μm, 1mm and 1.5mm. A differential equation is derived for the pressure gradient, and the subvoxel-scale (SVS) stresses are closed using the Smagorinsky and a new refined model. Model constants are optimised using DNS and in silico PTV data and validated based on pulsatile in vitro 3D-PTV data and pressure catheter measurements. The Smagorinsky-based model was found to be more accurate for SVS stress estimation but also more sensitive to errors especially at lower resolution, whereas the new model was found to more accurately estimate the projected pressure gradient even for larger voxel size of 1.5mm albeit at the cost of increased sensitivity at this voxel size. A comparison with other methods in the literature shows that the new approach applied to in vitro PTV measurements estimates the irreversible pressure drop by decreasing the errors by at least 20%. Our novel approach based on the modelling of subvoxel stress offers a validated and more accurate way to estimate pressure gradient, irreversible pressure loss and SVS stress. We anticipate that the approach may potentially be applied to image-based in vivo, in vitro 4D flow data or in silico data with limited spatial resolution to assess pressure loss and SVS stresses in disturbed aortic blood flow.

The Leaflex™ Catheter – A Novel Device for Treating Calcific Aortic Stenosis – First-in-Human Intra-Operative Assessment of Safety and Efficacy

ABSTRACT Background The Leaflex™ is a novel percutaneous device for restoring calcified aortic valve leaflet mobility by mechanical scoring. To demonstrate the safety and efficacy of the Leaflex™ during surgical aortic valve replacement and examination of excised valve tissue. In a growing elderly population with multiple comorbidities, increasing frailty, and often limited mobility a simple mechanical intervention for severe aortic stenosis (AS) may be appropriate in selected patients as a standalone first intervention. Methods Five patients with severe AS (including one with fused leaflets) were treated with the Leaflex™ during cardiopulmonary bypass prior to valve excision. Estimated pressure gradient (PG) was assessed by the force required to pull a cone through the valve before and after Leaflex therapy. The change in the estimated aortic valve area (AVA) was then calculated based on the Gorlin equation. The excised aortic leaflets were examined histologically, radiographically and by micro-CT, for leaflet integrity. Results The Estimated PG based on the pullback force decreased by 75% (±2.7%) and estimated AVA increased by 99% (±11%) across 4 tri-leaflet aortic valves and by 53% and 46%, respectively, in one valve with fused commissures. Micro-CT and histology confirmed ventricular surface integrity at the site of scoring in all five cases. Conclusions In the intraoperative setting, the Leaflex™ was effective in decreasing estimated PG and increasing estimated AVA with the maintenance of valve tissue integrity. Although the results of the pressure gradient are estimates, these encouraging results support further assessment of the Leaflex™ approach in patients with calcific AS.