Velocity Waveforms Research Articles

Rupture zones of the 1978 (Mw 7.6) and 2020 (Mw 7.4) earthquakes in the Oaxaca subduction zone: Implications for seismic slip and seismic hazard

Abstract The slip models of the Oaxaca, Mexico earthquakes of 29 November 1978 (M w 7.6) and 23 June 2020 (Mw 7.4) were estimated by inverting P and SH teleseismic velocity waveforms. The inversion of the 1978 event used broadband and long-period data. In the case of the 2020 event, broadband data were available. In both cases, the rupture zones lie down dip of the hypocenter. It has been suggested that the events of 1978 and 2020 are quasi-repeater earthquakes breaking similar asperities of previous events. Based on this, the slip of the seismic rupture obtained in recent events is used to characterize the slip of previous events, and to calculate the slip deficiency in the four rupture zones defined by the 1928 events. The largest slip deficiency is where the large 7.6 event occurred in October 1928, between the ruptures of 1978 and the Mw 7.2 earthquake of June 2018. Here, no great earthquakes have occurred in the last 96 years, suggesting high accumulation of elastic strain that may generate potentially an earthquake Mw 7.8. This gap separates two regions with different seismic behavior, suggesting a complex rupture process in the Oaxaca subduction zone. The other three regions, where the 1978, 2018, and 2020 earthquakes took place, show average slip deficiencies of 500 cm. The great earthquake of 1787 broke the four rupture areas defined by the 1928 events in a single Mw 8.6 earthquake, consistent with a variable rupture mode that has been observed in other subduction zones of the world. In conclusion, the Oaxaca subduction zone suggests a high seismic potential.

Identification of vascular hotspots and analysis of micro-vessel flow velocity waveforms in high-grade squamous intraepithelial lesions of the cervix.

To assess hotspot micro-vessel flow velocity waveforms in human papillomavirus (HPV) cervical infections using transvaginal power Doppler ultrasound (TV-PDU) and explore associations with high-grade squamous intraepithelial lesions (HSIL, cervical intraepithelial neoplasia [CIN] II and III). In all, 62 patients with confirmed HPV-HSIL (14 CIN II, 48 CIN III) and 65 age- and parity-matched women with neither HPV infection nor CIN were compared. Seven parameters by TV-PDU were used to assess vascular classification and micro-vessel flow velocity, including vascular grading (class I, II, III), lowest pulsatility index (PI), resistance index (RI), peak systolic velocity (PS), end-diastolic velocity (ED), time average maximum velocity (TAMV), and the vascular index (VI = PS/ED). HSIL was primarily associated with vascular class I (75.8%), followed by class II (14.5%) and class III (9.7%). PI, RI, and VI in HSIL were significantly lower than the control group (P < 0.0001). Mean PI, RI, and VI values decreased progressively from the normal cervix to CIN II-III. At a PI cutoff of 1.03, sensitivity was 88.7%, specificity was 83.8%, and area under the curve (AUC) was 95.0. At an RI cutoff of 0.68, sensitivity was 96.8%, specificity 61.5%, and AUC 84.0. At a VI cutoff of 2.84, sensitivity was 85.5%, specificity 78.5%, and AUC 85.0. Based on different patterns of hotspot vascular classification and micro-vessel flow velocity waveforms, particularly PI between HSIL and the normal cervix, TV-PDU may offer a potential role for aiding the planning for patients with suspicious HSIL. Further studies are needed to validate the findings.

Effect of left colonic artery preservation on perfusion at the anastomosis in rectal cancer surgery evaluated with intraoperative ultrasound

PurposeIntraoperative ultrasound was used to assess the flow velocity in the marginal vessel arch adjacent to the anastomosis, critical for evaluating the anastomotic blood supply. This technique also enabled us to investigate the potential effects of preserving the left colonic artery on the perfusion of the anastomosis.MethodsThis prospective study included 40 rectal cancer patients who underwent laparoscopic anterior resection between January 2021 and January 2023. The length of the inferior mesenteric artery (IMA) was measured from its origin to the first branch, and the diameters of the mesenteric vessel IMA, left colonic artery (LCA), and marginal mesenteric artery (MMA) were recorded. Blood flow velocity and Doppler ultrasound waveforms of the MMA near the anastomosis were collected. Measurements were taken both before and after clamping the IMA using atraumatic forceps. The tardus parvus pattern of the MMA ultrasound waveforms was recorded to evaluate the hypoperfusion status of the anastomosis.ResultsThe mean velocities of MMA were 47.9 cm/s before clamping and 34.9 cm/s after atraumatic clamping, indicating significant differences (p < 0.05). Thirteen patients (32.5%) exhibited a Tardus parvus pattern after IMA atraumatic clamping. Multivariate analysis revealed older age and LCA diameter as independent clinical predictors of the hypoperfusion status after IMA clamping.ConclusionsPreservation of the LCA may improve perfusion near the anastomosis during rectal cancer surgery. Older age and LCA diameter can be considered useful predictors of the mesenteric hypoperfusion status after IMA ligation. Intraoperative ultrasound can evaluate the perfusion of the MMA near the anastomosis.Chinese Clinical Trial Registry—Registration number: ChiCTR2000041475

Experimental study on identifying anomaly azimuth based on acoustic vector array of borehole acoustic reflection imaging

Accurate anomaly azimuth identification is a major challenge in borehole acoustic reflection imaging. We develop an azimuth estimation method using an acoustic vector array to address this issue. This method is rigorously tested through a physical simulation experiment in a water-filled tank using a monopole acoustic source and an acoustic receiver station composed of eight azimuthal elements. Our method involves the synthesis of multiazimuth acoustic pressure waveforms recorded by the receiver into multicomponent particle velocity waveforms. These waveforms are paired and subjected to coordinate conversion, yielding multiple groups of orthogonal component particle velocity waveforms. Each group undergoes polarization analysis to obtain the direction of particle polarization on the horizontal plane and isolate the principal component particle velocity waveform. Using the particle polarization direction, the amplitude of the multiazimuth acoustic pressure waveform, and the type of echo mode, we accurately determine the azimuth of the anomaly, facilitating the creation of a spatial distribution image of the anomaly. Further validation of this method is conducted through a large-scale physical simulation experiment in a deepwater lake using a borehole acoustic reflection imaging instrument. The obtained experimental data are used to validate the effectiveness of this method. Finally, considering an actual logging environment, the feasibility of this method in a borehole environment is verified using numerical simulations and field data of acoustic detection of nearby wells. The present findings demonstrate that this novel method considerably enhances the accuracy and stability of the measurement of anomaly azimuth based on the particle polarization direction. In addition, this method effectively harnesses acoustic pressure and particle velocity in borehole acoustic reflection imaging, exhibiting superior noise robustness, mitigating noise, and improving the signal-to-noise ratio of the echoes.

Physics-Informed Graph Neural Networks to solve 1-D equations of blood flow

Background and Objective:Computational models of hemodynamics can contribute to optimizing surgical plans, and improve our understanding of cardiovascular diseases. Recently, machine learning methods have become essential to reduce the computational cost of these models. In this study, we propose a method that integrates 1-D blood flow equations with Physics-Informed Graph Neural Networks (PIGNNs) to estimate the propagation of blood flow velocity and lumen area pulse waves along arteries. Methods:Our methodology involves the creation of a graph based on arterial topology, where each 1-D line represents edges and nodes in the blood flow analysis. The innovation lies in decoding the mathematical data connecting the nodes, where each node has velocity and lumen area pulse waveform outputs. The training protocol for PIGNNs involves measurement data, specifically velocity waves measured from inlet and outlet vessels and diastolic lumen area measurements from each vessel. To optimize the learning process, our approach incorporates fundamental physical principles directly into the loss function. This comprehensive training strategy not only harnesses the power of machine learning but also ensures that PIGNNs respect fundamental laws governing fluid dynamics. Results:The accuracy was validated in silico with different arterial networks, where PIGNNs achieved a coefficient of determination (R2) consistently above 0.99, comparable to numerical methods like the discontinuous Galerkin scheme. Moreover, with in vivo data, the prediction reached R2 values greater than 0.80, demonstrating the method’s effectiveness in predicting flow and lumen dynamics using minimal data. Conclusions:This study showcased the ability to calculate lumen area and blood flow rate in blood vessels within a given topology by seamlessly integrating 1-D blood flow with PIGNNs, using only blood flow velocity measurements. Moreover, this study is the first to compare the PIGNNs method with other classic Physics-Informed Neural Network (PINNs) approaches for blood flow simulation. Our findings highlight the potential to use this cost-effective and proficient tool to estimate real-time arterial pulse waves.

Fine Shallow Structures of Binchuan Basin Inverted From Receiver Functions and Implications for Basin Evolution

AbstractThe understanding of the velocity structure and basement morphology within the basin is crucial for seismic hazard mitigation and the study of basin evolution. To explore the intricate structure of the Binchuan Basin in western Yunnan, China, we deployed a linear dense array in the northern region of the Binchuan Basin, with inter‐station distance ranging from 50 to 100 m. We propose a novel receiver function processing workflow. Initially, we extracted coherent receiver functions based on the dense array, followed by a inversion of basement morphology, S‐wave velocities, and sedimentary layer's average Vp/Vs ratio jointly with frequency‐dependent teleseismic apparent shear velocity and receiver function waveforms. The results show that S‐wave velocity anomalies correspond to the unconsolidated sediments. The thickness of the sedimentary layer ranges from ∼0.5 to ∼0.75 km. The basement morphology suggests the basin is controlled by normal faults. Additionally, intra‐basin faults displayed higher fault displacement to length ratios (∼0.27) than most isolated normal faults (10−3–10−1), which may result from accumulated fault displacement due to interactions between fault segments. These results emphasize the significant role of N–S trending intra‐basin faults in basin evolution, suggesting that micro‐block rotations and transitional movements within the Northwestern Yunnan Rift Zone are primary mechanisms shaping the Binchuan Basin. We further proposed a multi‐stage model for the evolution of the Binchuan Basin. The robustness testing validates that the proposed processing flow is an effective approach to comprehensively image the basin velocity structure and the basement morphology.

Pathophysiology of the ascending aorta: Impact of dilation and valve phenotype on large-scale blood flow coherence detected by 4D flow MRI

Background and objectiveThe evidence on the role of hemodynamics in aorta pathophysiology has yet to be robustly translated into clinical applications, to improve risk stratification of aortic diseases. Motivated by the need to enrich the current understanding of the pathophysiology of the ascending aorta (AAo), this study evaluates in vivo how large-scale aortic flow coherence is affected by AAo dilation and aortic valve phenotype. MethodsA complex networks-based approach is applied to 4D flow MRI data to quantify subject-specific AAo flow coherence in terms of correlation between axial velocity waveforms and the aortic flow rate waveform along the cardiac cycle. The anatomical length of persistence of such correlation is quantified using the recently proposed network metric average weighted curvilinear distance (AWCD). The analysis considers 107 subjects selected to allow an ample stratification in terms of aortic valve morphology, absence/presence of AAo dilation and of aortic valve stenosis. ResultsThe analysis highlights that the presence of AAo dilation as well as of bicuspid aortic valve phenotype breaks the physiological AAo flow coherence, quantified in terms of AWCD. Of notice, it emerges that cycle-average blood flow rate and relative AAo dilation are main determinants of AWCD, playing opposite roles in promoting and hampering the persistence of large-scale flow coherence in AAo, respectively. ConclusionsThe findings of this study can contribute to broaden the current mechanistic link between large-scale blood flow coherence and aortic pathophysiology, with the prospect of enriching the existing tools for the in vivo non-invasive hemodynamic risk assessment for aortic diseases onset and progression.

Evidence that systemic vascular resistance is increased before the development of gestational diabetes mellitus

The ophthalmic artery, which is the first branch of the internal carotid artery, has a Doppler velocity waveform with two systolic peaks. The ratio of the peak systolic velocity (PSV) of the second wave divided by that of the first wave, reflects increased peripheral resistance. Previous studies in the first, second and third trimesters of pregnancy have reported that in pregnancies that subsequently develop preeclampsia (PE) the PSV ratio is increased. Both PE and gestational diabetes mellitus (GDM) are associated with endothelial dysfunction and an increased risk of cardiovascular diseases during the first decade following pregnancy. To compare the ophthalmic artery PSV ratio at 11-13 weeks' gestation in women who subsequently develop GDM to unaffected pregnancies and those who develop PE. This was a prospective observational study in women attending for a routine hospital visit at 11+0 - 13+6 weeks' gestation at King's College Hospital, London, UK. This visit included recording of maternal demographic characteristics and medical history, ultrasound examination for fetal anatomy and growth, assessment of flow velocity waveforms from the maternal ophthalmic arteries and calculation of the PSV ratio, and measurement of mean arterial pressure (MAP). Linear regression was performed for the prediction of ophthalmic artery PSV ratio, from maternal characteristics and MAP. The PSV ratio in the group with GDM was compared to that of PE and unaffected pregnancies. 3999 women were included in the study, including 375 (9.8%) who developed GDM and 101 (2.5%) who developed PE. In the GDM group, 161 (43.3%) were treated by diet alone, 130 (34,1%) were treated with metformin and 84 (22.6%) received insulin ± metformin. Significant prediction of PSV ratio was provided by development of PE, maternal age, body mass index, MAP, first degree family history of diabetes mellitus, family history of PE, Asian ethnicity, and smoking. There was no significant contribution from GDM. In women who developed GDM requiring insulin treatment, ophthalmic artery PSV ratio (0.67 ± 0.09) was higher (p <0.001) than in unaffected pregnancies (0.63 ± 0.10), but it was not significantly different from that in the PE group (0.69 ± 0.10; p=0.90). In women who develop severe GDM, requiring insulin treatment, there is evidence of increased peripheral resistance which is apparent from the first-trimester of pregnancy.

Numerical simulating the blood flow model via nonhomogeneous Riemann solver scheme

This paper examines a one-dimensional (1D) model that appears in arterial blood flow. The mathematical model for blood flow via arteries is similar to that of unstable incompressible flows in thin-walled collapsible tubes. We present the Riemann invariants of the suggested model, which is one of the fundamental components of this work. For numerical modeling of blood flow model, we present a nonhomogeneous Riemann solver (NHRS) technique. Next, we demonstrate the simulation of how pressure, velocity, and cross section area waveforms propagate through arteries. Specifically, we present numerical test cases with various initial data sets. In addition, we compare the NHRS scheme to the classic Rusanov, Lax–Friedrichs, and Roe schemes. Theoretical models for thin-walled collapsible tubes are applicable to a wide range of physiological events and may be used to build clinical devices for actual biomedical science. The NHRS method’s accuracy and efficiency are demonstrated by the numerical tests.

In vivo movement interrelationships among the medial meniscus, joint capsule, and semimembranosus during tibial rotation

The meniscal position within the knee is critical to maintain normal knee function. The joint capsule might dynamically coordinate the medial meniscus (MM) by transmitting a semimembranosus action. However, their interrelationships in vivo are unclear. We aimed to determine relationships among the MM, joint capsule, and semimembranosus during passive tibial external-internal and isometric tibial internal rotation at the medial and posteromedial knees of 10 healthy individuals in vivo using ultrasound. We analyzed images of the MM and joint capsule locations at the medial and posteromedial knee and the velocity waveform similarity of each structure during rotational tasks. Both isometric internal rotation with semimembranosus action and passive tibial external rotation displaced the MM inward at the medial knee. The MM and joint capsule during these MM displacements coordinately moved with more than moderate cross-correlation coefficients (passive external and isometric internal rotations, ≥ 0.54 and ≥ 0.90, respectively). The movements of the MM and joint capsule to the semimembranosus during isometric internal rotation also coordinated with moderate cross-correlation coefficients (≥ 0.62). Therefore, the joint capsule might dynamically coordinate the MM by transmitting semimembranosus action. Whether increased tibial internal rotation or semimembranosus shortening causes MM extrusion awaits further investigation.

Peak detection in intracranial pressure signal waveforms: a comparative study

BackgroundThe monitoring and analysis of quasi-periodic biological signals such as electrocardiography (ECG), intracranial pressure (ICP), and cerebral blood flow velocity (CBFV) waveforms plays an important role in the early detection of adverse patient events and contributes to improved care management in the intensive care unit (ICU). This work quantitatively evaluates existing computational frameworks for automatically extracting peaks within ICP waveforms.MethodsPeak detection techniques based on state-of-the-art machine learning models were evaluated in terms of robustness to varying noise levels. The evaluation was performed on a dataset of ICP signals assembled from 700 h of monitoring from 64 neurosurgical patients. The groundtruth of the peak locations was established manually on a subset of 13, 611 pulses. Additional evaluation was performed using a simulated dataset of ICP with controlled temporal dynamics and noise.ResultsThe quantitative analysis of peak detection algorithms applied to individual waveforms indicates that most techniques provide acceptable accuracy with a mean absolute error (MAE) ≤10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\le 10$$\\end{document} ms without noise. In the presence of a higher noise level, however, only kernel spectral regression and random forest remain below that error threshold while the performance of other techniques deteriorates. Our experiments also demonstrated that tracking methods such as Bayesian inference and long short-term memory (LSTM) can be applied continuously and provide additional robustness in situations where single pulse analysis methods fail, such as missing data.ConclusionWhile machine learning-based peak detection methods require manually labeled data for training, these models outperform conventional signal processing ones based on handcrafted rules and should be considered for peak detection in modern frameworks. In particular, peak tracking methods that incorporate temporal information between successive periods of the signals have demonstrated in our experiments to provide more robustness to noise and temporary artifacts that commonly arise as part of the monitoring setup in the clinical setting.

Real-time quantification of in vivo cerebrospinal fluid velocity using the functional magnetic resonance imaging inflow effect.

In vivo estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory-gated approaches, such as 4D flow magnetic resonance imaging (MRI), cannot capture CSF movement in real time because of limited temporal resolution and, in addition, deteriorate in accuracy at low fluid velocities. Other techniques like real-time phase-contrast-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability, even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional MRI (fMRI) for in vivo, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath-holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from in vivo fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.

Doppler ultrasound compared to shear wave elastography for assessment of liver cirrhosis

BackgroundThe progression of liver fibrosis to cirrhosis is a dynamic process necessitating non-invasive evaluation modalities. This study aims to evaluate the ability of Doppler ultrasound studies (DUS) in defining morphological and hemodynamic blood flow changes in the hepatic vasculature coinciding with advanced liver fibrosis.MethodsA prospective study was conducted on 100 patients with liver cirrhosis (F4). All cases underwent liver stiffness (LS) measurement by shear wave elastography (SWE), along with DUS to evaluate the liver texture, splenic size, hepatic artery resistive index (HARI), portal and splenic vein diameters, portal vein velocity (PVV), and hepatic vein waveform (HVV). All measures were assessed concurrently with a highly qualified single operator.ResultsPatients aged 55.5 ± 10.2 years with male predominance (72%). A highly significant correlation was found between LS by SWE and hepatic parenchymal texture, splenic size, portal vein width, and HVV (monophasic and biphasic) (p < 0.001). There were also high significant positive correlations (p < 0.001) between LS and PVV. However, there was no definitive correlation between LS and HARI, as well as splenic vein diameter.ConclusionThe widely available economic Doppler studies including portal vein velocity and hepatic vein waveform changes could be of substantial diagnostic value to liver cirrhosis.Study designProspective cohort study, employing descriptive and analytical statistics.

Thoughts of the February 20, 2023 Defne aftershock

On February 6 2023, two large earthquakes with magnitudes of Mw 7.8 (Pazarcık) and Mw 7.6 (Elbistan) occurred consecutively along the East Anatolian Fault Zone in eastern Turkey, causing enormous casualties and heavy damage. This devastating sequence of earthquakes was followed by the Defne aftershock on February 20 near Antakya province, which increased the damage and loss of life. Here, the teleseismic broadband P velocity waveforms are inverted to obtain the coseismic finite-fault slip distribution of the February 20, 2023 Defne aftershock. It was found that the rupture was controlled by the failure of a single asperity with the largest displacement of approximately 0.75 m, which occurred between 6 and 20 km depth. The source mechanism indicated a dominant left-lateral faulting with a significant normal component and released a total seismic moment of 5.85x1018 Nt.m. Coseismic Coulomb stress changes modelling showed that the Defne aftershock rupture was triggered by the earthquake sequence and that the February 6 Pazarcık earthquake had a dominant effect. In the stress modelling carried out on the Dead Sea Fault, the northern segment of the fault remained in the region of significant positive stress loading. Considering the positive stress load over 1 bar created by the earthquake sequence and the Defne aftershock ruptures, as well as the fact that no major earthquake has occurred for more than 600 years, it is clear that the probability of rupture in the northern part has increased significantly and the seismic hazard is high.

Using DFT on ultrasound measurements to determine patient-specific blood flow boundary conditions for computational hemodynamics of intracranial aneurysms

Boundary conditions (BCs) is one pivotal factor influencing the accuracy of hemodynamic predictions on intracranial aneurysms (IAs) using computational fluid dynamics (CFD) modeling. Unfortunately, a standard procedure to secure accurate BCs for hemodynamic modeling does not exist. To bridge such a knowledge gap, two representative patient-specific IA models (Case-I and Case-II) were reconstructed and their blood flow velocity waveforms in the internal carotid artery (ICA) were measured by ultrasonic techniques and modeled by discrete Fourier transform (DFT). Then, numerical investigations were conducted to explore the appropriate number of samples (N) for DFT modeling to secure the accurate BC by comparing a series of hemodynamic parameters using in-vitro validated CFD modeling. Subsequently, a comprehensive comparison in hemodynamic characteristics under patient-specific BCs and a generalized BC based on a one-dimensional (1D) model was conducted to reinforce the understanding that a patient-specific BC is pivotal for accurate hemodynamic risk evaluations on IA pathophysiology. In addition, the influence of the variance of heart rate/cardiac pulsatile period on hemodynamic characteristics in IA models was studied preliminarily. The results showed that N ≥ 16 for DFT model is a decent choice to secure the proper BC profile to calculate time-averaged hemodynamic parameters, while more data points such as N ≥ 36 can ensure the accuracy of instantaneous hemodynamic predictions. In addition, results revealed the generalized BC could overestimate or underestimate the hemodynamic risks on IAs significantly; thus, patient-specific BCs are highly recommended for hemodynamic modeling for IA risk evaluation. Furthermore, this study discovered the variance of heart rate has rare influences on hemodynamic characteristics in both instantaneous and time-averaged parameters under the assumption of an identical blood flow rate.

Modelling lower-limb peripheral arterial disease using clinically available datasets: impact of inflow boundary conditions on hemodynamic indices for restenosis prediction

Background and ObjectivesThe integration of hemodynamic markers as risk factors in restenosis prediction models for lower-limb peripheral arteries is hindered by fragmented clinical datasets. Computed tomography (CT) scans enable vessel geometry reconstruction and can be obtained at different times than the Doppler ultrasound (DUS) images, which provide information on blood flow velocity. Computational fluid dynamics (CFD) simulations allow the computation of near-wall hemodynamic indices, whose accuracy depends on the prescribed inlet boundary condition (BC), derived from the DUS images. This study aims to: (i) investigate the impact of different DUS-derived velocity waveforms on CFD results; (ii) test whether the same vessel areas, subjected to altered hemodynamics, can be detected independently of the applied inlet BC; (iii) suggest suitable DUS images to obtain reliable CFD results. MethodsCFD simulations were conducted on three patients treated with bypass surgery, using patient-specific DUS-derived inlet BCs recorded at either the same or different time points than the CT scan. The impact of the chosen inflow condition on bypass hemodynamics was assessed in terms of wall shear stress (WSS)-derived quantities. Patient-specific critical thresholds for the hemodynamic indices were applied to identify critical luminal areas and compare the results with a reference obtained with a DUS image acquired in close temporal proximity to the CT scan. ResultsThe main findings indicate that: (i) DUS-derived inlet velocity waveforms acquired at different time points than the CT scan led to statistically significantly different CFD results (p<0.001); (ii) the same luminal surface areas, exposed to low time-averaged WSS, could be identified independently of the applied inlet BCs; (iii) similar outcomes were observed for the other hemodynamic indices if the prescribed inlet velocity waveform had the same shape and comparable systolic acceleration time to the one recorded in close temporal proximity to the CT scan. ConclusionsDespite a lack of standardised data collection for diseased lower-limb peripheral arteries, an accurate estimation of luminal areas subjected to altered near-wall hemodynamics is possible independently of the applied inlet BC. This holds if the applied inlet waveform shares some characteristics – derivable from the DUS report – as one matching the acquisition time of the CT scan.

Echocardiographic estimation of right ventricular diastolic stiffness based on pulmonary regurgitant velocity waveform analysis in precapillary pulmonary hypertension.

Right ventricular (RV) diastolic stiffness is an independent predictor of survival and is strongly associated with disease severity in patients with precapillary pulmonary hypertension (PH). Therefore, a fully validated echocardiographic method for assessing RV diastolic stiffness needs to be established. This study aimed to compare echocardiography-derived RV diastolic stiffness and invasively measured pressure-volume loop-derived RV diastolic stiffness in patients with precapillary PH. We studied 50 consecutive patients with suspected or confirmed precapillary PH who underwent cardiac catheterization, magnetic resonance imaging, and echocardiography within a 1-week interval. Single-beat RV pressure-volume analysis was performed to determine the gold standard for RV diastolic stiffness. Elevated RV end-diastolic pressure (RVEDP) was defined as RVEDP ≥ 8 mmHg. Using continuous-wave Doppler and M-mode echocardiography, an echocardiographic index of RV diastolic stiffness was calculated as the ratio of the atrial-systolic descent of the pulmonary artery-RV pressure gradient derived from pulmonary regurgitant velocity (PRPGDAC) to the tricuspid annular plane movement during atrial contraction (TAPMAC). PRPGDAC/TAPMAC showed significant correlation with β (r = 0.54, p < 0.001) and RVEDP (r = 0.61, p < 0.001). A cut-off value of 0.74 mmHg/mm for PRPGDAC/TAPMAC showed 83% sensitivity and 93% specificity for identifying elevated RVEDP. Multivariate analyses indicated that PRPGDAC/TAPMAC was independently associated with disease severity in patients with precapillary PH, including substantial PH symptoms, stroke volume index, right atrial size, and pressure. PRPGDAC/TAPMAC, based on pulmonary regurgitation velocity waveform analysis, is useful for the noninvasive assessment of RV diastolic stiffness and is associated with prognostic risk factors in precapillary PH.

GNSS gyroscopes: determination of angular velocity and acceleration with very high-rate GNSS

Although global navigation satellite systems (GNSS) have been routinely applied to determine attitudes, there exists no literature on determining angular velocity and/or angular acceleration from GNSS. Motivated by the invention of computerized accelerometers of the correspondence author and following the success of accurately recovering translational velocity and acceleration waveforms from very high-rate GNSS precise positioning by Xu and his collaborators in 2021, we propose the concept of GNSS gyroscopes and reconstruct angular velocity and acceleration from very high-rate GNSS attitudes by applying regularization under the criterion of minimum mean squared errors. The major results from the experiments can be summarized in the following: (i) angular velocity and acceleration waveforms computed by applying the difference methods to high-rate GNSS attitudes are too noisy and can be physically not meaningful and numerically incorrect. The same can be said about inertial measurement unit (IMU) attitudes, if IMU gyros are not of very high accuracy; (ii) regularization is successfully applied to reconstruct the high-rate angular velocity and acceleration waveforms from 50 Hz GNSS attitudes and significantly outperforms the difference methods, validating the proposed concept of GNSS gyroscopes. By comparing the angular velocity and acceleration results by using the difference methods and regularization, we find that the peak values of angular velocity and acceleration by regularization are much smaller by a maximum factor of 1.57 in the angular velocity to a maximum factor of 8662.53 times in the angular acceleration in the case of high-rate GNSS, and by a maximum factor of 1.26 in the angular velocity to a maximum factor of 2819.85 times in the angular acceleration in the case of IMU, respectively; and (iii) the IMU attitudes apparently lead to better regularized angular velocity and acceleration waveforms than the high-rate GNSS attitudes, which can well be explained by the fact that the former is of better accuracy than the latter. As a result, to suppress the significant amplification of noise in GNSS attitudes, larger regularization parameters have to be chosen for the high-rate GNSS attitudes, resulting in smaller peak angular accelerations by a maximum factor of 37.55 percent in the angular velocity to a maximum factor of 6.20 times in the angular acceleration in comparison of the corresponding IMU results. Nevertheless, the regularized angular acceleration waveforms for both GNSS and IMU look more or less similar in pattern or waveform shape.

Investigation of Rupture Risk of Thoracic Aortic Aneurysms via Fluid–Structure Interaction and Artificial Intelligence Method

Patient-specific studies on vascular flows have significantly increased for hemodynamics due to the need for different observation techniques in clinical practice. In this study, we investigate aortic aneurysms in terms of deformation, stress, and rupture risk. The effect of Ascending Aortic Diameter (AAD) was investigated in different aortic arches (19.81 mm, 42.94 mm, and 48.01 mm) via Computational Fluid Dynamics (CFD), Two-way coupling Fluid–Structure Interactions (FSI) and deep learning. The non-newtonian Carreau viscosity model was utilized with patient-specific velocity waveform. Deformations, Wall Shear Stresses (WSSs), von Mises stress, and rupture risk were presented by safety factors. Results show that the WSS distribution is distinctly higher in rigid cases than the elastic cases. Although WSS values rise with the increase in AAD, aneurysm regions indicate low WSS values in both rigid and elastic artery solutions. For the given AADs, the deformations are 2.75 mm, 6. 82 mm, and 8.48 mm and Equivalent von Mises stresses are 0.16 MPa, 0.46 MPa, and 0.53 MPa. When the rupture risk was evaluated for the arteries, the results showed that the aneurysm with AAD of 48.01 mm poses a risk up to three times more than AAD of 19.81 mm. In addition, an Artificial neural network (ANN) method was developed to predict the rupture risk with a 98.6% accurate prediction by numerical data. As a result, FSI could indicate more accurately the level of rupture risk than the rigid artery assumptions to guide the clinical assessments and deep learning methods could decrease the computational costs according to CFD and FSI.

Modeling and friction response analysis of rocking-sliding friction of drill string in directional wells

The main goal of this research is to conduct a quantitative assessment of how rocking influences friction during sliding. The kinetic equations were developed, accounting for the friction coefficient's velocity weakening effect. The model's precision and dependability were confirmed by comparing simulation results against experimental data. Furthermore, the study discovered that the Stribeck model presents benefits when compared to alternative models. Investigations were carried out to examine how rocking parameters affect axial friction during rocking motions. The findings indicate that variations in axial friction forces are predominantly observed during the phase of tangential acceleration. Crucially, the research demonstrates that modulating the rocking velocity's waveform can markedly decrease the average axial friction, even when the maximum rocking speeds remain the same.