Power Doppler Research Articles

Earthquake record truncation metric for nonlinear dynamic analyses of high rockfill dams

The long initial and coda waves with small amplitude are often observed in an actual earthquake record. Truncating those wavebands that contribute little to structural responses is helpful to focus on the strong shaking phase and reduce computational cost. In the paper, 157 actual earthquake records and the acceleration time windows constrained by truncation thresholds of Arias intensity serve as input ground motions. A large number of elastoplastic dynamic analyses on a 295 m-high core-wall rockfill dam (CRFD) are conducted using the generalized plasticity model and seismic wave input method. Inspired by fragility equation, the probability curves for the accuracy loss of dam response less than different limits under different truncation thresholds are established, quantifying the destructiveness of the truncated seismic acceleration time windows. Results show that the probabilities are minimally affected by peak ground acceleration (PGA); the allowable tail truncation of earthquake records is much more than the leading due to the asymmetry of seismic waveforms and the cyclic hardening characteristic of rockfill materials; the truncation metric of 0.01–98 % Arias intensity is proved to be effective and robust in accelerating dynamic analyses of rockfill dams with an accuracy loss within 5 % and an average reduction in computational workload of approximately 50 %.

Cystatin D serum level in rheumatoid arthritis and its relation to disease activity

BackgroundRheumatoid arthritis (RA) is a chronic autoimmune condition that causes synovitis and functional impairment. Currently, the most often utilized biomarkers for monitoring disease activity and severity are acute phase proteins, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP).However, discrepancies have been found between the clinical inflammation and their levels. Therefore, there is a strong need for a novel biomarker to forecast how RA will proceed clinically and monitor the response to therapy. This study assessed the diagnostic value of serum cystatin D in RA patients and its potential as a biomarker for disease activity monitoring.ResultsRA patients had considerably greater serum levels of cystatin D than the control group. These values showed a positive correlation with Disease Activity Score-28 (DAS28), ESR, CRP, grayscale synovitis, power Doppler synovitis, grayscale tenosynovitis (p < 0.001), and erosions, sum scores (p < 0.05). Nonetheless, no noteworthy association was observed between the serum cystatin D levels and sociodemographic data, rheumatoid factor (RF), and anti-cyclic citrullinated peptide (anti-CCP).ConclusionCystatin D serum levels are higher in RA patients compared to healthy subjects and are strongly correlated with the activity of RA. It can be a valuable biomarker for evaluating RA disease activity.

Clinical course and flare predictors in patients with rheumatoid arthritis in low disease activity and ultrasound remission monitored by ultrasound yearly and on-demand: A prospective 2-year observation study

Introduction and objectivesUltrasound (US) remission in rheumatoid arthritis (RA) targets synovitis absence. Tenosynovitis triggers flares. Despite increased ultrasound use, flare patterns among patients with low disease activity (LDA) and ultrasound remission, especially in real-world settings, are poorly understood. This study examined flare rates and predictors of US remission in patients without synovitis or tenosynovitis. Materials and methodsIn a study of 88 patients achieving US remission and LDA, the focus was on the time to the first flare over a 2-year follow-up. US remission, indicated by the absence of active synovitis and tenosynovitis based on a power Doppler (US-PD) score of 0, was assessed on various joints. Flares are defined by the need for additional medication or encountering a US-PD flare. They were monitored at the baseline, 1-year, and 2-year visits with further US evaluation at clinical flare-ups. Baseline factors linked to a shorter time to flare were analyzed. ResultsAt 1 year, LDA and US remission rates were 75% and 92%, respectively, and at 2 years, 73% and 87% respectively. Over the 2 years, 40% experienced flare, occurring on average at 11.7±7.0 months. Notably, 5.7% have US-PD flares without clinical signs. Analysis revealed Stage III disease and CRP as factors linked to a shorter time to flare. Discussion and conclusionsIn patients with RA achieving LDA and US remission, frequent flares were observed with US remission over 2 years, but most maintained sustained remission. Baseline factors are essential for predicting flares, emphasizing continuous monitoring and personalized treatment to sustain remission and minimize flare risks in RA management.

Multiple-point ignition as a driver of flame acceleration at the early stage of burning in channels

In the present study, flame acceleration driven by an array of multiple ignition kernels, equally spaced in the axial direction of a channel closed at one end, is studied numerically. In order to demonstrate the effects of the proposed ignition configuration on the flow dynamics, free-slip wall boundary condition is adopted. It is demonstrated that the burning of multiple flame kernels generates a powerful upstream flow, propelling the flame kernels, with the leading kernel’s tip undergoing a strong exponential acceleration. In a channel with smooth walls, such a powerful acceleration process is limited in time. The present study is mainly focused on the dynamics of the flame during the exponential stage of acceleration. The dependence of the acceleration rate, total acceleration time, and the maximum flame velocity on the initial distance between the kernels, the number of ignition kernels, and the thermal gas expansion coefficient, is quantified. Remarkably, the initial distance between the kernels has a weak influence on the above mentioned characteristics of flame dynamics as long as it is sufficiently large. It is observed that the acceleration rate increases with the kernel number. Notably, a significantly large maximum flame tip velocity can be achieved using the multi-kernel configuration as compared to the single-point ignition scenario. The acceleration rate demonstrates a nearly linear dependence on the thermal expansion coefficient, thus, the increase in thermal expansion results in a considerably stronger flame acceleration process.Novelty and Significance StatementFor the first time, the flame acceleration process upon simultaneous ignition of a multi-point array of hot kernels equally spaced at the centerline of a channel was systematically studied. The work emphasizes the potential for achieving an extremely high flame speed within a very short time as compared to the single-ignition method. The acceleration rate, total acceleration time, and maximum achievable flame velocity were quantified. In a multi-point ignition scenario, we demonstrate that the burning of the fresh mixture between the kernels increases an overall cumulative gas expansion, propelling the leading tip. This result suggests a method for creating a powerful flame acceleration, which is an essential step in deflagration-to-detonation transition. Notably, the powerful acceleration is achieved in channels with smooth walls, which is important for DDT applications, in which using obstructed channels may be associated with a range of operational problems. The simplicity of the setup is also emphasized.

Recursive Bayesian estimation of wind load on a monopile-supported offshore wind turbine using output-only measurements

Offshore wind turbine structures experience combined wind and wave loading during their lifetime, and the cyclic characteristics of these loads significantly impact the fatigue life of the support structure. Continuous monitoring of stress-related quantities, such as strain time histories at hotspot locations of the structure, can help to estimate the fatigue life. However, sparse measurements from the substructure necessitate using a digital twin as a tool for structural health monitoring by creating a virtual model. This virtual model relies on real-time input loads for virtual sensing and stress-related quantities prediction. However, the exact loading on these structural systems is often unknown or estimated with considerable uncertainty. This paper implements a recursive window-based Bayesian estimator for input load estimation and virtual sensing of acceleration and strain time history at unmeasured critical locations using output-only measurements. The estimator is numerically and experimentally validated in the context of input load estimation for an offshore wind turbine, and the results are compared with a traditional augmented Kalman filter and a linear regression approach for the quasi-static component of loading. The method is first demonstrated through a numerical study using a finite element model of a 6 MW offshore wind turbine, where input wind load time histories are accurately estimated. Then, the framework is applied to the real data measured from an offshore wind turbine in the North Sea. The study demonstrates the window-based Bayesian input estimator as a promising tool for the digital twinning of offshore wind turbines, demonstrating superior accuracy in input load estimations and full response predictions compared to the augmented Kalman filter and linear regression methods without the constraint of collocated measurements at input load locations.

FORENSIC IMPLICATIONS OF CARPAL TUNNEL SYNDROME IN RELATION TO RADIOLOGICAL AND ORHOPEDITION

Carpal tunnel syndrome (CTS) is a common peripheral neuropathy with significant clinical and forensic implications. The condition is characterized by compression of the median nerve within the carpal tunnel, leading to pain, tingling, and functional impairment. Accurate diagnosis is crucial not only for clinical management but also for forensic evaluations, especially in cases of occupational claims and medico-legal disputes. Objective: The purpose of this research is to investigate the forensic consequences of carpal tunnel syndrome regarding radiographic and ophthalmic examinations. Methods: This prospective study included 180 individuals, aged 18 to 65 years, of both genders. This study was conducted at the Department of Forensic Medicine LUMHS from January 2023 to June 2023. Group I comprised 90 patients diagnosed with CTS, while Group II included 90 individuals without CTS, serving as controls. Demographic data, including age, sex, and BMI, were recorded. CTS was confirmed using ultrasonographic and other diagnostic modalities. The cross-sectional area of the carpal tunnel at the pisiform (CSAp) and the carpal tunnel at the hook of the hamate (CSAc) was measured. Delta CSA was calculated as the difference between CSAc and CSAp. Sensitivity and specificity for CTS diagnosis were evaluated. Statistical analysis was performed using SPSS Version 26.0. Results: The study found a predominance of females in both groups, with 63 (70%) females in Group I and 58 (64.4%) in Group II. The mean age in Group I was 47.34 ± 8.58 years with a mean BMI of 25.13 ± 10.49 kg/m², while Group II had a mean age of 49.53 ± 12.74 years and a BMI of 26.34 ± 11.61 kg/m². Group I demonstrated significantly higher CSAc values (18.5 ± 3.35 mm²) compared to Group II (9.8 ± 7.25 mm²; p &lt; 0.004). The delta CSA was also higher in Group I (7.37 ± 8.32 mm²) compared to Group II (1.3 ± 2.13 mm²; p &lt; 0.005). The CSAp values showed no significant differences between groups (Group I: 9.4 ± 3.6 mm²; Group II: 7.12 ± 9.6 mm²). A delta CSA threshold of 2 mm² demonstrated high diagnostic accuracy, yielding a sensitivity of 99.1% and specificity of 100% for Group I wrists. Conclusion: Delta CSA is a highly reliable parameter for diagnosing CTS, surpassing CSAc in accuracy. Advanced ultrasonographic techniques, including high-frequency probes and enhanced power Doppler imaging, represent the gold standard for CTS diagnosis, providing robust evidence for both clinical and forensic applications.

Ultrasound diagnosis of first trimester umbilical cord entanglement in monochorionic monoamniotic twins - case report and review of the literature

BackgroundDiagnosis of umbilical cord entanglement (UCE) by ultrasound (US) in monochorionic monoamniotic (MCMA) twins in the second and third trimesters is common. However, only a few cases have been reported on the diagnosis of UCE as early as the first trimester. Herein, we report a case of the earliest-ever sonographic diagnosis of UCE and demonstrate the feasibility of its diagnosis by US.Case presentationA 32-year-old gravida 2 para 1 woman conceived after assisted reproductive technology (ART) treatment. In transvaginal US examination at 8.5 gestational weeks, two embryos with regular heartbeats in the same amniotic sac and with only one yolk sac were demonstrated. The fetal crown-rump lengths were 20 and 21 mm, appropriate for 8.4 and 8.5 gestational weeks, respectively. HD-flow power Doppler 2D and 3D US demonstrated two tightly entangled umbilical cords of the two fetuses. Spectral Doppler US showed two different heart rates (162 and 167 beats per minute) and blood flow in opposite directions from the point of entanglement of the two umbilical cords. This was consistent with a diagnosis of a first-trimester MCMA pregnancy with UCE. Missed abortion of the two embryos was diagnosed by US examination at 10.5 weeks, and the pregnancy was terminated by dilatation and curettage without further complications.ConclusionsUCE in the first trimester may occur as early as eight gestational weeks, and its diagnosis by ultrasound is feasible. UCE diagnosed in the first trimester may be a poor prognostic factor.

Ultrasound visualization and blood flow velocity measurements of the adrenal arteries in the fetus.

Detection and surveillance of fetal growth restriction (FGR) is well established, but there is still room for improvement. Animal studies indicate that compromised fetuses increase adrenal blood flow. Modern ultrasound equipment allows us to measure vascular impedance in the fetal adrenal arteries despite their modest size. However, extensive anatomical variance is a challenge to standardizing measurements. We set out to improve this. We included 75 low-risk pregnant women in a prospective cross-sectional study aiming to develop a reliable technique to visualize and measure flow velocity in human fetal adrenal arteries. We used commercially available ultrasound equipment: a GE Voluson 10 2019 with a C2-9 probe (GE Healthcare, Zipf, Austria), and a Philips Epiq Elite with a V9-2 probe (Philips Medical Systems International B.V., Best, The Netherlands), exploiting the modern sensitive power Doppler modes in both scanners to visualize small vessels. Among 72 fetuses, the inferior adrenal artery was the most consistently visualized and measured artery to the gland. Doppler velocimetry was achieved in 66 (92%) participants. We found the anatomical variation described previously but were able to develop visualization strategies to identify the common arteries and use a consistent Doppler technique for the second half of pregnancy. It is possible to visualize and measure flow velocity in the adrenal arteries of human fetuses. The success rate was highest for the inferior adrenal artery making this vessel a candidate for clinical studies.

Reference Ranges for Third-Trimester Maternal Cardiovascular Function Parameters Measured in Normotensive Pregnant Women Using a Noninvasive Cardiac Output Monitor: A Study Based on Data From the Prospective PEACH Cohort Study

(BJOG. 2024;131:463–471. doi: 10.1111/1471-0528.17667) Changes to the cardiovascular system during pregnancy are expected; however, maladaptation is indicative of pregnancy-related cardiovascular disease and should be screened for. Invasive catheterization and echocardiography have traditionally been the tools used for detection of such conditions; however, more noninvasive alternatives have become available, such as the Ultrasound Cardiac Output Monitor 1A (US-COME-1A). This device uses continuous-wave Doppler ultrasound and has been used in pregnant patients with similar results to third trimester echocardiography. Clinicians would benefit further from reference ranges to make this a more useful tool; thus, this study seeks to provide such reference ranges for cardiac output (CO), stroke volume (SV), and systemic vascular resistance (SVR) in singleton pregnancies.

Thermographic and ultrasound assessment in patients with rheumatoid arthritis: can thermography detect subclinical synovitis at the wrist?

BackgroundThermography is an emerging imaging modality which allows for a quick and objective measure of joint surface temperature in patients with rheumatoid arthritis (RA). To date, there are no published studies comparing thermography with ultrasonography in the subclinical assessment of joint inflammation at the wrist of patients with RA, and no published data on inter-rater reliability for multiple raters for thermographic assessment at the RA wrist. In our study comparing thermography and ultrasonography at the RA wrist, we aim to determine if thermography can detect subclinical synovitis. Additionally, we performed inter-reliability testing (multiple raters) for both thermography and ultrasonography.MethodsThermographic (average (Tavg), maximum (Tmax) and minimum (Tmin) temperatures) and ultrasound (total grey-scale (TGS) score and total power Doppler (TPD) scores) parameters were compared between two patient groups: Asymptomatic Group (with non-swollen and non-tender wrists) and Symptomatic Group (with swollen and/or tender wrists). Among Asymptomatic Group patients, thermographic parameters were compared between those with and without wrist joint recess(es) having ultrasound synovitis (PD ≥ 1 or GS ≥ 2); Spearman’s correlation and simple linear regression were used to study the relationship between thermographic and ultrasound parameters. Intra-class correlation coefficient (ICC) was used for inter-rater reliability calculation.ResultsEighty-seven RA patients’ right wrists were imaged in this cross-sectional study. Thermographic temperatures, TPD and TGS scores were all significantly (p < 0.05) greater among Symptomatic Group versus Asymptomatic Group patients. Among Asymptomatic Group patients, thermographic temperatures were all significantly higher (P < 0.01) in wrists having joint recess(es) with ultrasound PD ≥ 1 or GS ≥ 2, while all thermographic parameters correlated significantly with TPD (correlation coefficient ranging from 0.43 to 0.48, p < 0.001) and TGS (correlation coefficient ranging from 0.33 to 0.37, p < 0.01). The ICC values based on a subset of images obtained for inter-reliability testing were high for thermography (0.994 to 0.998) and ultrasonography (0.933 to 0.952).ConclusionsSwollen and/or tender RA wrists displayed greater thermographic and ultrasound-detected joint inflammation. At clinically quiescent (non-swollen; non-tender) wrists, thermographic temperatures significantly correlated with ultrasound-detected joint inflammation.Clinical trial numberNot applicable.

Persistent pulmonary hypertension in children after apparent resolution of ultrasound-defined pulmonary hypertension associated with bronchopulmonary dysplasia

To evaluate pulmonary hemodynamics in patients who had been followed up for bronchopulmonary dysplasia (BPD)-associated pulmonary hypertension (PH) in the mid-term by right heart catheterization (RHC). A retrospective study was conducted among 56 patients who were born at a gestational age < 28 weeks during 2018–2020, and the consecutive patients complicated by BPD and ultrasound-defined PH (n = 10, 18%), of whom 7 patients were treated with sildenafil, were examined by RHC in the mid-term follow-up (median age: 25 months [IQR: 19–32]). Ultrasound study at RHC showed improvement in PH as represented by left ventricular end-systolic eccentricity index (median [IQR], 1.05 [IQR: 1.03–1.06] vs. 1.18 [IQR: 1.15–1.33]), pulmonary artery acceleration time (PAAT) (mean ± SD, 97.3 ± 18.2 vs. 55.2 ± 10.1) and a ratio of PAAT to right ventricular ejection time (0.35 ± 0.05 vs. 0.25 ± 0.04) compared with those at 40 weeks of postmenstrual age (PMA) (p < 0.05, respectively). RHC (mean pulmonary artery [PA] pressure: 21 [19–22] mmHg; pulmonary vascular resistance index [PVRi]: 2.63 [1.95–2.94] Wood Units·m2) revealed that 5 infants (50%) had mild PH (21–24 mmHg) and reduced peripheral PAs by pulmonary wedge angiography. The presence of emphysema on chest CT at 40 weeks of PMA and moderate/marked reduction of contrast filling in peripheral PAs on angiography were correlated with increased PVRi (p < 0.05, respectively). Conclusion: We observed that even after apparent resolution of ultrasound-defined PH, half of patients had catheterization-defined PH and vasculopathy at 2 years of age. These findings warrant long-term follow-up studies of BPD-associated PH.What is Known:• Pulmonary hypertension (PH) is associated with increased mortality in infants with bronchopulmonary dysplasia (BPD). Mortality in patients with BPD-associated PH predominantly occurs within the first 6 months of life and most patients who survive beyond 6 months show resolution of PH on echocardiography by 2 to 3 years of age.What is New:• Even after the resolution of echocardiography-derived PH in infants with BPD-associated PH in the mid-term, the majority of such patients have abnormal pulmonary vasculature with PH or mildly elevated pulmonary artery pressure on right heart catheterization (RHC), indicating that echocardiography is insufficient and RHC may be necessary to follow up this population of patients.

Multi-objective optimization shift strategy for vehicle based on adaptive linear weighted sum method

The shift strategy plays a pivotal role in influencing the power and economy performance of vehicles. In order to improve the adaptability of shift to dynamic driving conditions, this paper proposes a comprehensive shift strategy. This study employs the FMRLS algorithm to establish a model for identifying vehicle mass and road slope and presents a model for altitude identification based on SVM. The comprehensive shift strategy is formulated by using the NSGA-II algorithm to calculate the Pareto front of the shift speeds and determine the power and economy weights for different driving conditions based on the linear weighted sum method in an adaptive manner. The simulation results show that the energy consumption of the comprehensive shift strategy is close to the economy shift strategy under the CHTC-HT condition. Significantly, the maximum difference is 2.97% in acceleration time between the comprehensive and the power shift strategy under plateau condition. Additionally, the comprehensive shift strategy can eliminate cyclic shift on upslope and provide braking force in response to the driver intention to decelerate on downslope, improving vehicle safety, and dynamic adaptability.

Longitudinal evaluation of hemodynamic blood and echocardiographic biomarkers for the prediction of BPD and BPD-related pulmonary hypertension in very-low-birth-weight preterm infants

Very-low-birth-weight infants (VLBW, < 1500 g) are at risk of developing bronchopulmonary dysplasia (BPD) and are at risk for BPD-related pulmonary hypertension (PH). The longitudinal measurement of innovative blood and echocardiographic biomarkers might allow for a risk stratification of these infants. A prospective single-center cohort study was conducted between 01/2021 and 06/2023. Inclusion criteria were the combination of a birth weight < 1500 g and a gestational age (GA) ≤ 30/0 weeks. Assessment timepoints: T1 (day 7), T2 (day 28), and T3 (at 36 weeks post-menstrual age, PMA). Overall, 71 preterm infants were included for final analysis. The Zlog-transformed NTproBNPZlog (at T1 AUC 0.772; p = 0.019; at T2 AUC 0.874, p = 0.002), and endothelin-1 (ET1, at T1 AUC 0.789, p = 0.013) were identified as an early predictive biomarker for BPD/death in the univariate analysis. Additionally, echocardiographic markers of ventricular function and PH at T1 were predictive for BPD/death in the univariate analysis, with the highest predictivity found for the tricuspid annular plane systolic excursion-TAPSE (AUC 0.748, p = 0.016) and the pulmonary artery acceleration time to right ventricular ejection time (PAAT/RVET; AUC 0.744, p = 0.043). Regarding predictability of mortality alone NTroBNPZlog (at T1 AUC 0.973, p = 0.000), and CA125 (at T1 AUC 0.747, p = 0.008) were identified as potential predictors, as well as TAPSE (AUC 0.926, p = 0.000), and PAAT/RVET (AUC 0.985, p = 0.000) Several biomarkers including ET-1 (at T1 AUC 0.893, p = 0.000), TAPSE (AUC 0.974, p = 0.000), and PAAT/RVET (AUC 1.0, p = 0.000) at T1 were identified as univariate predictors for BPD-PH. In the multivariate analysis, no biomarker was identified as an independent predictor of the primary endpoint. Conclusion: Mainly at an early stage of postnatal neonatal care in VLBW preterm infants, several biomarkers were found to be associated with the combined endpoint BPD/death and BPD-PH. New candidates of blood biomarkers (NTproBNPZlog, ET-1, and CA125) and echocardiographic markers (TAPSE, PAAT/RVET) might serve as innovative predictors for BPD, BPD-PH, and adverse outcomes in VBLW infants. What is Known:• VLBW infants are at risk for the development of BPD and BPD-related PH, which both are main contributors for short and long-term morbidity and mortality. Several studies in the past focused on the evaluation of circulating blood biomarkers and biomarkers from echocardiographic assessment of these infants. But to date, there is still a lack on longitudinal prospective studies especially in VLBW infants.What is New:• For the first time, this set of selected blood biomarkers (with the first description of Zlog-transformed NTproBNP and CA125 in preterm infants) and several echocardiographic markers were analyzed in a prospective longitudinal study from birth until 36 weeks post menstrual age in VLBW infants. Our data help clinicians to identify preterm infants at risk for BPD, BPD-PH and death and to offer new candidates of biomarkers. This might help to facilitate decision making and guidance of therapy in these highly vulnerable patients.

Big fish can't jump? Allometry of terrestrial jumping in cyprinodontiform fishes.

Teleost fishes that emerge onto land must produce effective terrestrial movements to return to the water. Using the Cyprinodontiformes as a model system, we examined a terrestrial behavior termed the tail-flip jump across a size range of individuals representing three species of aquatic killifishes (Gambusia affinis, Poecilia mexicana, and Jordanella floridae) and two species of amphibious killifishes (Kryptolebias marmoratus and Fundulus heteroclitus) to identify potential effects of size (mass) on jumping performance. The ballistic trajectory equation was used to partition the contributions of velocity (determined by acceleration and contact time) and takeoff angle to jump distance. Despite differences in size (over an order of magnitude) all fishes took off from the ground at ∼45°. However, in terms of total displacement, aquatic and amphibious killifish species scaled differently in their ability to perform the tail-flip jump. Aquatic killifishes decrease in total jump distance as mass increases; however, amphibious killifishes increase in total jump distance as mass increases. Aquatic killifishes cannot produce adequate accelerations at larger sizes, but amphibious killifishes produce similar accelerations despite over an order of magnitude size difference. Because of this, amphibious killifish species are able to maintain fast takeoff velocities at large body sizes. Distinct scaling patterns may be generated by differences in body shape. Aquatic killifishes have a fusiform body shape, with most of their body mass in the anterior of the body, while amphibious killifishes have a more uniform body shape that reduces their overall mass present in the anterior body. We hypothesize that reduced mass in the anterior body facilitates raising the head over the tail to prepare for takeoff. In contrast with amphibious species, the negative scaling relationship seen in body size vs. displacement in aquatic killifishes implies an upper size limit to producing the tail-flip jump for fish species that infrequently encounter the terrestrial environment.

Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study.

Three-dimensional gait analysis, supported by advanced sensor systems, is a crucial component in the rehabilitation assessment of post-stroke hemiplegic patients. However, the sensor data generated from such analyses are often complex and challenging to interpret in clinical practice, requiring significant time and complicated procedures. The Gait Deviation Index (GDI) serves as a simplified metric for quantifying the severity of pathological gait. Although isokinetic dynamometry, utilizing sophisticated sensors, is widely employed in muscle function assessment and rehabilitation, its application in gait analysis remains underexplored. This study aims to investigate the use of sensor-acquired isokinetic muscle strength data, combined with machine learning techniques, to predict the GDI in hemiplegic patients. This study utilizes data captured from sensors embedded in the Biodex dynamometry system and the Vicon 3D motion capture system, highlighting the integration of sensor technology in clinical gait analysis. This study was a cross-sectional, observational study that included a cohort of 150 post-stroke hemiplegic patients. The sensor data included measurements such as peak torque, peak torque/body weight, maximum work of repeated actions, coefficient of variation, average power, total work, acceleration time, deceleration time, range of motion, and average peak torque for both flexor and extensor muscles on the affected side at three angular velocities (60°/s, 90°/s, and 120°/s) using the Biodex System 4 Pro. The GDI was calculated using data from a Vicon 3D motion capture system. This study employed four machine learning models-Lasso Regression, Random Forest (RF), Support Vector regression (SVR), and BP Neural Network-to model and validate the sensor data. Model performance was evaluated using mean squared error (MSE), the coefficient of determination (R2), and mean absolute error (MAE). SHapley Additive exPlanations (SHAP) analysis was used to enhance model interpretability. The RF model outperformed others in predicting GDI, with an MSE of 16.18, an R2 of 0.89, and an MAE of 2.99. In contrast, the Lasso Regression model yielded an MSE of 22.29, an R2 of 0.85, and an MAE of 3.71. The SVR model had an MSE of 31.58, an R2 of 0.82, and an MAE of 7.68, while the BP Neural Network model exhibited the poorest performance with an MSE of 50.38, an R2 of 0.79, and an MAE of 9.59. SHAP analysis identified the maximum work of repeated actions of the extensor muscles at 60°/s and 120°/s as the most critical sensor-derived features for predicting GDI, underscoring the importance of muscle strength metrics at varying speeds in rehabilitation assessments. This study highlights the potential of integrating advanced sensor technology with machine learning techniques in the analysis of complex clinical data. The developed GDI prediction model, based on sensor-acquired isokinetic dynamometry data, offers a novel, streamlined, and effective tool for assessing rehabilitation progress in post-stroke hemiplegic patients, with promising implications for broader clinical application.

Patient-specific, multiscale modelling of neointimal hyperplasia in lower-limb vein grafts using readily available clinical data

The prediction of neointimal hyperplasia (NIH) growth, leading to vein graft failure in lower-limb peripheral arterial disease (PAD), is hindered by the multifactorial and multiscale mechanobiological mechanisms underlying the vascular remodelling process. Multiscale in silico models, linking patients’ hemodynamics to NIH pathobiological mechanisms, can serve as a clinical support tool to monitor disease progression. Here, we propose a new computational pipeline for simulating NIH growth, carefully balancing model complexity/inclusion of mechanisms and readily available clinical data, and we use it to predict NIH growth for an entire vein graft. To this end, three different fittings to published in vitro data of time-averaged wall shear stress (TAWSS) vs nitric oxide (NO) production were tested for predicting long-term graft response (10-month follow-up) on a single patient. Additionally, the sensitivity of the model’s predictions to different inflow boundary conditions (BCs) was assessed. The main findings indicate that: (i) a TAWSS-NO hyperbolic relationship best predicts long-term graft response; (ii) the model is insensitive to the inflow BCs if the waveform shape and the systolic acceleration time are comparable with the one acquired at the same time as the computed-tomography scan. This proof-of-concept study demonstrates the potential of using multiscale, computational techniques to predict NIH growth in lower-limb vein grafts, considering the routine clinical scenario of non-standardised data collection and sparse, incomplete datasets.

Abstract 4136290: Toward Quantitative Assessment of Cerebrovascular Autoregulation in Neonates using Ultrafast Ultrasound Power Doppler

Introduction: Newborns with congenital heart diseases requiring cardiopulmonary bypass are at risk of neurodevelopmental impairment. The impact of deep hypothermia during cardiopulmonary bypass (DH-CPB) on cerebrovascular autoregulation (CAR) that controls brain perfusion in the presence of variable blood pressure is not well understood. Recently, Ultrafast Power Doppler (UPD) showed potential to study CAR in neonates based on the measurement of cerebral blood volume (CBV). However, since CAR relies mainly on the arterial vasoconstriction/vasodilation, the interpretation of brain perfusion based on CBV requires further separation of arterial CBV from total CBV. This study aims to use UPD to monitor CAR during DH-CPB in neonates. Methods: An ultrasonic probe (5.7 MHz) was placed on the anterior fontanel of 6 newborns before, during and after DH-CPB. Using ultrafast sequences generated by a Verasonic Vantage research system, mid-coronal plane images were acquired (PRF of 9 kHz, 5 compounded diverging waves). An adaptive spatiotemporal singular value decomposition was used to separate the blood signal from tissue signal and obtain UPD. CBV was computed in the deep gray matter (DGM). This region was chosen due to its higher susceptibility to hypoxic-ischemic injury. Arterial CBV was isolated from total CBV based on the upward arterial flow obtained using signed-power Doppler (See Fig A). Pearson correlation ® was computed between mean arterial blood pressure (MAP) and arterial CBV to study CAR. Results: Before and after DH-CPB, negative correlations were found between arterial CBV and MAP: -0.30 and -0.43 respectively. This indicates that an increase in MAP is associated with a decrease in cerebral arterial blood volume. This decrease in arterial CBV likely arises from arterial vasoconstriction, suggesting an active CAR response. Conversely, during DH-CPB, no correlation was found (r = -0.02). This means that despite the increase in MAP, arterial CBV remains unchanged. This lack of variation of arterial CBV is likely due to absent arterial vasoconstriction, suggesting an impaired CAR response. Conclusion: Our findings highlight the potential of UPD for continuous monitoring of CAR, paving the way for improving neurovascular management strategies during DH- CPB.

Abstract 4118444: Right Ventricular Contractile Reserve and Right Ventricular-Pulmonary Arterial Coupling Are Impaired in Long-Term Survivors of Childhood Cancers

Background: Childhood cancer survivors are at risk of right ventricular (RV) dysfunction in relation to cardiac toxicity due to chemotherapy and radiation therapy. This study tested the hypothesis that RV contractile reserve and RV-pulmonary arterial (PA) coupling are altered in long-term survivors of childhood cancers. Methods: Thirty survivors (60% men) aged 24.3 ± 5.2 years at 15.3 ± 6.3 years after completion of chemotherapy and thirty healthy control subjects (47% men) were studied. Resting and submaximal supine bicycle stress echocardiography was performed for assessment of RV fractional area change (FAC), tricuspid annular plane systolic excursion (TAPSE), left ventricular (LV) and RV longitudinal strain, mitral and tricuspid annular velocities and myocardial acceleration during isovolumic contraction (IVA). The slope of the RV force-frequency relationship was derived from the change in IVA with the change in heart rate during exercise (△IVA/△heart rate), while RV-PA coupling was determined by the ratio between TAPSE and pulmonary arterial acceleration time indexed to RV ejection time (PAATi). Results: At rest, tricuspid annular systolic velocity and RV systolic strain were significantly lower in survivors ( P &lt; 0.05 for both), while RV FAC, TAPSE and IVA were similar between the two groups ( P &gt; 0.05 for all). During submaximal exercise testing, all RV systolic functional indices were significantly lower in survivors than controls ( P &lt; 0.05 for all). The slope of the RV force-frequency relationship was significantly flatter in survivors compared to controls (0.038 ± 0.002 vs 0.059 ± 0.003 m/sec 2 beats/min, P &lt; 0.001). For RV-PA coupling, TAPSE/PAATi was similar between survivors and controls at baseline but became significantly lower in survivors during submaximal exercise ( P = 0.002). Conclusions: The RV contractile reserve and RV-PA coupling are impaired during exercise in long-term survivors of childhood cancers. Future studies aimed at determining the clinical and prognostic significance of these impairments are warranted.

Explaining deep learning models for age-related gait classification based on acceleration time series

BackgroundGait analysis holds significant importance in monitoring daily health, particularly among older adults. Advancements in sensor technology enable the capture of movement in real-life environments and generate big data. Machine learning, notably deep learning (DL), shows promise to use these big data in gait analysis. However, the inherent black-box nature of these models poses challenges for their clinical application. This study aims to enhance transparency in DL-based gait classification for aged-related gait patterns using Explainable Artificial Intelligence, such as SHapley Additive exPlanations (SHAP). MethodsIn this cross-sectional study, a total of 244 participants, comprising 129 adults and 115 older adults (age>65), were included. They performed a 3-min walking task while accelerometers were affixed to the lumbar segment L3. DL models, convolutional neural network (CNN) and gated recurrent unit (GRU), were trained using 1-stride and 8-stride accelerations, respectively, to classify adult and older adult groups. SHAP was employed to explain the models' predictions. ResultsCNN achieved a satisfactory performance with an accuracy of 81.4 % and an AUC of 0.89, and GRU demonstrated promising results with an accuracy of 84.5 % and an AUC of 0.94. SHAP analysis revealed that both CNN and GRU assigned higher SHAP values to the data from vertical and walking directions, particularly emphasizing data around heel contact, spanning from the terminal swing to loading response phases. Furthermore, SHAP values indicated that GRU did not treat every stride equally. ConclusionCNN accurately distinguished between adults and older adults based on the characteristics of a single stride's data. GRU achieved accurate classification by considering the relationships and subtle differences between strides. In both models, data around heel contact emerged as most critical, suggesting differences in acceleration and deceleration patterns during walking between different age groups.

A deep learning-based method for assessing tricuspid regurgitation using continuous wave Doppler spectra

Transthoracic echocardiography (TTE) is widely recognized as one of the principal modalities for diagnosing tricuspid regurgitation (TR). The diagnostic procedures associated with conventional methods are intricate and labor-intensive, with human errors leading to measurement variability, with outcomes critically dependent on the operators’ diagnostic expertise. In this study, we present an innovative assessment methodology for evaluating TR severity utilizing an end-to-end deep learning system. This deep learning system comprises a segmentation model of single cardiac cycle TR continuous wave (CW) Doppler spectra and a classification model of the spectra, trained on the TR CW Doppler spectra from a cohort of 11,654 patients. The efficacy of this intelligent assessment methodology was validated on 1500 internal cases and 573 external cases. The receiver operating characteristic (ROC) curves of the internal validation results indicate that the deep learning system achieved the areas under curve (AUCs) of 0.88, 0.84, and 0.89 for mild, moderate, and severe TR, respectively. The ROC curves of the external validation results demonstrate that the system attained the AUCs of 0.86, 0.79, and 0.87 for mild, moderate, and severe TR, respectively. Our study results confirm the feasibility and efficacy of this novel intelligent assessment method for TR severity.