Translating proof-of-concept for platelet slip into improved antithrombotic therapeutic regimens.

Platelets are central to thrombosis. Research at the intersection of biological and physical sciences provides proof-of-concept for shear rate-dependent platelet slip at vascular stenosis and near device surfaces. Platelet slip extends the observed biological "slip-bonds" to the boundary of functional gliding without contact. As a result, there is diminished engagement of the coagulation cascade by platelets at these surfaces. Comprehending platelet slip would more precisely direct antithrombotic regimens for different shear environments, including for percutaneous coronary intervention (PCI). In this brief report we promote translation of the proof-of-concept for platelet slip into improved antithrombotic regimens by: (1) reviewing new supporting basic biological science and clinical research for platelet slip; (2) hypothesizing the principal variables that affect platelet slip; (3) applying the consequent construct model in support of-and in some cases to challenge-relevant contemporary guidelines and their foundations (including for urgent, higher-risk PCI); and (4) suggesting future research pathways (both basic and clinical). Should future research demonstrate, explain and control platelet slip, then a paradigm shift for choosing and recommending antithrombotic regimens based on predicted shear rate should follow. Improved clinical outcomes with decreased complications accompanying this paradigm shift for higher-risk PCI would also result in substantive cost savings.

Enhanced echocardiographic assessment of intracardiac flow in congenital heart disease.

BACKGROUND: 4D flow magnetic resonance imaging (4D flow MRI) can assess and measure the complex flow patterns of the right ventricle (RV) in congenital heart diseases, but its limited availability makes the broad application of intracardiac flow assessment challenging. Color Doppler imaging velocity reconstruction from conventional echocardiography is an emerging alternative, but its validity against 4D flow MRI needs to be established. OBJECTIVE: To compare intracardiac flow parameters measured by color Doppler velocity reconstruction (DoVeR) against parameters measured from 4D flow MRI. METHODS: We analyzed 20 subjects, including 7 normal RVs and 13 abnormal RVs (10 with repaired Tetralogy of Fallot, and 3 with atrial-level shunts). Intracardiac flow parameters such as relative pressure difference, vortex strength, total kinetic energy, and viscous energy loss were quantified using DoVeR and 4D flow MRI. The agreement between the two methods was determined by comparing the spatial fields and quantifying the cross-correlation and normalized difference between time-series measurements. RESULTS: The hemodynamic parameters obtained from DoVeR and 4D flow MRI showed similar flow characteristics and spatial distributions. The time evolutions of the parameters were also in good agreement between the two methods. The median correlation coefficient between the time-series of any parameter was between 0.87 and 0.92, and the median L2-norm deviation was between 10% to 14%. CONCLUSIONS: Our study shows that DoVeR is a reliable alternative to 4D flow MRI for quantifying intracardiac hemodynamic parameters in the RV.

An experimentally validated cavitation inception model for spring-driven autoinjectors.

Cavitation, the formation and collapse of vapor-filled bubbles, poses a problem in spring-driven autoinjectors (AIs). It occurs when the syringe accelerates abruptly during activation, causing pressure fluctuations within the liquid. These bubbles expand and then collapse, generating shock waves that can harm both the device and the drug molecules. This issue stems from the syringe's sudden acceleration when the driving rod hits the plunger. To better understand cavitation in AIs, we explore how design factors like drive spring force, air gap size, and fluid viscosity affect its likelihood and severity. We use a dynamic model for spring-driven autoinjectors to predict and analyze the factors contributing to cavitation initiation and severity. This model predicts the motion of AI components, such as the displacement and velocity of the syringe barrel, and allows us to investigate pressure wave propagation and the subsequent dynamics of cavitation under various operating conditions. We investigated different air gap heights (from 1 to 4 mm), drive spring forces (from 8 to 30 N), and drug solution viscosities (from 1 to 18 cp) to assess cavitation inception based on operational parameters. Results reveal that AI dynamics and cavitation onset and severity strongly depend upon AI operating parameters, namely drive spring force and air gap height. The maximum syringe acceleration increases with spring stiffness and decreases with air gap height; increases in air gap height prolong the time interval of syringe acceleration but diminish the maximum syringe acceleration. From actuation to injection, air gap pressure peaks twice, first due to impact with the rod/plunger and secondly due to the deacceleration event upon injection. The maximum air gap pressure increases with spring stiffness and decreases with air gap height. Results show that maximum cavitation bubble radii and collapse-driven extension rates occur with higher driver spring forces, smaller air gap heights, and less viscous solutions. A cavitation criterion is developed for cavitation in autoinjectors that concludes that cavitation in autoinjectors depends on the peak syringe acceleration.

Quantifying Numerical Uncertainty in Background-Oriented Schlieren.

Our study presents and evaluates a method for computing the numerical uncertainty in Background Oriented Schlieren (BOS). We use Richardson extrapolation to assess the uncertainty of numerical integration of density gradients, based on residuals of density results across two grid levels. By integrating this numerical uncertainty with the existing random uncertainty, we obtain the final uncertainty of the density field. We assess the method's effectiveness using synthetic fields with artificial noise. Our error analysis shows that the sharpness of the density gradient significantly affects bias error and the prediction of numerical uncertainty. The prediction of numerical uncertainty corresponds to variations in bias error, particularly when the noise level and wavelength of the flow field are altered. By accounting for the numerical uncertainty, our method achieves up to 91% accuracy in predicting total uncertainty, as measured against the root-mean-square of the total error. We further demonstrate the utility of our methodology by applying it to experimental BOS images. Our proposed approach offers a more accurate understanding of uncertainty estimation in the BOS technique, with implications for future experiments.

Interpenetrating Networks of Collagen and Hyaluronic Acid That Serve as In Vitro Tissue Models for Assessing Macromolecular Transport.

High-fidelity preclinical in vitro tissue models can reduce the failure rate of drugs entering clinical trials. Collagen and hyaluronic acid (HA) are major components of the extracellular matrix of many native tissues and affect therapeutic macromolecule diffusion and recovery through tissues. Although collagen and HA are commonly used in tissue engineering, the physical and mechanical properties of these materials are variable and depend highly on processing conditions. In this study, HA was chemically modified and crosslinked via hydrazone bonds to form interpenetrating networks of crosslinked HA (HAX) with collagen (Col). These networks enabled a wide range of mechanical properties, including stiffness and swellability, and microstructures, such as pore morphology and size, that can better recapitulate diverse tissues. We utilized these interpenetrating ColHAX hydrogels as in vitro tissue models to examine macromolecular transport and recovery for early-stage drug screening. Hydrogel formulations with varying collagen and HAX concentrations imparted different gel properties based on the ratio of collagen to HAX. These gels were stable and swelled up to 170% of their original mass, and the storage moduli of the ColHAX gels increased over an order of magnitude by increasing collagen and HA concentration. Interestingly, when HAX concentration was constant and collagen concentration increased, both the pore size and spatial colocalization of collagen and HA increased. HA in the system dominated the ζ-potentials of the gels. The hydrogel and macromolecule properties impacted the mass transport and recovery of lysozyme, ß-lactoglobulin, and bovine serum albumin (BSA) from the ColHAX gels─large molecules were largely impacted by mesh size, whereas small molecules were influenced primarily by electrostatic forces. Overall, the tunable properties demonstrated by the ColHAX hydrogels can be used to mimic different tissues for early-stage assays to understand drug transport and its relationship to matrix properties.

Computational modeling of the effect of skin pinch and stretch on subcutaneous injection of monoclonal antibodies using autoinjector devices.

Subcutaneous injection of monoclonal antibodies (mAbs) has experienced unprecedented growth in the pharmaceutical industry due to its benefits in patient compliance and cost-effectiveness. However, the impact of different injection techniques and autoinjector devices on the drug's transport and uptake is poorly understood. Here, we develop a biphasic large-deformation chemomechanical model that accounts for the components of the extracellular matrix that govern solid deformation and fluid flow within the subcutaneous tissue: interstitial fluid, collagen fibers and negatively charged proteoglycan aggregates. We use this model to build a high-fidelity representation of a virtual patient performing a subcutaneous injection of mAbs. We analyze the impact of the pinch and stretch methods on the injection dynamics and the use of different handheld autoinjector devices. The results suggest that autoinjector base plates with a larger device-skin contact area cause significantly lower tissue mechanical stress, fluid pressure and fluid velocity during the injection process. Our simulations indicate that the stretch technique presents a higher risk of intramuscular injection for autoinjectors with a relatively long needle insertion depth.

Mechanistic Computational Modeling of Implantable, Bioresorbable Drug Release Systems.

Implantable, bioresorbable drug delivery systems offer an alternative to current drug administration techniques; allowing for patient-tailored drug dosage, while also increasing patient compliance. Mechanistic mathematical modeling allows for the acceleration of the design of the release systems, and for prediction of physical anomalies that are not intuitive and may otherwise elude discovery. This study investigates short-term drug release as a function of water-mediated polymer phase inversion into a solid depot within hours to days, as well as long-term hydrolysis-mediated degradation and erosion of the implant over the next few weeks. Finite difference methods are used to model spatial and temporal changes in polymer phase inversion, solidification, and hydrolysis. Modeling reveals the impact of non-uniform drug distribution, production and transport of H+ ions, and localized polymer degradation on the diffusion of water, drug, and hydrolyzed polymer byproducts. Compared to experimental data, the computational model accurately predicts the drug release during the solidification of implants over days and drug release profiles over weeks from microspheres and implants. This work offers new insight into the impact of various parameters on drug release profiles, and is a new tool to accelerate the design process for release systems to meet a patient specific clinical need.

Automatic 4D Flow MRI Segmentation Using the Standardized Difference of Means Velocity.

We present a method to automatically segment 4D flow magnetic resonance imaging (MRI) by identifying net flow effects using the standardized difference of means (SDM) velocity. The SDM velocity quantifies the ratio between the net flow and observed flow pulsatility in each voxel. Vessel segmentation is performed using an F-test, identifying voxels with significantly higher SDM velocity values than background voxels. We compare the SDM segmentation algorithm against pseudo-complex difference (PCD) intensity segmentation of 4D flow measurements in in vitro cerebral aneurysm models and 10 in vitro Circle of Willis (CoW) datasets. We also compared the SDM algorithm to convolutional neural network (CNN) segmentation in 5 thoracic vasculature datasets. The in vitro flow phantom geometry is known, while the ground truth geometries for the CoW and thoracic aortas are derived from high-resolution time-of-flight (TOF) magnetic resonance angiography and manual segmentation, respectively. The SDM algorithm demonstrates greater robustness than PCD and CNN approaches and can be applied to 4D flow data from other vascular territories. The SDM to PCD comparison demonstrated an approximate 48% increase in sensitivity in vitro and 70% increase in the CoW, respectively; the SDM and CNN sensitivities were similar. The vessel surface derived from the SDM method was 46% closer to the in vitro surfaces and 72% closer to the in vitro TOF surfaces than the PCD approach. The SDM and CNN approaches both accurately identify vessel surfaces. The SDM algorithm is a repeatable segmentation method, enabling reliable computation of hemodynamic metrics associated with cardiovascular disease.

Complex hemolymph circulation patterns in grasshopper wings.

An insect's living systems-circulation, respiration, and a branching nervous system-extend from the body into the wing. Wing hemolymph circulation is critical for hydrating tissues and supplying nutrients to living systems such as sensory organs across the wing. Despite the critical role of hemolymph circulation in maintaining healthy wing function, wings are often considered "lifeless" cuticle, and flows remain largely unquantified. High-speed fluorescent microscopy and particle tracking of hemolymph in the wings and body of the grasshopper Schistocerca americana revealed dynamic flow in every vein of the fore- and hindwings. The global system forms a circuit, but local flow behavior is complex, exhibiting three distinct types: pulsatile, aperiodic, and "leaky" flow. Thoracic wing hearts pull hemolymph from the wing at slower frequencies than the dorsal vessel; however, the velocity of returning hemolymph (in the hindwing) is faster than in that of the dorsal vessel. To characterize the wing's internal flow mechanics, we mapped dimensionless flow parameters across the wings, revealing viscous flow regimes. Wings sustain ecologically important insect behaviors such as pollination and migration. Analysis of the wing circulatory system provides a template for future studies investigating the critical hemodynamics necessary to sustaining wing health and insect flight.

Intracardiac Flow Analysis of the Right Ventricle in Pediatric Patients With Repaired Tetralogy of Fallot Using a Novel Color Doppler Velocity Reconstruction.

BACKGROUND: Repaired tetralogy of Fallot (RTOF) patients will develop right ventricular (RV) dysfunction from chronic pulmonary regurgitation (PR). Cardiac magnetic resonance sequences such as four-dimensional flow can demonstrate altered vorticity and flow energy loss (FEL); however, they are not as available as conventional echocardiography (echo). The study determined whether a novel, vendor-independent Doppler velocity reconstruction (DoVeR) could measure RV intracardiac flow in conventional echo of RTOF patients. The primary hypothesis was that DoVeR could detect increased vorticity and diastolic FEL in RTOF patients. METHODS: Repaired tetralogy of Fallot patients with echo were retrospectively paired with age-/size-matched controls. Doppler velocity reconstruction employed the stream function-vorticity equation to approximate intracardiac flow fields from color Doppler. A velocity field of the right ventricle was reconstructed from the apical 4-chamber view. Vortex strength (VS, area integral of vorticity) and FEL were derived from DoVeR. Cardiac magnetic resonance and exercise stress parameters (performed within 1 year of echo) were collected for analysis. RESULTS: Twenty RTOF patients and age-matched controls were included in the study. Mean regurgitant fraction was 40.5% ± 7.6%, and indexed RV end-diastolic volume was 158 ± 36 mL/m2. Repaired tetralogy of Fallot patients had higher total, mean diastolic, and peak diastolic VS (P = .0013, P = .0012, P = .0032, respectively) and higher total, mean diastolic, and peak diastolic body surface area-indexed FEL (P = .0016, P = .0022, P < .001, respectively). Peak diastolic indexed FEL and peak diastolic VS had weak-to-moderate negative correlation with RV ejection fraction (r = -0.52 [P = .019] and r = -0.49 [P = .030], respectively) and left ventricular ejection fraction (r = -0.47 [P = .034] and r = -0.64 [P = .002], respectively). Mean diastolic indexed FEL and VS had moderate-to-strong negative correlation with percent predicted maximal oxygen consumption (r = -0.69 [P = .012] and r = -0.75 [P = .006], respectively). CONCLUSIONS: DoVeR can detect alterations to intracardiac flow in RTOF patients from conventional color Doppler imaging. Echo-based measures of diastolic VS and FEL correlated with ventricular function. DoVeR has the potential to provide serial evaluation of abnormal flow dynamics in RTOF patients.

Investigation of macromolecular transport through tunable collagen hyaluronic acid matrices.

Therapeutic macromolecules possess properties such as size and electrostatic charge that will dictate their transport through subcutaneous (SC) tissue and ultimate bioavailability and efficacy. To improve therapeutic design, platforms that systematically measure the transport of macromolecules as a function of both drug and tissue properties are needed. We utilize a Transwell chamber with tunable collagen-hyaluronic acid (ColHA) hydrogels as an in vitro model to determine mass transport of macromolecules using non-invasive UV spectroscopy. Increasing hyaluronic acid (HA) concentration from 0 to 2 mg/mL within collagen gels decreases the mass transport of five macromolecules independent of size and charge and results in a maximum decrease in recovery of 23.3% in the case of bovine immunoglobulin G (IgG). However, in a pure 10 mg/mL HA solution, negatively-charged macromolecules bovine serum albumin (BSA), ß-lactoglobulin (BLg), dextran (Dex), and IgG had drastically increased recovery by 20-40% compared to their performance in ColHA matrices. This result was different from the positively-charged macromolecule Lysozyme (Lys), which, despite its small size, showed reduced recovery by 3% in pure HA. These results demonstrate two distinct regimes of mass transport within our tissue model. In the presence of both collagen and HA, increasing HA concentrations decrease mass transport; however, in the absence of collagen, the high negative charge of HA sequesters and increases residence time of positively-charged macromolecules and decreases residence time of negatively-charged macromolecules. Through our approach, ColHA hydrogels serve as a platform for the systematic evaluation of therapeutic macromolecule transport as a function of molecular characteristics.

Multi-feature-Based Robust Cell Tracking.

Cell tracking algorithms have been used to extract cell counts and motility information from time-lapse images of migrating cells. However, these algorithms often fail when the collected images have cells with spatially and temporally varying features, such as morphology, position, and signal-to-noise ratio. Consequently, state-of-the-art algorithms are not robust or reliable because they require manual inputs to overcome the cell feature changes. To address these issues, we present a fully automated, adaptive, and robust feature-based cell tracking algorithm for the accurate detection and tracking of cells in time-lapse images. Our algorithm tackles measurement limitations twofold. First, we use Hessian filtering and adaptive thresholding to detect the cells in images, overcoming spatial feature variations among the existing cells without manually changing the input thresholds. Second, cell feature parameters are measured, including position, diameter, mean intensity, area, and orientation, and these parameters are simultaneously used to accurately track the cells between subsequent frames, even under poor temporal resolution. Our technique achieved a minimum of 92% detection and tracking accuracy, compared to 16% from Mosaic and Trackmate. Our improved method allows for extended tracking and characterization of heterogeneous cell behavior that are of particular interest for intravital imaging users.

Modeling large-volume subcutaneous injection of monoclonal antibodies with anisotropic porohyperelastic models and data-driven tissue layer geometries.

Subcutaneous injection of therapeutic monoclonal antibodies (mAbs) has become one of the fastest-growing fields in the pharmaceutical industry. The transport and mechanical processes behind large volume injections are poorly understood. Here, we leverage a large-deformation poroelastic model to study high-dose, high-speed subcutaneous injection. We account for the anisotropy of subcutaneous tissue using of a fibril-reinforced porohyperelastic model. We also incorporate the multi-layer structure of the skin tissue, generating data-driven geometrical models of the tissue layers using histological data. We analyze the impact of handheld autoinjectors on the injection dynamics for different patient forces. Our simulations show the importance of considering the large deformation approach to model large injection volumes. This work opens opportunities to better understand the mechanics and transport processes that occur in large-volume subcutaneous injections of mAbs.

Material properties of skin in the flying snake Chrysopelea ornata.

In snakes, the skin serves for protection, camouflage, visual signaling, locomotion, and its ability to stretch facilitates large prey ingestion. The flying snakes of the genus Chrysopelea are capable of jumping and gliding through the air, requiring additional functional demands: its skin must accommodate stretch in multiple directions during gliding and, perhaps more importantly, during high-speed, direct-impact landing. Is the skin of flying snakes specialized for gliding? Here, we characterized the material properties of the skin of Chrysopelea ornata and compared them with two nongliding species of colubrid snakes, Thamnophis sirtalis and Pantherophis guttatus, as well as with previously published values. The skin was examined using uniaxial tensile testing to measure stresses, and digital image correlation methods to determine strains, yielding metrics of strength, elastic modulus, strain energy, and extensibility. To test for loading orientation effects, specimens were tested from three orientations relative to the snake's long axis: lateral, circumferential, and ventral. Specimens were taken from two regions of the body, pre- and pos-tpyloric, to test for regional effects related to the ingestion of large prey. In comparison with T. sirtalis and P. guttatus, C. ornata exhibited higher post-pyloric and lower pre-pyloric extensibility in circumferential specimens. However, overall there were few differences in skin material properties of C. ornata compared to other species, both within and across studies, suggesting that the skin of flying snakes is not specialized for gliding locomotion. Surprisingly, circumferential specimens demonstrated lower strength and extensibility in pre-pyloric skin, suggesting less regional specialization related to large prey.

Automated Layer Identification Method for Skin Tissue Histology Images.

We present a novel automated tissue layer identification method for histology images. The method requires a single user input: the number of layers to be identified. The method incorporates a coarse boundary identification step followed by a refinement step. The coarse identification segments the image into 125 × 125 pixel sub-tiles, computes the histogram of each sub-tile, implements K-means clustering to label each sub-tile, and uses Dijkstra's algorithm to form the layer boundary. The refinement step identifies hair follicles, improves the detail and accuracy of the boundary, and segments the epidermis. The method only uses one color channel (blue). We test our proposed method using eight excised porcine tissue samples taken at different anatomical locations. The layer segmentations demonstrated that the dermis thickness increased, and the subcutaneous thickness decreased moving from breast to belly. Minimal variation in the thickness of the epidermis layer across anatomical locations was observed. Overall, these results highlight the importance of quantifying and assessing the tissue environment. Moreover, we demonstrate that our proposed method was robust across different histology stains and did not depend on color-specific information.

Determinants of exercise capacity in patients with heart failure without left ventricular hypertrophy.

BACKGROUND: Determinants of exercise intolerance in a phenotype of heart failure with preserved ejection fraction (HFpEF) with normal left ventricular (LV) structure have not been fully elucidated. METHODS: Cardiopulmonary exercise testing and exercise-stress echocardiography were performed in 44 HFpEF patients without LV hypertrophy. Exercise capacity was determined by peak oxygen consumption (peak VO2). Doppler-derived cardiac output (CO), transmitral E velocity, systolic (LV-s') and early diastolic mitral annular velocities (e'), systolic pulmonary artery (PA) pressure (SPAP), tricuspid annular plane systolic excursion (TAPSE), and peak systolic right ventricular (RV) free wall velocity (RV-s') were measured at rest and exercise. E/e' and TAPSE/SPAP were used as an LV filling pressure parameter and RV-PA coupling, respectively. RESULTS: During exercise, CO, LV-s', RV-s', e', and SPAP were significantly increased (p < 0.05 for all), whereas E/e' remained unchanged and TAPSE/SPAP was significantly reduced (p < 0.001). SPAP was higher and TAPSE/SPAP was lower at peak exercise in patients showing lower-half peak VO2. In univariable analyses, LV-s' (R = 0.35, p = 0.022), SPAP (R = -0.40, p = 0.008), RV-s' (R = 0.47, p = 0.002), and TAPSE/SPAP (R = 0.42, p = 0.005) were significantly correlated with peak VO2. In multivariable analyses, not only SPAP, but also TAPSE/SPAP independently determined peak VO2 even after the adjustment for clinically relevant parameters. CONCLUSIONS: In HFpEF patients without LV hypertrophy, altered RV-PA coupling by exercise could be associated with exercise intolerance, which might not be caused by elevated LV filling pressure.

The air entrainment and hydrodynamic shear of the liquid slosh in syringes.

Understanding the interface motion and hydrodynamic shear induced by the liquid sloshing during the insertion stage of an autoinjector can help improve drug product administration. We perform experiments to investigate the interfacial motion and hydrodynamic shear due to the acceleration and deceleration of syringes. The goal is to explore the role of fluid properties, air gap size, and syringe acceleration on the interface dynamics caused by autoinjector activation. We used a simplified autoinjector platform to record the syringe and liquid motion without any view obstruction. Water and silicone oil with the same viscosity are used as the model fluids. Particle Image Velocimetry (PIV) is employed to measure the velocity field. Simultaneous shadowgraph visualization captures the air entrainment. Our in-house PIV and image processing algorithms are used to quantify the hydrodynamic stress and interfacial area to investigate the effects of various autoinjector design parameters and fluid types on liquid sloshing. The results indicate that reducing the air gap volume and syringe acceleration/deceleration mitigate the interface area and effective shear. Moreover, the interfacial area and induced hydrodynamic stress decrease with the Fr=U/aD, where U is the interface velocity, a is the maximum syringe acceleration, and D is the syringe diameter.

Wall Shear Stress Estimation for 4D Flow MRI Using Navier-Stokes Equation Correction.

This study introduces a novel wall shear stress (WSS) estimation method for 4D flow MRI. The method improves the WSS accuracy by using the reconstructed pressure gradient and the flow-physics constraints to correct velocity gradient estimation. The method was tested on synthetic 4D flow data of analytical Womersley flow and flow in cerebral aneurysms and applied to in vivo 4D flow data acquired in cerebral aneurysms and aortas. The proposed method's performance was compared to the state-of-the-art method based on smooth-spline fitting of velocity profile and the WSS calculated from uncorrected velocity gradient. The proposed method improved the WSS accuracy by as much as 100% for the Womersley flow and reduced the underestimation of mean WSS by 39 to 50% for the synthetic aneurysmal flow. The predicted mean WSS from the in vivo aneurysmal data using the proposed method was 31 to 50% higher than the other methods. The predicted aortic WSS using the proposed method was 3 to 6 times higher than the other methods and was consistent with previous CFD studies and the results from recently developed methods that take into account the limited spatial resolution of 4D flow MRI. The proposed method improves the accuracy of WSS estimation from 4D flow MRI, which can help predict blood vessel remodeling and progression of cardiovascular diseases.

Assessment of Cavitation Intensity in Accelerating Syringes of Spring-Driven Autoinjectors.

PURPOSE: Cavitation is an undesired phenomenon that may occur in certain types of autoinjectors (AIs). Cavitation happens because of rapid changes of pressure in a liquid, leading to the formation of small vapor-filled cavities, which upon collapsing, can generate an intense shock wave that may damage the device container and the protein drug molecules. Cavitation occurs in the AI because of the syringe-drug relative displacement as a result of the syringe's sudden acceleration during needle insertion and the ensuing pressure drop at the bottom of the container. Therefore, it's crucial to analyze the potential effect of cavitation on AI. The goal of the current study is to investigate the effects of syringe and AI design parameters such as air gap size, syringe filling volume, fluid viscosity, and drive spring force (syringe acceleration) on the risk and severity of cavitation. METHODS: A model autoinjector platform is built to record the syringe and cavitation dynamics which we use to estimate the cavitation intensity in terms of extension rate and to study the effects of design parameters on the severity of cavitation. RESULTS: Our results show the generation of an intense shock wave and a high extension rate upon cavitation collapse. The induced extension rate increases with syringe acceleration and filling volume and decreases with viscosity and air gap size. CONCLUSION: The most severe cavitation occurred in an AI device with the larger drive spring force and the syringe of a smaller air gap size filled with a less viscous fluid and a larger filling volume.

A method for direct estimation of left ventricular global longitudinal strain rate from echocardiograms.

We present a new method for measuring global longitudinal strain and global longitudinal strain rate from 2D echocardiograms using a logarithmic-transform correlation (LTC) method. Traditional echocardiography strain analysis depends on user inputs and chamber segmentation, which yield increased measurement variability. In contrast, our approach is automated and does not require cardiac chamber segmentation and regularization, thus eliminating these issues. The algorithm was benchmarked against two conventional strain analysis methods using synthetic left ventricle ultrasound images. Measurement error was assessed as a function of contrast-to-noise ratio (CNR) using mean absolute error and root-mean-square error. LTC showed better agreement to the ground truth strain [Formula: see text] and ground truth strain rate [Formula: see text] compared with agreement to ground truth for two block-matching speckle tracking algorithms (one based on sum of square difference and the other on Fourier transform correlation; strain [Formula: see text], strain rate [Formula: see text]). A 200% increase in strain measurement accuracy was observed compared to the conventional algorithms. Subsequently, we tested the method using a 53-subject clinical cohort (20 subjects diseased with cardiomyopathy, 33 healthy controls). Our method distinguished between normal and abnormal left ventricular function with an AUC = 0.89, a 5% improvement over the conventional GLS algorithms.