Evaluating the accuracy of cerebrovascular computational fluid dynamics modeling through time-resolved experimental validation.

Accurate modeling of cerebral hemodynamics is crucial for better understanding the hemodynamics of stroke, for which computational fluid dynamics (CFD) modeling is a viable tool to obtain information. However, a comprehensive study on the accuracy of cerebrovascular CFD models including both transient arterial pressures and flows does not exist. This study systematically assessed the accuracy of different outlet boundary conditions (BCs) comparing CFD modeling and an in-vitro experiment. The experimental setup consisted of an anatomical cerebrovascular phantom and high-resolution flow and pressure data acquisition. The CFD model of the same cerebrovascular geometry comprised five sets of stationary and transient BCs including established techniques and a novel BC, the phase modulation approach. The experiment produced physiological hemodynamics consistent with reported clinical results for total cerebral blood flow, inlet pressure, flow distribution, and flow pulsatility indices (PI). The in-silico model instead yielded time-dependent deviations between 19-66% for flows and 6-26% for pressures. For cerebrovascular CFD modeling, it is recommended to avoid stationary outlet pressure BCs, which caused the highest deviations. The Windkessel and the phase modulation BCs provided realistic flow PI values and cerebrovascular pressures, respectively. However, this study shows that the accuracy of current cerebrovascular CFD models is limited.

Systematic analysis of non-intrusive polynomial chaos expansion to determine rotary blood pump performance over the entire operating range.

This study applies non-intrusive polynomial chaos expansion (NIPCE) surrogate modeling to analyze the performance of a rotary blood pump (RBP) across its operating range. We systematically investigate key parameters, including polynomial order, training data points, and data smoothness, while comparing them to test data. Using a polynomial order of 4 and a minimum of 20 training points, we successfully train a NIPCE model that accurately predicts pressure head and axial force within the specified operating point range ([0-5000] rpm and [0-7] l/min). We also assess the NIPCE model's ability to predict two-dimensional velocity data across the given range and find good overall agreement (mean absolute error = 0.1 m/s) with a test simulation under the same operating condition. Our approach extends current NIPCE modeling of RBPs by considering the entire operating range and providing validation guidelines. While acknowledging computational benefits, we emphasize the challenge of modeling discontinuous data and its relevance to clinically realistic operating points. We offer open access to our raw data and Python code, promoting reproducibility and accessibility within the scientific community. In conclusion, this study advances comprehensive NIPCE modeling of RBP performance and underlines how critically NIPCE parameters and rigorous validation affect results.

Effect of TAVR commissural alignment on coronary flow: A fluid-structure interaction analysis.

BACKGROUND AND OBJECTIVES: Coronary obstruction is a complication that may affect patients receiving Transcatheter Aortic Valve Replacement (TAVR), with catastrophic consequences and long-term negative effects. To enable healthy coronary perfusion, it is fundamental to appropriately position the device with respect to the coronary ostia. Nonetheless, most TAVR delivery systems do not control commissural alignment to do so. Moreover, no in silico study has directly assessed the effect of commissural alignment on coronary perfusion. This work aims to evaluate the effect of TAVR commissural alignment on coronary perfusion and device performance. METHODS: A two-way computational fluid-structure interaction model is used to predict coronary perfusion at different commissural alignments. Moreover, in each scenario, hemodynamic biomarkers are evaluated to assess device performance. RESULTS: Commissural misalignment is shown to reduce the total coronary perfusion by -3.2% and the flow rate to a single coronary branch by -6.8%. It is also observed to impair valvular function by reducing the systolic geometric orifice area by -2.5% and increasing the systolic transvalvular pressure gradients by +5.3% and the diastolic leaflet stresses by +16.0%. CONCLUSIONS: The present TAVR patient model indicates that coronary perfusion, hemodynamic and structural performance are minimized when the prosthesis commissures are fully misaligned with the native ones. These results support the importance of enabling axial control in new TAVR delivery catheter systems and defining recommended values of commissural alignment in upcoming clinical treatment guidelines.

Computational modeling of hemodynamics and risk of thrombosis in the left atrial appendage using patient-specific blood viscosity and boundary conditions at the mitral valve.

Hemodynamics play a vital role for the risk of thrombosis in the left atrial appendage (LAA) and left atrium (LA) for patients with atrial fibrillation. Accurate prediction of hemodynamics in the LA can provide important guidance for assessing the risk of thrombosis in the LAA. Patient specificity is a crucial factor in representing the true hemodynamic fields. In this study, we investigated the effects of blood rheology (as a function of hematocrit and shear rate), as well as patient-specific mitral valve (MV) boundary conditions (MV area and velocity profiles measured by ultrasound) on the hemodynamics and thrombosis potential of the LAA. Four scenarios were setup with different degrees of patient specificity. Though using a constant blood viscosity can classify the thrombus and non-thrombus patients for all the hemodynamic indicators, the risk of thrombosis was underestimated for all patients compared with patient-specific viscosities. The results with least patient specificities showed that patients prone to thrombosis predicted by three hemodynamic indicators were inconsistent with clinical observations. Moreover, though patients had the same MV inlet flow rate, different MV models lead to different trends in the risk of thrombosis in different patients. We also found that endothelial cell activation potential and relative residence time can effectively distinguish thrombus and non-thrombus patients for all the scenarios, relatively insensitive to patient specificities. Overall, the findings of this study provide useful insights on patients-specific hemodynamic simulations of the LA.

Inflow from a Cardiopulmonary Assist System to the Pulmonary Artery and Its Implications for Local Hemodynamics-a Computational Fluid Dynamics Study.

When returning blood to the pulmonary artery (PA), the inflow jet interferes with local hemodynamics. We investigated the consequences for several connection scenarios using transient computational fluid dynamics simulations. The PA was derived from CT data. Three aspects were varied: graft flow rate, anastomosis location, and inflow jet path length from anastomosis site to impingement on the PA wall. Lateral anastomosis locations caused abnormal flow distribution between the left and right PA. The central location provided near-physiological distribution but induced higher wall shear stress (WSS). All effects were most pronounced at high graft flows. A central location is beneficial regarding flow distribution, but the resulting high WSS might promote detachment of local thromboembolisms or influence the autonomic nervous innervation. Lateral locations, depending on jet path length, result in lower WSS at the cost of an unfavorable flow distribution that could promote pulmonary vasculature changes. Case-specific decisions and further research are necessary.

Generic framework for quantifying the influence of the mitral valve on ventricular blood flow.

Blood flow within the left ventricle provides important information regarding cardiac function in health and disease. The mitral valve strongly influences the formation of flow structures and there exist various approaches for the representation of the valve in numerical models of left ventricular blood flow. However, a systematic comparison of the various mitral valve models is missing, making a priori decisions considering the overall model's context of use impossible. Within this study, a benchmark setup to compare the influence of mitral valve modeling strategies on intraventricular flow features was developed. Then, five mitral valve models of increasing complexity: no modeling, static wall, 2D and 3D porous medium with time-dependent porosity, and one-way fluid-structure interaction (FSI) were compared with each other. The flow features velocity, kinetic energy, transmitral pressure drop, vortex formation, flow asymmetry as well as computational cost and ease-of-implementation were evaluated. The one-way FSI approach provides the highest level of flow detail, which is accompanied by the highest numerical costs and challenges with the implementation. As an alternative, the porous medium approach with the expansion including time-dependent porosity provides good results with up to 10% deviations in the flow features (except the transmitral pressure drop) in comparison to the FSI model and only a fraction (11%) of numerical costs. However, jet propagation speed is highly underestimated by all alternative approaches to the FSI model. Taken together, our benchmark setup allows a quantitative comparison of various mitral valve modeling approaches and is provided to the scientific community for further testing and expansion.

Flow control in the middle cerebral artery during thrombectomy: the effect of anatomy, catheter size and tip location.

BACKGROUND: Catheter size, location and circle of Willis anatomy impact the flow conditions during interventional stroke therapy. The aim of the study was to systematically investigate the influence of these factors on flow control in the middle cerebral artery by means of a computational model based on 100 patients with stroke who received endovascular treatment. METHODS: The dimensions of the cervical and intracranial cerebral arteries of 100 patients who received endovascular mechanical thrombectomy for acute ischemic stroke were measured and a three-dimensional model of the circle of Willis was created based on these data. Flow control in the middle cerebral artery with variations in catheter size, catheter location and configurations of collateral vessels was determined using a computational model. A total of 48 scenarios were analyzed. RESULTS: Flow reversal with a distal aspiration catheter alone was not possible in the internal carotid artery and only sometimes possible in the middle cerebral artery (14 of 48 cases). The Catalyst 7 catheter was more often successful in achieving flow reversal than Catalyst 5 or 6 catheters (p<0.001). In a full circle of Willis anatomy, flow reversal was almost never possible. The absence of one or more communicating arteries significantly influenced flow direction compared with the full anatomy with all communicating arteries present (p=0.028). CONCLUSION: Choosing the biggest possible aspiration catheter and locating it in the middle cerebral artery significantly increases the chances of successful flow control. Flow through the collaterals may impair the flow, and circle of Willis anatomy should be considered during aspiration thrombectomy.

Trends, Advantages and Disadvantages in Combined Extracorporeal Lung and Kidney Support From a Technical Point of View.

Extracorporeal membrane oxygenation (ECMO) provides pulmonary and/or cardiac support for critically ill patients. Due to their diseases, they are at high risk of developing acute kidney injury. In that case, continuous renal replacement therapy (CRRT) is applied to provide renal support and fluid management. The ECMO and CRRT circuits can be combined by an integrated or parallel approach. So far, all methods used for combined extracorporeal lung and kidney support present serious drawbacks. This includes not only high risks of circuit related complications such as bleeding, thrombus formation, and hemolysis, but also increase in technical workload and health care costs. In this sense, the development of a novel optimized artificial lung device with integrated renal support could offer important treatment benefits. Therefore, we conducted a review to provide technical background on existing techniques for extracorporeal lung and kidney support and give insight on important aspects to be addressed in the development of this novel highly integrated artificial lung device.

Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments.

In osteoarthritis (OA), chondrocyte metabolism dysregulation increases relative catabolic activity, which leads to cartilage degradation. To enable the semiquantitative interpretation of the intricate mechanisms of OA progression, we propose a network-based model at the chondrocyte level that incorporates the complex ways in which inflammatory factors affect structural protein and protease expression and nociceptive signals. Understanding such interactions will leverage the identification of new potential therapeutic targets that could improve current pharmacological treatments. Our computational model arises from a combination of knowledge-based and data-driven approaches that includes in-depth analyses of evidence reported in the specialized literature and targeted network enrichment. We achieved a mechanistic network of molecular interactions that represent both biosynthetic, inflammatory and degradative chondrocyte activity. The network is calibrated against experimental data through a genetic algorithm, and 81% of the responses tested have a normalized root squared error lower than 0.15. The model captures chondrocyte-reported behaviors with 95% accuracy, and it correctly predicts the main outcomes of OA treatment based on blood-derived biologics. The proposed methodology allows us to model an optimal regulatory network that controls chondrocyte metabolism based on measurable soluble molecules. Further research should target the incorporation of mechanical signals.

An Accelerated Thrombosis Model for Computational Fluid Dynamics Simulations in Rotary Blood Pumps.

PURPOSE: Thrombosis ranks among the major complications in blood-carrying medical devices and a better understanding to influence the design related contribution to thrombosis is desirable. Over the past years many computational models of thrombosis have been developed. However, numerically cheap models able to predict localized thrombus risk in complex geometries are still lacking. The aim of the study was to develop and test a computationally efficient model for thrombus risk prediction in rotary blood pumps. METHODS: We used a two-stage approach to calculate thrombus risk. The first stage involves the computation of velocity and pressure fields by computational fluid dynamic simulations. At the second stage, platelet activation by mechanical and chemical stimuli was determined through species transport with an Eulerian approach. The model was compared with existing clinical data on thrombus deposition within the HeartMate II. Furthermore, an operating point and model parameter sensitivity analysis was performed. RESULTS: Our model shows good correlation (R2 > 0.93) with clinical data and identifies the bearing and outlet stator region of the HeartMate II as the location most prone to thrombus formation. The calculation of thrombus risk requires an additional 10-20 core hours of computation time. CONCLUSION: The concentration of activated platelets can be used as a surrogate and computationally low-cost marker to determine potential risk regions of thrombus deposition in a blood pump. Relative comparisons of thrombus risk are possible even considering the intrinsic uncertainty in model parameters and operating conditions.

Intraventricular Flow Simulations in Singular Right Ventricles Reveal Deteriorated Washout and Low Vortex Formation.

PURPOSE: Patients with a functionally univentricular heart represent one of the most common severe cardiac lesions with a prevalence of 3 per 10,000 live births. Hemodynamics of the singular ventricle is a major research topic in cardiology and there exists a relationship between fluid dynamical features and cardiac behavior in health and disease. The aim of the present work was to compare intraventricular flow in single right ventricle (SRV) patients and subjects with healthy left hearts (LV) through patient-specific CFD simulations. METHODS: Three-dimensional real-time echocardiographic images were obtained for five SRV patients and two healthy subjects and CFD simulations with a moving mesh methodology were performed. Intraventricular vortex formation and vortex formation time (VFT) as well as the turbulent kinetic energy (TKE) and ventricular washout were evaluated. RESULTS: The results show significantly lower values for the VFT and the TKE in SRV patients compared with healthy LV subjects. Furthermore, vortex formation does not progress to the apex in SRV patients. These findings were confirmed by a significantly lower washout in SRV patients. CONCLUSIONS: The study pinpoints the intriguing role of intraventricular flows to characterize performance of SRVs that goes beyond standard clinical metrics such as ejection fraction.

Possible Contexts of Use for In Silico Trials Methodologies: A Consensus-Based Review.

The term "In Silico Trial" indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diagnostic product or an advanced therapy medicinal product. Predictive models are positioned as new methodologies for the development and the regulatory evaluation of medical products. New methodologies are qualified by regulators such as FDA and EMA through formal processes, where a first step is the definition of the Context of Use (CoU), which is a concise description of how the new methodology is intended to be used in the development and regulatory assessment process. As In Silico Trials are a disruptively innovative class of new methodologies, it is important to have a list of possible CoUs highlighting potential applications for the development of the relative regulatory science. This review paper presents the result of a consensus process that took place in the InSilicoWorld Community of Practice, an online forum for experts in in silico medicine. The experts involved identified 46 descriptions of possible CoUs which were organised into a candidate taxonomy of nine CoU categories. Examples of 31 CoUs were identified in the available literature; the remaining 15 should, for now, be considered speculative.

Understanding the influence of left ventricular assist device inflow cannula alignment and the risk of intraventricular thrombosis.

BACKGROUND: Adverse neurological events associated with left ventricular assist devices (LVADs) have been suspected to be related to thrombosis. This study aimed to understand the risks of thrombosis with variations in the implanted device orientation. A severely dilated pulsatile patient-specific left ventricle, modelled with computational fluid dynamics, was utilised to identify the risk of thrombosis for five cannulation angles. With respect to the inflow cannula axis directed towards the mitral valve, the other angles were 25° and 20° towards the septum and 20° and 30° towards the free wall. RESULTS: Inflow cannula angulation towards the free wall resulted in longer blood residence time within the ventricle, slower ventricular washout and reduced pulsatility indices along the septal wall. Based on the model, the ideal inflow cannula alignment to reduce the risk of thrombosis was angulation towards the mitral valve and up to parallel to the septum, avoiding the premature clearance of incoming blood. CONCLUSIONS: This study indicates the potential effects of inflow cannulation angles and may guide optimised implantation configurations; however, the ideal approach will be influenced by other patient factors and is suspected to change over the course of support.

Tipless transseptal cannula concept combines improved hemodynamic properties and risk-reduced placement: An in silico proof-of-concept.

As a leading cause of death worldwide, heart failure is a serious medical condition in which many critically ill patients require temporary mechanical circulatory support (MCS) as a bridge-to-recovery or bridge-to-decision. In many cases, the TandemHeart system is used to unload the left heart by draining blood from the left atrium (LA) to the femoral artery via a transseptal multistage cannula. However, even though the correct positioning of the cannula is crucial for a safe treatment, the long cannula tip currently used in transseptal cannulas complicates positioning, making the cannula vulnerable to displacement during MCS. To overcome these limitations, we propose the development of a new tipless transseptal cannula with improved hemodynamic properties. We discuss the tipless cannula concept by comparing it to the common multistage cannula concept using computational fluid dynamics simulations and assess the flow field in the LA, the wall shear stresses (WSS), and the pressure loss. Across the two distinct time points of end-systole and end-diastole and two drainage flow rates of 3.5 and 5.0 L/min, we find a more homogeneous inlet flow pattern for the tipless cannula concept, accompanied by a remarkably reduced area of platelet-activating WSS (up to 10-times smaller area compared to the multistage cannula). Moreover, pressure loss is up to 14.5% lower in the tipless cannula concept, confirming overall improved hemodynamic properties of the tipless cannula concept. Finally, a diameter-dependent study reveals that lower WSS and pressure losses can be further reduced by large-lumen designs for any simulation setting. Overall, our results suggest that a tipless cannula concept remedies the crucial disadvantages of a long-tip multistage cannula by reducing the risk of misplacement, and it furthermore promotes optimized hemodynamics. With this successful proof-of-concept, we underscore the potential for and encourage the realization of further experimental investigations regarding the development of a tipless transseptal cannula for MCS.

Multiscale Regulation of the Intervertebral Disc: Achievements in Experimental, In Silico, and Regenerative Research.

Intervertebral disc (IVD) degeneration is a major risk factor of low back pain. It is defined by a progressive loss of the IVD structure and functionality, leading to severe impairments with restricted treatment options due to the highly demanding mechanical exposure of the IVD. Degenerative changes in the IVD usually increase with age but at an accelerated rate in some individuals. To understand the initiation and progression of this disease, it is crucial to identify key top-down and bottom-up regulations' processes, across the cell, tissue, and organ levels, in health and disease. Owing to unremitting investigation of experimental research, the comprehension of detailed cell signaling pathways and their effect on matrix turnover significantly rose. Likewise, in silico research substantially contributed to a holistic understanding of spatiotemporal effects and complex, multifactorial interactions within the IVD. Together with important achievements in the research of biomaterials, manifold promising approaches for regenerative treatment options were presented over the last years. This review provides an integrative analysis of the current knowledge about (1) the multiscale function and regulation of the IVD in health and disease, (2) the possible regenerative strategies, and (3) the in silico models that shall eventually support the development of advanced therapies.

Estimation of left ventricular stroke work based on a large cohort of healthy children.

Left ventricular stroke work is an important prognostic marker to analyze cardiac function. Standard values for children are, however, missing. For clinicians, standards can help to improve the treatment decision of heart failures. For engineers, they can help to optimize medical devices. In this study, we estimated the left ventricular stroke work for children based on modeled pressure-volume loops. A lumped parameter model was fitted to clinical data of 340 healthy children. Reference curves for standard values were created over age, weight, and height. Left ventricular volume was measured with 3D echocardiography, while maximal ventricular pressure was approximated with a regression model from the literature. For validation of this method, we used 18 measurements acquired by a conductance catheter in 11 patients. The method demonstrated a low absolute mean difference of 0.033 J (SD: 0.031 J) for stroke work between measurement and estimation, while the percentage error was 21.66 %. According to the resulting reference curves, left ventricular stroke work of newborns has a median of 0.06 J and increases to 1.15 J at the age of 18 years. Stroke work increases over weight and height in a similar trend. The percentile curves depict the distribution. We demonstrate how reference curves can be used for quantification of differences and comparison in patients.

A Novel Multiplex Based Platform for Osteoarthritis Drug Candidate Evaluation.

Osteoarthritis (OA) is characterized by irreversible cartilage degradation with very limited therapeutic interventions. Drug candidates targeted at prototypic players had limited success until now and systems based approaches might be necessary. Consequently, drug evaluation platforms should consider the biological complexity looking beyond well-known contributors of OA. In this study an ex vivo model of cartilage degradation, combined with measuring releases of 27 proteins, was utilized to study 9 drug candidates. After an initial single drug evaluation step the 3 most promising compounds were selected and employed in an exhaustive combinatorial experiment. The resulting most and least promising treatment candidates were selected and validated in an independent study. This included estimation of mechanical properties via finite element modelling (FEM) and quantification of cartilage degradation as glycosaminoglycan (GAG) release. The most promising candidate showed increase of Young's modulus, decrease of hydraulic permeability and decrease of GAG release. The least promising candidate exhibited the opposite behaviour. The study shows the potential of a novel drug evaluation platform in identifying treatments that might reduce cartilage degradation. It also demonstrates the promise of exhaustive combination experiments and a connection between chondrocyte responses at the molecular level with changes of biomechanical properties at the tissue level.

COMBSecretomics: A pragmatic methodological framework for higher-order drug combination analysis using secretomics.

Multi drug treatments are increasingly used in the clinic to combat complex and co-occurring diseases. However, most drug combination discovery efforts today are mainly focused on anticancer therapy and rarely examine the potential of using more than two drugs simultaneously. Moreover, there is currently no reported methodology for performing second- and higher-order drug combination analysis of secretomic patterns, meaning protein concentration profiles released by the cells. Here, we introduce COMBSecretomics (https://github.com/EffieChantzi/COMBSecretomics.git), the first pragmatic methodological framework designed to search exhaustively for second- and higher-order mixtures of candidate treatments that can modify, or even reverse malfunctioning secretomic patterns of human cells. This framework comes with two novel model-free combination analysis methods; a tailor-made generalization of the highest single agent principle and a data mining approach based on top-down hierarchical clustering. Quality control procedures to eliminate outliers and non-parametric statistics to quantify uncertainty in the results obtained are also included. COMBSecretomics is based on a standardized reproducible format and could be employed with any experimental platform that provides the required protein release data. Its practical use and functionality are demonstrated by means of a proof-of-principle pharmacological study related to cartilage degradation. COMBSecretomics is the first methodological framework reported to enable secretome-related second- and higher-order drug combination analysis. It could be used in drug discovery and development projects, clinical practice, as well as basic biological understanding of the largely unexplored changes in cell-cell communication that occurs due to disease and/or associated pharmacological treatment conditions.

Multi-tissue network analysis for drug prioritization in knee osteoarthritis.

Knee osteoarthritis (OA) is a joint disease that affects several tissues: cartilage, synovium, meniscus and subchondral bone. The pathophysiology of this complex disease is still not completely understood and existing pharmaceutical strategies are limited to pain relief treatments. Therefore, a computational method was developed considering the diverse mechanisms and the multi-tissue nature of OA in order to suggest pharmaceutical compounds. Specifically, weighted gene co-expression network analysis (WGCNA) was utilized to identify gene modules that were preserved across four joint tissues. The driver genes of these modules were selected as an input for a network-based drug discovery approach. WGCNA identified two preserved modules that described functions related to extracellular matrix physiology and immune system responses. Compounds that affected various anti-inflammatory pathways and drugs targeted at coagulation pathways were suggested. 9 out of the top 10 compounds had a proven association with OA and significantly outperformed randomized approaches not including WGCNA. The method presented herein is a viable strategy to identify overlapping molecular mechanisms in multi-tissue diseases such as OA and employ this information for drug discovery and compound prioritization.

An ex vivo tissue model of cartilage degradation suggests that cartilage state can be determined from secreted key protein patterns.

The pathophysiology of osteoarthritis (OA) involves dysregulation of anabolic and catabolic processes associated with a broad panel of proteins that ultimately lead to cartilage degradation. An increased understanding about these protein interactions with systematic in vitro analyses may give new ideas regarding candidates for treatment of OA related cartilage degradation. Therefore, an ex vivo tissue model of cartilage degradation was established by culturing tissue explants with bacterial collagenase II. Responses of healthy and degrading cartilage were analyzed through protein abundance in tissue supernatant with a 26-multiplex protein profiling assay, after exposing the samples to a panel of 55 protein stimulations present in synovial joints of OA patients. Multivariate data analysis including exhaustive pairwise variable subset selection identified the most outstanding changes in measured protein secretions. MMP9 response to stimulation was outstandingly low in degrading cartilage and there were several protein pairs like IFNG and MMP9 that can be used for successful discrimination between degrading and healthy samples. The discovered changes in protein responses seem promising for accurate detection of degrading cartilage. The ex vivo model seems interesting for drug discovery projects related to cartilage degradation, for example when trying to uncover the unknown interactions between secreted proteins in healthy and degrading tissues.