1,721,036 research outputs found
Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty
Get PDFComputational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. Copyright © 2016 John Wiley & Sons, Ltd
support in Norwood patients across diverse clinical scenarios with computational modeling
Get PDFBackground: Infants with single-ventricle (SV) physiology undergo the 3-stage Fontan surgery. Norwood patients, who have completed the first stage, face the highest interstage mortality. The Berlin Heart EXCOR (BH), a pediatric pulsatile ventricular assist device, has shown promise in supporting these patients. However, clinical questions regarding device configurations prevent optimal support. Methods: We developed a combined idealized mechanics-lumped parameter model of a Norwood patient and simulated two additional patient-specific cases: pulmonary hypertension (PH) and post-operative treatment with milrinone. We quantified the effects of BH support across different device volumes, rates, and inflow connections on patient hemodynamics and BH performance. Results: Increasing device volume and rate increased cardiac output, but with unsubstantial changes in specific arterial oxygen content. We identified distinct SV-BH interactions that may impact patient myocardial health and contribute to poor clinical outcomes. Our results suggested BH settings for patients with PH and for patients treated post-operatively with milrinone. Conclusions: We present a computational model to characterize and quantify patient hemodynamics and BH support for infants with Norwood physiology. Our results emphasized that oxygen delivery does not increase with BH rate or volume, which may not meet patient needs and contribute to suboptimal clinical outcomes. Our findings demonstrated that an atrial BH may provide optimal cardiac loading for patients with diastolic dysfunction. Meanwhile, a ventricular BH decreased active stress in the myocardium and countered the effects of milrinone. Patients with PH showed greater sensitivity to device volume. In this work, we demonstrate the adaptability of our model to analyze BH support across varied clinical situations
An in-silico analysis of experimental designs to study ventricular function: A focus on the right ventricle
Get PDFIn-vivo studies of pulmonary vascular disease and pulmonary hypertension (PH) have provided key insight into the progression of right ventricular (RV) dysfunction. Additional in-silico experiments using multiscale computational models have provided further details into biventricular mechanics and hemodynamic function in the presence of PH, yet few have assessed whether model parameters are practically identifiable prior to data collection. Moreover, none have used modeling to devise synergistic experimental designs. To address this knowledge gap, we conduct a practical identifiability analysis of a multiscale cardiovascular model across four simulated experimental designs. We determine a set of parameters using a combination of Morris screening and local sensitivity analysis, and test for practical identifiability using profile likelihood-based confidence intervals. We employ Markov chain Monte Carlo (MCMC) techniques to quantify parameter and model forecast uncertainty in the presence of noise corrupted data. Our results show that model calibration to only RV pressure suffers from practical identifiability issues and suffers from large forecast uncertainty in output space. In contrast, parameter and model forecast uncertainty is substantially reduced once additional left ventricular (LV) pressure and volume data is included. A comparison between single point systolic and diastolic LV data and continuous, time-dependent LV pressure-volume data reveals that at least some quantitative data from both ventricles should be included for future experimental studies
Uncertainty quantification in cerebral circulation simulations focusing on the collateral flow: Surrogate model approach with machine learning
Get PDFCollateral circulation in the circle of Willis (CoW), closely associated with disease mechanisms and treatment outcomes, can be effectively investigated using one-dimensional–zero-dimensional hemodynamic simulations. As the entire cardiovascular system is considered in the simulation, it captures the systemic effects of local arterial changes, thus reproducing collateral circulation that reflects biological phenomena. The simulation facilitates rapid assessment of clinically relevant hemodynamic quantities under patient-specific conditions by incorporating clinical data. During patient-specific simulations, the impact of clinical data uncertainty on the simulated quantities should be quantified to obtain reliable results. However, as uncertainty quantification (UQ) is time-consuming and computationally expensive, its implementation in time-sensitive clinical applications is considered impractical. Therefore, we constructed a surrogate model based on machine learning using simulation data. The model accurately predicts the flow rate and pressure in the CoW in a few milliseconds. This reduced computation time enables the UQ execution with 100 000 predictions in a few minutes on a single CPU core and in less than a minute on a GPU. We performed UQ to predict the risk of cerebral hyperperfusion (CH), a life-threatening condition that can occur after carotid artery stenosis surgery if collateral circulation fails to function appropriately. We predicted the statistics of the postoperative flow rate increase in the CoW, which is a measure of CH, considering the uncertainties of arterial diameters, stenosis parameters, and flow rates measured using the patients’ clinical data. A sensitivity analysis was performed to clarify the impact of each uncertain parameter on the flow rate increase. Results indicated that CH occurred when two conditions were satisfied simultaneously: severe stenosis and when arteries of small diameter serve as the collateral pathway to the cerebral artery on the stenosis side. These findings elucidate the biological aspects of cerebral circulation in terms of the relationship between collateral flow and CH
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Assessment of Coronary Artery Aneurysms Cased By Kawasaki Diesease Using Transluminal Attenuation Gradient Analysis of CT Angiograms
Get PDFPatients with coronary artery aneurysms (CAA) resulting from Kawasaki Disease (KD) are at risk for thrombosis and myocardial infarction. Current guidelines recommend using CAA diameter >8 mm as the criterion for initiating systemic anticoagulation, but there is little outcome data to support this choice. Transluminal Attenuation Gradient (TAG) has been proposed as a non-invasive method for evaluating the functional significance of coronary stenoses using CT Angiography (CTA). However TAG has not previously been used to assess CAA. We hypothesized that abnormal flow dynamics in CAA caused by KD could be quantified using TAG. We quantified TAG in the major coronary arteries by performing linear regression of the average lumen intensity as a function of vessel length and compared TAG values for aneurysmal and normal arteries. Aneurysm geometry was characterized using maximum aneurysm diameter, aneurysm shape index and sphericity index. TAG of aneurysmal arteries was significantly lower than in normal arteries. Significant differences were also seen between aneurysmal vs. normal left anterior descending and right coronary. Geometrical parameters showed minimal to no correlation with TAG. This study is the first application of TAG analysis to CAA caused by KD, and demonstrates significantly different TAG values in aneurysmal versus normal arteries. Lack of correlation between TAG and CAA geometry suggests that TAG may provide information on hemodynamic conditions not available from anatomy alone. The use of TAG in KD patients represents a possible extension to standard CTA that could aid in clinical decision-making and help to better evaluate the risk of thrombus formation
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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Towards a Fluid-Structure-Growth and Remodeling Framework to Simulate Vein Graft Failure Post Coronary Artery Bypass Surgery
Get PDFVein graft maladaptation, leading to poor long-term patency, is a serious clinical problem in patients receiving coronary artery bypass grafts (CABGs). Mechanics is known to play a key role as a stimulus contributing towards vein graft failure. Mechanical stimuli are key to understanding disease progression and clinically observed differences in failure rates between arterial and venous grafts following coronary artery bypass graft surgery. But little has been done to quantify the mechanics in these grafts and its effects on long-term outcomes on grafts. Hence, one of the goals of this thesis was to quantify mechanical stimuli acting on the grafts and the other goal was to develop continuum mechanics based models of growth and remodeling (G&R) to simulate long-term adaptation.We quantify biologically relevant mechanical stimuli, not available from standard imaging, in patient-specific simulations incorporating non-invasive clinical data. We couple computational fluid dynamics with closed-loop circulatory physiology models to quantify biologically relevant indices, including wall shear, oscillatory shear, and wall strain. We account for vessel-specific material properties in simulating vessel wall deformation. Wall shear was significantly lower and atheroprone area significantlyhigher in venous compared to arterial grafts. Wall strain in venous grafts was significantly lower than in arterial grafts while no significant difference was observed in oscillatory shear index. Simulations demonstrate significant differences in mechanical stimuli acting on venous vs. arterial grafts, in line with clinically observed graft failure rates, offering a promising avenue for stratifying patients at risk for graft failure.We also propose a computational model of venous adaptation to altered hemodynamics based on a constrained mixture theory of G&R. We identify constitutive parameters that optimally match biaxial data from a mouse vena cava, then numerically subject the vein to altered hemodynamic conditions and quantify the extent of adaptation. We identify constitutive relations and parameters that enable adap-tations for a moderate perturbation in hemodynamics. We then fix these relations and parameters, and subject the vein to a range of combined loads (pressure and flow), from moderate to severe, and identify plausible mechanisms of adaptation versus maladaptation. We also explore the beneficial effects of a gradual increase in load on adaptation
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