scholarly journals Prior Distributions of Material Parameters for Bayesian Calibration of Growth and Remodeling Computational Model of Abdominal Aortic Wall

2015 ◽  
Vol 137 (10) ◽  
Author(s):  
Sajjad Seyedsalehi ◽  
Liangliang Zhang ◽  
Jongeun Choi ◽  
Seungik Baek
Keyword(s):  
Computational Model ◽  
Prior Distribution ◽  
Specific Model ◽  
Patient Specific ◽  
Model Parameters ◽  
Bayesian Calibration ◽  
Prior Distributions ◽  
Group I ◽  
Biaxial Tests ◽  
Group Ii

For the accurate prediction of the vascular disease progression, there is a crucial need for developing a systematic tool aimed toward patient-specific modeling. Considering the interpatient variations, a prior distribution of model parameters has a strong influence on computational results for arterial mechanics. One crucial step toward patient-specific computational modeling is to identify parameters of prior distributions that reflect existing knowledge. In this paper, we present a new systematic method to estimate the prior distribution for the parameters of a constrained mixture model using previous biaxial tests of healthy abdominal aortas (AAs). We investigate the correlation between the estimated parameters for each constituent and the patient's age and gender; however, the results indicate that the parameters are correlated with age only. The parameters are classified into two groups: Group-I in which the parameters ce, ck1, ck2, cm2,Ghc, and ϕe are correlated with age, and Group-II in which the parameters cm1, Ghm, G1e, G2e, and α are not correlated with age. For the parameters in Group-I, we used regression associated with age via linear or inverse relations, in which their prior distributions provide conditional distributions with confidence intervals. For Group-II, the parameter estimated values were subjected to multiple transformations and chosen if the transformed data had a better fit to the normal distribution than the original. This information improves the prior distribution of a subject-specific model by specifying parameters that are correlated with age and their transformed distributions. Therefore, this study is a necessary first step in our group's approach toward a Bayesian calibration of an aortic model. The results from this study will be used as the prior information necessary for the initialization of Bayesian calibration of a computational model for future applications.

scholarly journals A personalized computational model of edema formation in myocarditis based on long-axis biventricular MRI images

2019 ◽  
Vol 20 (S6) ◽  
Author(s):  
Ruy Freitas Reis ◽  
Juliano Lara Fernandes ◽  
Thaiz Ruberti Schmal ◽  
Bernardo Martins Rocha ◽  
Rodrigo Weber dos Santos ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Immune Response ◽  
Computational Model ◽  
Cardiac Tissue ◽  
Geometrical Model ◽  
Specific Model ◽  
Patient Specific ◽  
Edema Formation ◽  
Promising Tool ◽  
Inflammatory Edema

Abstract Background Myocarditis is defined as the inflammation of the myocardium, i.e. the cardiac muscle. Among the reasons that lead to this disease, we may include infections caused by a virus, bacteria, protozoa, fungus, and others. One of the signs of the inflammation is the formation of edema, which may be a consequence of the interaction between interstitial fluid dynamics and immune response. This complex physiological process was mathematically modeled using a nonlinear system of partial differential equations (PDE) based on porous media approach. By combing a model based on Biot’s poroelasticity theory with a model for the immune response we developed a new hydro-mechanical model for inflammatory edema. To verify this new computational model, T2 parametric mapping obtained by Magnetic Resonance (MR) imaging was used to identify the region of edema in a patient diagnosed with unspecific myocarditis. Results A patient-specific geometrical model was created using MRI images from the patient with myocarditis. With this model, edema formation was simulated using the proposed hydro-mechanical mathematical model in a two-dimensional domain. The computer simulations allowed us to correlate spatiotemporal dynamics of representative cells of the immune systems, such as leucocytes and the pathogen, with fluid accumulation and cardiac tissue deformation. Conclusions This study demonstrates that the proposed mathematical model is a very promising tool to better understand edema formation in myocarditis. Simulations obtained from a patient-specific model reproduced important aspects related to the formation of cardiac edema, its area, position, and shape, and how these features are related to immune response.

scholarly journals Inverse problems in reduced order models of cardiovascular haemodynamics: aspects of data assimilation and heart rate variability

2017 ◽  
Vol 14 (126) ◽  
pp. 20160513 ◽  
Author(s):  
Sanjay Pant ◽  
Chiara Corsini ◽  
Catriona Baker ◽  
Tain-Yen Hsia ◽  
Giancarlo Pennati ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Inverse Problems ◽  
Unscented Kalman Filter ◽  
Clinical Situation ◽  
Specific Model ◽  
Patient Specific ◽  
Model Parameters ◽  
Heart Rates ◽  
Model Predictions ◽  
Patient State

Inverse problems in cardiovascular modelling have become increasingly important to assess each patient individually. These problems entail estimation of patient-specific model parameters from uncertain measurements acquired in the clinic. In recent years, the method of data assimilation, especially the unscented Kalman filter, has gained popularity to address computational efficiency and uncertainty consideration in such problems. This work highlights and presents solutions to several challenges of this method pertinent to models of cardiovascular haemodynamics. These include methods to (i) avoid ill-conditioning of the covariance matrix, (ii) handle a variety of measurement types, (iii) include a variety of prior knowledge in the method, and (iv) incorporate measurements acquired at different heart rates, a common situation in the clinic where the patient state differs according to the clinical situation. Results are presented for two patient-specific cases of congenital heart disease. To illustrate and validate data assimilation with measurements at different heart rates, the results are presented on a synthetic dataset and on a patient-specific case with heart valve regurgitation. It is shown that the new method significantly improves the agreement between model predictions and measurements. The developed methods can be readily applied to other pathophysiologies and extended to dynamical systems which exhibit different responses under different sets of known parameters or different sets of inputs (such as forcing/excitation frequencies).

scholarly journals A Bayesian approach for the identification of patient-specific parameters in a dialysis kinetic model

2018 ◽  
Vol 28 (7) ◽  
pp. 2069-2095
Author(s):  
Camilla Bianchi ◽  
Ettore Lanzarone ◽  
Giustina Casagrande ◽  
Maria Laura Costantino
Keyword(s):  
Bayesian Approach ◽  
Likelihood Function ◽  
Compartment Model ◽  
Specific Model ◽  
Patient Specific ◽  
Model Parameters ◽  
Uremic Patient ◽  
Blood Electrolytes ◽  
Runge Kutta Method ◽  
Dialysis Complications

Hemodialysis is the most common therapy to treat renal insufficiency. However, notwithstanding the recent improvements, hemodialysis is still associated with a non-negligible rate of comorbidities, which could be reduced by customizing the treatment. Many differential compartment models have been developed to describe the mass balance of blood electrolytes and catabolites during hemodialysis, with the goal of improving and controlling hemodialysis sessions. However, these models often refer to an average uremic patient, while on the contrary the clinical need for customization requires patient-specific models. In this work, we assume that the customization can be obtained by means of patient-specific model parameters. We propose and validate a Bayesian approach to estimate the patient-specific parameters of a multi-compartment model, and to predict the single patient’s response to the treatment, in order to prevent intra-dialysis complications. The likelihood function is obtained by means of a discretized version of the multi-compartment model, where the discretization is in terms of a Runge–Kutta method to guarantee convergence, and the posterior densities of model parameters are obtained through Markov Chain Monte Carlo simulation. Results show fair estimations and the applicability in the clinical practice.

A Sequential Calibration and Validation Framework for Model Parameter Updating and Bias Correction

2020 ◽  
Author(s):  
Chen Jiang ◽  
Yixuan Liu ◽  
Zhen Hu ◽  
Zissimos P. Mourelatos ◽  
David Gorsich ◽  
...  
Keyword(s):  
Model Validation ◽  
Bias Correction ◽  
Model Parameters ◽  
Model Bias ◽  
Bayesian Calibration ◽  
Prior Distributions ◽  
Model Parameter ◽  
Calibration And Validation ◽  
Validation Framework ◽  
Uncertain Model

Abstract Model parameter updating and bias correction plays an essential role in improving the validity of Modeling and Simulation (M&S) in engineering design and analysis. However, it is observed that the existing methods may either be misled by potentially wrong information if the computer model cannot adequately capture the underlying true physics, or be affected by the prior distributions of the unknown model parameters. In this paper, a sequential model calibration and validation (SeCAV) framework is proposed to improve the efficacy of both model parameter updating and model bias correction, where the model validation and Bayesian calibration are implemented in a sequential manner. In each iteration, the model validation assessment is employed as a filter to select the best experimental data for Bayesian calibration, and to update the prior distributions of uncertain model parameters for the next iteration. The calibrated parameters are then integrated with model bias correction to improve the prediction accuracy of the M&S. A mathematical example is employed to demonstrate the advantages of the SeCAV method.

Software Application Profile: Bayesian estimation of inverse variance weighted and MR-Egger models for two-sample Mendelian randomization studies—mrbayes

2020 ◽  
Author(s):  
Okezie Uche-Ikonne ◽  
Frank Dondelinger ◽  
Tom Palmer
Keyword(s):  
Bayesian Estimation ◽  
Prior Distribution ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Model Parameters ◽  
Software Environment ◽  
Prior Distributions ◽  
Software Application ◽  
Level Data ◽  
Inverse Variance

Abstract Motivation We present our package, mrbayes, for the open source software environment R. The package implements Bayesian estimation for inverse variance weighted (IVW) and MR-Egger models, including the radial MR-Egger model, for summary-level data in Mendelian randomization (MR) analyses. Implementation We have implemented a choice of prior distributions for the model parameters, namely; weakly informative, non-informative, a joint prior for the MR-Egger model slope and intercept, and an informative prior (pseudo-horseshoe prior), or the user can specify their own prior distribution. General features Users have the option of fitting the models using either JAGS or Stan software packages with similar prior distributions; the option for the user-defined prior distribution is only in our JAGS functions. We show how to use the package through an applied example investigating the causal effect of body mass index (BMI) on acute ischaemic stroke. Availability The package is freely available, under the GNU General Public License v3.0, on GitHub [https://github.com/okezie94/mrbayes] or CRAN [https://CRAN.R-project.org/package=mrbayes].

scholarly journals Coupled personalization of cardiac electrophysiology models for prediction of ischaemic ventricular tachycardia

2011 ◽  
Vol 1 (3) ◽  
pp. 396-407 ◽  
Author(s):  
Jatin Relan ◽  
Phani Chinchapatnam ◽  
Maxime Sermesant ◽  
Kawal Rhode ◽  
Matt Ginks ◽  
...  
Keyword(s):  
Ventricular Tachycardia ◽  
Cardiac Electrophysiology ◽  
Specific Model ◽  
Biophysical Model ◽  
Patient Specific ◽  
Model Parameters ◽  
Tissue Conductivity ◽  
Mapping Procedure ◽  
Macroscopic Models ◽  
Contact Mapping

In order to translate the important progress in cardiac electrophysiology modelling of the last decades into clinical applications, there is a requirement to make macroscopic models that can be used for the planning and performance of the clinical procedures. This requires model personalization, i.e. estimation of patient-specific model parameters and computations compatible with clinical constraints. Simplified macroscopic models can allow a rapid estimation of the tissue conductivity, but are often unreliable to predict arrhythmias. Conversely, complex biophysical models are more complete and have mechanisms of arrhythmogenesis and arrhythmia sustainibility, but are computationally expensive and their predictions at the organ scale still have to be validated. We present a coupled personalization framework that combines the power of the two kinds of models while keeping the computational complexity tractable. A simple eikonal model is used to estimate the conductivity parameters, which are then used to set the parameters of a biophysical model, the Mitchell–Schaeffer (MS) model. Additional parameters related to action potential duration restitution curves for the tissue are further estimated for the MS model. This framework is applied to a clinical dataset derived from a hybrid X-ray/magnetic resonance imaging and non-contact mapping procedure on a patient with heart failure. This personalized MS model is then used to perform an in silico simulation of a ventricular tachycardia (VT) stimulation protocol to predict the induction of VT. This proof of concept opens up possibilities of using VT induction modelling in order to both assess the risk of VT for a given patient and also to plan a potential subsequent radio-frequency ablation strategy to treat VT.

Ultrastructural Lesions Produced by Alcohol and Sucrose in the Heart and Liver of C57BL Mice

1970 ◽  
Vol 28 ◽  
pp. 208-209
Author(s):  
K.K. SEKHRI ◽  
C.S. ALEXANDER ◽  
H.T. NAGASAWA
Keyword(s):  
Osmium Tetroxide ◽  
Male Mice ◽  
Alcohol Group ◽  
Group Iii ◽  
Group I ◽  
C57bl Mice ◽  
Group Ii

C57BL male mice (Jackson Lab., Bar Harbor, Maine) weighing about 18 gms were randomly divided into three groups: group I was fed sweetened liquid alcohol diet (modified Schenkl) in which 36% of the calories were derived from alcohol; group II was maintained on a similar diet but alcohol was isocalorically substituted by sucrose; group III was fed regular mouse chow ad lib for five months. Liver and heart tissues were fixed in 2.5% cacodylate buffered glutaraldehyde, post-fixed in 2% osmium tetroxide and embedded in Epon-araldite.

Heterogeneity and Immunochemical Properties of Anti-β2-glycoprotein I Autoantibodies

1998 ◽  
Vol 80 (09) ◽  
pp. 393-398 ◽  
Author(s):  
V. Regnault ◽  
E. Hachulla ◽  
L. Darnige ◽  
B. Roussel ◽  
J. C. Bensa ◽  
...  
Keyword(s):  
Fluid Phase ◽  
Anticardiolipin Antibodies ◽  
Dual Reactivity ◽  
Group Iii ◽  
Important Group ◽  
Epitope Specificity ◽  
Glycoprotein I ◽  
Group I ◽  
Group Ii ◽  
Sufficient Concentration

SummaryMost anticardiolipin antibodies (ACA) associated with antiphospholipid syndrome (APS) are directed against epitopes expressed on β2-glycoprotein I (β2GPI). Despite a good correlation between standard ACA assays and those using purified human β2GPI as the sole antigen, some sera from APS patients only react in the latter. This is indicative of heterogeneity in anti-β2GPI antibodies. To characterize their reactivity profiles, human and bovine β2GPI were immobilized on γ-irradiated plates (β2GPI-ELISA), plain polystyrene precoated with increasing cardiolipin concentrations (CL/β2GPI-ELISA), and affinity columns. Fluid-phase inhibition experiments were also carried out with both proteins. Of 56 selected sera, restricted recognition of bovine or human β2GPI occurred respectively in 10/29 IgA-positive and 9/22 IgM-positive samples, and most of the latter (8/9) were missed by the standard ACA assay, as expected from a previous study. Based on species specificity and ACA results, IgG-positive samples (53/56) were categorized into three groups: antibodies reactive to bovine β2GPI only (group I) or to bovine and human β2GPI, group II being ACA-negative, and group III being ACA-positive. The most important group, group III (n = 33) was characterized by (i) binding when β2GPI was immobilized on γ-irradiated polystyrene or cardiolipin at sufficient concentration (regardless of β2GPI density, as assessed using 125I-β2GPI); (ii) and low avidity binding to fluid-phase β2GPI (Kd in the range 10–5 M). In contrast, all six group II samples showed (i) ability to bind human and bovine β2GPI immobilized on non-irradiated plates; (ii) concentration-dependent blockade of binding by cardiolipin, suggesting epitope location in the vicinity of the phospholipid binding site on native β2GPI; (iii) and relative avidities approximately 100-fold higher than in group III. Group I patients were heterogeneous with respect to CL/β2GPI-ELISA and ACA results (6/14 scored negative), possibly reflecting antibody differences in terms of avidity and epitope specificity. Affinity fractionation of 23 sera showed the existence, in individual patients, of various combinations of antibody subsets solely reactive to human or bovine β2GPI, together with cross-species reactive subsets present in all samples with dual reactivity namely groups III and II, although the latter antibodies were poorly purified on either column. Therefore, the mode of presentation of β2GPI greatly influences its recognition by anti-β2GPI antibodies with marked inter-individual heterogeneity, in relation to ACA quantitation and, possibly, disease presentation and pathogenesis.

Treatment of venous leg ulcers with sulodexide

Phlebologie ◽  
2003 ◽  
Vol 32 (05) ◽  
pp. 115-120 ◽  
Author(s):  
A. Franek ◽  
H. Koziolek ◽  
M. Kucharzewski
Keyword(s):  
Pharmacological Treatment ◽  
Healing Process ◽  
Leg Ulcers ◽  
Venous Ulceration ◽  
Venous Leg Ulcers ◽  
Group I ◽  
Group Ii

SummaryAim: The study of the influence of sulodexide in the treatment of venous leg ulcers. Patients and method: 44 patients with chronic venous ulceration were randomly divided into two groups. Group I: 21 patients (ulceration area: 12.7-18.9 cm2), Group II: 23 patients (ulceration size: 12.1-20.3 cm2). Both groups were treated by using Unna’s boot. This dressing was changed every seven days until the ulcer had healed. Additionally, the patients in group II received the systemic pharmacological treatment with sulodexide. Results: After 7 weeks of treatment ulcers of seven patients (35%) from group I had healed, and 3 weeks later the ulceration of two more patients had healed completely. After further 7 weeks the ulcers of 12 patients had healed completely. Whereas in group II after 7 weeks of treatment ulceration of 16 (70%, p <0.05) patient had healed completely and after further 3 weeks the ulcers of the remaining 7 patients had healed, too. Conclusion: The use of sulodexide in patients with chronic venous leg ulcers accelerates the healing process.

Effects of Rest and Exercise on Cardiac Blood Volume Determinations

1997 ◽  
Vol 36 (08) ◽  
pp. 259-264
Author(s):  
N. Topuzović
Keyword(s):  
Radionuclide Ventriculography ◽  
Left Ventricular ◽  
Peak Exercise ◽  
Volume Determination ◽  
Group I ◽  
Lv Volumes ◽  
Group Ii ◽  
Lv Volume

Summary Aim: The purpose of this study was to investigate the changes in blood activity during rest, exercise and recovery, and to assess its influence on left ventricular (LV) volume determination using the count-based method requiring blood sampling. Methods: Forty-four patients underwent rest-stress radionuclide ventriculography; Tc-99m-human serum albumin was used in 13 patients (Group I), red blood cells was labeled using Tc-99m in 17 patients (Group II) in vivo, and in 14 patients (Group III) by modified in vivo/in vitro method. LV volumes were determined by a count-based method using corrected count rate in blood samples obtained during rest, peak exercise and after recovery. Results: In group I at stress, the blood activity decreased by 12.6 ± 5.4%, p <0.05, as compared to the rest level, and increased by 25.1 ± 6.4%, p <0.001, and 12.8 ± 4.5%, p <0.05, above the resting level in group II and III, respectively. This had profound effects on LV volume determinations if only one rest blood aliquot was used: during exercise, the LV volumes significantly decreased by 22.1 ± 9.6%, p <0.05, in group I, whereas in groups II and III it was significantly overestimated by 32.1 ± 10.3%, p <0.001, and 10.7 ± 6.4%, p <0.05, respectively. The changes in blood activity between stress and recovery were not significantly different for any of the groups. Conclusion: The use of only a single blood sample as volume aliquot at rest in rest-stress studies leads to erroneous estimation of cardiac volumes due to significant changes in blood radioactivity during exercise and recovery.

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