scholarly journals Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

2016 ◽  
Vol 33 (3) ◽  
pp. e02799 ◽  
Author(s):  
Daniele E. Schiavazzi ◽  
Alessia Baretta ◽  
Giancarlo Pennati ◽  
Tain-Yen Hsia ◽  
Alison L. Marsden
Keyword(s):  
Parameter Estimation ◽  
Single Ventricle ◽  
Patient Specific ◽  
Specific Parameter

scholarly journals Arrhythmogenic cardiomyopathy is characterized by apex-to-base heterogeneity of right ventricular myocardial contractility, stiffness, and mechanical delay: a patient-specific modeling study

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
N Van Osta ◽  
F Kirkels ◽  
A Lyon ◽  
T Koopsen ◽  
TAM Van Loon ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Patient Specific ◽  
Myocardial Tissue ◽  
Free Wall ◽  
Longitudinal Deformation ◽  
Arrhythmogenic Cardiomyopathy ◽  
Tissue Properties ◽  
Specific Parameter ◽  
Deformation Patterns ◽  
Modelling Approach

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NWO-ZonMw, VIDI grant 016.176.340 Dutch Heart Foundation (2015T082) Introduction Arrhythmogenic Cardiomyopathy (AC) is an inherited cardiac disease, characterized by life-threatening ventricular arrhythmias and progressive cardiac dysfunction. Geno-positive subjects with and without symptoms may suffer from sudden cardiac death. Therefore, early disease detection and risk stratification is important. Right ventricular (RV) longitudinal deformation abnormalities in early stages of disease have been shown to be of prognostic value. We propose an imaging-based patient-specific computer modelling approach for non-invasive quantification of regional ventricular tissue abnormalities. Purpose To non-invasively reveal the individual patient’s myocardial tissue substrates underlying the regional RV deformation abnormalities in AC mutation carriers. Methods In 65 individuals carrying a plakophilin-2 or desmoglein-2 mutation and 20 control subjects, regional longitudinal deformation patterns of the RV free wall (RVfw), interventricular septum (IVS) and left ventricular free wall (LVfw) were obtained using speckle-tracking echocardiography (Figure: left). This cohort was subdivided into 3 consecutive clinical stages i.e. subclinical (concealed, n = 18) with no abnormalities, electrical stage (n = 13) with only electrocardiographic abnormalities, and structural stage (n = 34) with both electrical and structural abnormalities defined by the 2010 Task Force AC criteria. We developed and used a patient-specific parameter estimation protocol based on the multi-scale CircAdapt cardiovascular system model to create virtual AC subjects (Figure: middle). Using the individuals’ RVfw, IVS, and LVfw strain patterns as model input, this protocol automatically estimated regional RV and global IVS and LVfw tissue properties, such as myocardial contractility, stiffness, and activation delay. Results The computational model was able to reproduce the regional deformation patterns as measured clinically. Patient-specific parameter estimation results (Figure: right) revealed that clinical AC disease progression is characterized by a decrease in contractility and an increase in stiffness and mechanical delay of the RV myocardial tissue in the basal segment compared to the apex. The subclinical stage subjects showed tissue properties comparable to the control group, including a small apex-to-base heterogeneity in tissue properties. Conclusion Our patient-specific modelling approach is able to reveal individual myocardial substrates underlying the regional RV deformation abnormalities. Early abnormalities in RV longitudinal strain are most likely caused by increased heterogeneity in local tissue properties, such as an apex-to-base decrease of contractility, increased of myocardial stiffness, and time to peak stress. Abnormalities in tissue properties may be found already in the subclinical stage. In future studies, this artificial intelligence approach will be used to investigate how these abnormalities relate to disease progression and arrhythmogenic risk. Abstract Figure. Characterization of AC Disease Substrate

scholarly journals Limitations in the Assessment of Prosthesis-Patient Mismatch

2019 ◽  
Vol 68 (07) ◽  
pp. 550-556 ◽  
Author(s):  
Paulo A. Amorim ◽  
Mahmoud Diab ◽  
Mario Walther ◽  
Gloria Färber ◽  
Andreas Hagendorff ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Surface Area ◽  
Body Surface Area ◽  
Body Surface ◽  
Patient Specific ◽  
Effective Orifice Area ◽  
Pressure Gradients ◽  
Specific Parameter ◽  
Impact On Survival ◽  
The Individual

Abstract Background Prosthesis-patient mismatch (PPM) after aortic valve replacement (AVR) may affect survival but data are conflicting. It is assessed by relating effective orifice area (EOA) to body surface area (EOAi). EOA is patient-specific as the result of flow-velocity times area at the individual patient's outflow tract levels (LVOTA) divided by trans-prosthetic flow velocity. However, some studies use projected EOAs (i.e., valve size associated EOAs from other patient populations) to assess how PPM affects outcome. Methods We analyzed 76 studies addressing hemodynamic outcome and/or mortality after bioprosthetic AVR. Results In 48 studies, projected or measured EOA for calculation of EOAi and PPM assessment was used (of which 25 demonstrated an effect on survival). We identified 28 additional studies providing measured EOA values and the corresponding Bernoulli's pressure gradients after AVR. Despite EOA being a patient-specific parameter, 77% of studies assessing a PPM impact on survival used projected EOAs. The 28 studies are providing measured EOA values and the corresponding Bernoulli's pressure gradients in patients after AVR showed a highly significant, linear relationship between EOA and Bernoulli's gradient. Considering this relationship, it is surprising that relating EOA to body surface area (BSA) (EOAi) is standard but relating pressure gradients to BSA is not. Conclusion We conclude that the majority of studies assessing PPM have used false assumptions because EOA is a patient-specific parameter and cannot be transferred to other patients. In addition, the use of EOAi to assess PPM may not be appropriate and could explain the inconsistent relation between PPM and survival in previous studies.

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