Electrical modelling of tissue experiments confirms precise locations of resistance and compliance in systemic arterial tree ‐ they are mutually exclusive

Author(s):  
Naveen Gangadharan ◽  
V Aravindhan ◽  
Benjamin Jebaraj ◽  
Shikha Mary Zachariah ◽  
Suresh Devasahayam ◽  
...  
2009 ◽  
Vol 297 (1) ◽  
pp. H208-H222 ◽  
Author(s):  
Philippe Reymond ◽  
Fabrice Merenda ◽  
Fabienne Perren ◽  
Daniel Rüfenacht ◽  
Nikos Stergiopulos

A distributed model of the human arterial tree including all main systemic arteries coupled to a heart model is developed. The one-dimensional (1-D) form of the momentum and continuity equations is solved numerically to obtain pressures and flows throughout the systemic arterial tree. Intimal shear is modeled using the Witzig-Womersley theory. A nonlinear viscoelastic constitutive law for the arterial wall is considered. The left ventricle is modeled using the varying elastance model. Distal vessels are terminated with three-element windkessels. Coronaries are modeled assuming a systolic flow impediment proportional to ventricular varying elastance. Arterial dimensions were taken from previous 1-D models and were extended to include a detailed description of cerebral vasculature. Elastic properties were taken from the literature. To validate model predictions, noninvasive measurements of pressure and flow were performed in young volunteers. Flow in large arteries was measured with MRI, cerebral flow with ultrasound Doppler, and pressure with tonometry. The resulting 1-D model is the most complete, because it encompasses all major segments of the arterial tree, accounts for ventricular-vascular interaction, and includes an improved description of shear stress and wall viscoelasticity. Model predictions at different arterial locations compared well with measured flow and pressure waves at the same anatomical points, reflecting the agreement in the general characteristics of the “generic 1-D model” and the “average subject” of our volunteer population. The study constitutes a first validation of the complete 1-D model using human pressure and flow data and supports the applicability of the 1-D model in the human circulation.


2014 ◽  
Vol 26 (01) ◽  
pp. 1450002 ◽  
Author(s):  
Hanguang Xiao

The early detection and intervention of artery stenosis is very important to reduce the mortality of cardiovascular disease. A novel method for predicting artery stenosis was proposed by using the input impedance of the systemic arterial tree and support vector machine (SVM). Based on the built transmission line model of a 55-segment systemic arterial tree, the input impedance of the arterial tree was calculated by using a recursive algorithm. A sample database of the input impedance was established by specifying the different positions and degrees of artery stenosis. A SVM prediction model was trained by using the sample database. 10-fold cross-validation was used to evaluate the performance of the SVM. The effects of stenosis position and degree on the accuracy of the prediction were discussed. The results showed that the mean specificity, sensitivity and overall accuracy of the SVM are 80.2%, 98.2% and 89.2%, respectively, for the 50% threshold of stenosis degree. Increasing the threshold of the stenosis degree from 10% to 90% increases the overall accuracy from 82.2% to 97.4%. Increasing the distance of the stenosis artery from the heart gradually decreases the overall accuracy from 97.1% to 58%. The deterioration of the stenosis degree to 90% increases the prediction accuracy of the SVM to more than 90% for the stenosis of peripheral artery. The simulation demonstrated theoretically the feasibility of the proposed method for predicting artery stenosis via the input impedance of the systemic arterial tree and SVM.


Author(s):  
Philippe Reymond ◽  
Fabrice Merenda ◽  
Fabienne Perren ◽  
Daniel Rüfenacht ◽  
Nikos Stergiopulos

The aim of this study is to develop a distributed model of the entire systemic arterial tree, coupled to a heart model and including a detailed description of the cerebral arteries. Distributed models of the arterial tree have been studied extensively in the past (Avolio [1], Stergiopulos et al [2], Westerhof et al [3]), however, no model has been developed so far that offers a physiologically relevant coupling to the heart and includes the entire cerebral arterial tree.


Author(s):  
Philippe Reymond ◽  
Fabrice Merenda ◽  
Fabienne Perren ◽  
Daniel Rüfenacht ◽  
Nikos Stergiopulos

The aim of this study is to develop a distributed model of the entire systemic arterial tree, coupled to a heart model and including a detailed description of the cerebral arteries. Distributed models of the arterial tree have been studied extensively in the past (Avolio [1]; Cassot et al [2]; Meister [3]; Schaaf and Abbrecht [4]; Stergiopulos et al [5]; Westerhof et al [6]; Zagzoule and Marc-Vergnes [7]), however, no model has been developed so far that offers a physiologically relevant coupling to the heart and includes the entire cerebral artery network.


2020 ◽  
Vol 8 ◽  
Author(s):  
Berend E. Westerhof ◽  
Martin J. C. van Gemert ◽  
Jeroen P. van den Wijngaard

2011 ◽  
Vol 5 (4) ◽  
pp. 164
Author(s):  
B.E. Westerhof ◽  
J.P. van den Wijngaard ◽  
J. van Goudoever ◽  
M.J. van Gemert ◽  
J.A. Spaan

2014 ◽  
Vol 8 (4) ◽  
pp. 154
Author(s):  
L. Aslanidou ◽  
B. Trachet ◽  
P. Reymond ◽  
P. Segers ◽  
N. Stergiopulos

2011 ◽  
Vol 301 (3) ◽  
pp. H1173-H1182 ◽  
Author(s):  
Philippe Reymond ◽  
Yvette Bohraus ◽  
Fabienne Perren ◽  
Francois Lazeyras ◽  
Nikos Stergiopulos

The aim of this study is to develop and validate a patient-specific distributed model of the systemic arterial tree. This model is built using geometric and hemodynamic data measured on a specific person and validated with noninvasive measurements of flow and pressure on the same person, providing thus a patient-specific model and validation. The systemic arterial tree geometry was obtained from MR angiographic measurements. A nonlinear viscoelastic constitutive law for the arterial wall is considered. Arterial wall distensibility is based on literature data and adapted to match the wave propagation velocity of the main arteries of the specific subject, which were estimated by pressure waves traveling time. The intimal shear stress is modeled using the Witzig-Womersley theory. Blood pressure is measured using applanation tonometry and flow rate using transcranial ultrasound and phase-contrast-MRI. The model predicts pressure and flow waveforms in good qualitative and quantitative agreement with the in vivo measurements, in terms of wave shape and specific wave features. Comparison with a generic one-dimensional model shows that the patient-specific model better predicts pressure and flow at specific arterial sites. These results obtained let us conclude that a patient-specific one-dimensional model of the arterial tree is able to predict well pressure and flow waveforms in the main systemic circulation, whereas this is not always the case for a generic one-dimensional model.


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