NUMERICAL SIMULATION AND VALIDITY OF A NOVEL METHOD FOR THE PREDICTION OF ARTERY STENOSIS VIA INPUT IMPEDANCE AND SUPPORT VECTOR MACHINE

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.

Validation of a patient-specific one-dimensional model of the systemic arterial tree

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.

A Coupled Simulation of Spinal Cord Blood Flow and Cerebrospinal Fluid Motion in the Spinal Subarachnoid Space Based on In Vivo Measurements

A preliminary coupled 1-D model of the systemic arterial tree and cerebrospinal fluid (CSF) system was constructed. The systemic tree model includes arteries greater than 2 mm in diameter and a simplified spinal cord vasculature. Coupling of the arterial tree and CSF system is accomplished by a transfer function based on in vivo cerebral blood flow (CBF) and CSF pulsation measurements in 17 young healthy adults. A 1-D tube model of the CSF in the spinal subarachnoid space (SSS) is formed based on in vivo measurements and used to determine flow and pressure along the SSS. The pressure and flow results in the CSF and systemic arterial tree are qualitatively and quantitatively similar to in vivo measurements in healthy subjects. The relative arrival time of blood pulsations in the spinal cord and CSF in the SSS is impacted by CSF system compliance and geometry. With low CSF system compliance the CSF pulsations arrive around the spinal cord before arterial pulsations and vice versa. Overall, the preliminary results support that geometric and mechanical properties of the CSF and cardiovascular system have an important impact on the flow and pressure environment and accent the importance to obtain in vivo measurements to improve modeling capabilities.