One-dimensional model of the pulmonary vascular network to study pulmonary hypertension

JEAN VENTRE; MARIA TERESA POLITI; JUAN MANUEL FRANCISCO FERNÁNDEZ; PABLO SPALETRA; MARIANO ABUD; MANUEL LOPEZ SUAREZ; RICARDO RONDEROS; DIEZ, MIRTA; CLAUDIA CAPURRO; JOSE MARIA FULLANA; LAGRÉE, PIERRE-YVES

Paris

Congreso; World Congress on Computational Mechanics (WCCM); 2020

European Community on Computational Methods in Applied Sciences

Background: Pulmonary hypertension is a complex pathology that involves multiple clinical conditionsand can complicate many forms of heart failure [1]. We developed a numerical model of the pulmonaryvascular network to evaluate the patient-specific hemodynamics involved in heart failure and pulmonaryhypertension, which are difficult to assess through routine clinical studies.Methods: We carried invasive pressure measurements from the right heart and pulmonary vascular networkin one patient with heart failure using a Swan-Ganz catheter and an analog-digital converter withinternal hardware filters (MP150, BIOPAC Systems Inc.). The measurements were recorded in five locations:in the right ventricle, in the proximal and distal pulmonary arteries, in the left atrium and in theright radial artery. The systolic volume (SV) was assessed using pulmonary artery thermodilution.We compared these pressure measurements with the numerical predictions of a one-dimensional (1D)blood flow model of the pulmonary vascular network [2], coupled to a zero-dimensional (0D) diodemodel to represent the pulmonary valve. The network consists of three generations of 1D branchesand resistances at the end of the terminal vessels to account for capillary circulation. We imposed themeasured right ventricle pressure as the inlet boundary condition of our model and the left atrium pressureas the outlet boundary condition.Results: We compared the measured and simulated distal artery pressure by fitting the systolic volumeand vascular resistance. We found a high correlation between both signals. Preliminary results showthat the model has great potential for evaluating relevant patient-specific indicators of heart failure andpulmonary hypertension.