Mathematical model of venous occlusion plethysmography for diagnosing deep vein thrombosis

Abstract

Abstract-Although the results of VOP can determine the being of DVT, it has difficulty in analyzing quantitatively the effects of the degrees of thrombosis, blood pressure and cuff pressure on VOP. In this paper, by developing a combined model that is composed of pulsatile cardiovascular model and venous occlusion model, we showed the availability of more realistic simulation. Using the proposed combined model in simulation about the effects of different head pressure and degree of thrombosis on VOP, we can get the basic understanding what relationship is between the state of patient and measured VOP. Keywords -Deep venous thrombosis, venous occlusion plethysmography, mathematical model I. INTRODUCTIONDeep venous thrombosis(DVT) is the formation of blood clots in the deep venous system. It is a source of morbidity or mortality after surgery and a complication in many other branches of medicine. While invasive methods for DVT detection such as venography are most accurate, they could cause some risk to the patient. As a result there has been many studies on non-invasive techniques, including venous occlusion plethysmography(VOP), to screen patients for the presence of DVT [1][2][3].Although the results of VOP are helpful to detect DVT, being an indirect measure, there are difficulties in quantitative comparison of results that come from different degrees of thrombosis. So, there has been a study which estimates the effects of thrombosis size on patient's venous outflow with a numerical model [4].In this study, by developing a mathematical model which consists of cardiovascular system model and venous occlusion model, basic understanding of relationships between the hemodynamic changes caused by varying VOP related parameters and the indirect measurements such as impedance plethysmography (IPG) and strain gauge plethysmography (SPG), are offered. II. METHODOLOGYTotal cardiovascular system is a loop that has many blood branches and at individual compartment of system, blood pressure, flow and blood volume provides meaningful clinical information. Each compartment has their own resistance, inertance and compliance and, from the value, cardiovascular system can be modelled [5]. Fig. 1 shows a simple cardiovascular model.In Fig. 2, a venous occlusion model is shown. Ra is the arterial resistance, Rcap the capillary resistance, Rcalf the total resistance of anterior tibial, posterior tibial and peroneal resistance, Rfem the femoral resistance, Rsaph the saphenous resistance, Cv the compliance of calf vein. where Pa is the arterial pressure, Pcuff is the cuff pressure, Ph is the head pressure due to leg raising, Rv is the venous resistance and Ra is the arterial resistance. To combine two models, the mean arterial pressure of the cardiovascular model was used as the arterial inflow. In this study, the effects of leg raise and the changes of vein resistance and compliance caused by DVT were simulated. Additionally, the waveform of IPG contaminated by the arterial pulses was generated. Numerical values of equation paramet...

A Haemodynamic Model of the Venous Network of the Lower Limbs

“…The mechanism of the venous return and the cardiovascular response upon gravity changes was also studied in [5]. Another model [6] helps to diagnose the deep vein thrombosis starting from venous occlusion plethysmography measurements.…”