Interpretation of venous occlusion plethysmography using a nonlinear model

Anderson, Fred; Durgin, William W.; Wheeler, H. Brownell

doi:10.1007/bf02442692

Cited by 11 publications

(16 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The arm volume was calculated using the larger (below the elbow region) and smaller (at the wrist) arm circumferences. This procedure has been described previously to estimate lower limb volume (Anderson et al 1986).…”

Section: The Proposed Vop Modelmentioning

confidence: 99%

“…The proposed model considered that hydraulic resistance to the forearm venous blood flow is mainly originated by basilic and cephalic veins, which are in parallel association. Considering that these veins have similar resistance values and diameter of approximately 2.9 cm (cephalic vein value referred on Eiken and Kölegard 2004) and a length of about 20 cm (leg deep veins value presented on Anderson et al 1986) and a blood viscosity of 2.63 × 10 −5 mmHg s (Hoeks et al 1995), the estimated R V was 1.5 mmHg s/ml.…”

Section: Arteriolar and Venous Resistancesmentioning

confidence: 99%

“…Most electrical-hydraulic VOP models were proposed in the 1980s and 1990s to estimate venous compliance and resistance of lower limbs (Anderson et al 1986;Seagar et al 1984;Sinton and Seagar 1988). In the early 2000s, Lee et al (2001) and Turner et al (2000) developed VOP models also focused on venous behavior.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A novel model to simulate venous occlusion plethysmography data and to estimate arterial and venous parameters

et al. 2020

View full text Add to dashboard Cite

Introduction Several models of venous occlusion plethysmography (VOP) aim to detect venous mechanical dysfunctions. However, such models ignore arterial contribution to plethysmographic signal. Arterial resistance is an important factor because it regulates blood inflow through veins. Furthermore, modeling arterial compliance and resistance permits evaluation of arterial pressure throughout VOP protocol. Method This study presents a new simulation model and VOP data interpretation, making it possible to estimate arterial and venous mechanical characteristics. The model was evaluated using VOP data obtained under different vascular conditions (placebo, post-ibuprofen, and post-exercise). Results Estimated mean values of venous compliance were 0.34 ml/mmHg (placebo), 0.33 ml/mmHg (post-ibuprofen), and 0.27 ml/mmHg (post-exercise). The corresponding estimated values of venous resistance were 11.55 mmHg s/ml (placebo), 10.58 mmHg s/ml (post-ibuprofen), and 8.84 mmHg s/ml (post-exercise). The estimated mean values of arteriolar resistance were 132.14 mmHg s/ml (placebo), 123.93 mmHg s/ml (post-ibuprofen), and 95.36 mmHg s/ml (post-exercise). Conclusion The estimated values are consistent with previous VOP model results and with expected physiological behavior. The proposed model can provide further information for studies using the VOP technique including studies involving exercise, reactive hyperemia, mental stress, body temperature changes, and vasomotor substance administration.

show abstract

Section: The Proposed Vop Modelmentioning

confidence: 99%

Section: Arteriolar and Venous Resistancesmentioning

confidence: 99%

See 1 more Smart Citation

A novel model to simulate venous occlusion plethysmography data and to estimate arterial and venous parameters

et al. 2020

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…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].…”

mentioning

confidence: 99%

Mathematical model of venous occlusion plethysmography for diagnosing deep vein thrombosis

Lee

Noh

Yoon

et al.

2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

View full text Add to dashboard Cite

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...

show abstract