The arterial Windkessel

Frank’s Windkessel model described the hemodynamics of the arterial system in terms of resistance and compliance. It explained aortic pressure decay in diastole, but fell short in systole. Therefore characteristic impedance was introduced as a third element of the Windkessel model. Characteristic impedance links the lumped Windkessel to transmission phenomena (e.g., wave travel). Windkessels are used as hydraulic load for isolated hearts and in studies of the entire circulation. Furthermore, they are used to estimate total arterial compliance from pressure and flow; several of these methods are reviewed. Windkessels describe the general features of the input impedance, with physiologically interpretable parameters. Since it is a lumped model it is not suitable for the assessment of spatially distributed phenomena and aspects of wave travel, but it is a simple and fairly accurate approximation of ventricular afterload

Modeling the Instantaneous Pressure–Volume Relation of the Left Ventricle: A Comparison of Six Models

Simulations are useful to study the heart’s ability to generate flow and the interaction between contractility and loading conditions. The left ventricular pressure–volume (PV) relation has been shown to be nonlinear, but it is unknown whether a linear model is accurate enough for simulations. Six models were fitted to the PV-data measured in five sheep and the estimated parameters were used to simulate PV-loops. Simulated and measured PV-loops were compared with the Akaike information criterion (AIC) and the Hamming distance, a measure for geometric shape similarity. The compared models were: a time-varying elastance model with fixed volume intercept (LinFix); a time-varying elastance model with varying volume intercept (LinFree); a Langewouter’s pressure-dependent elasticity model (Langew); a sigmoidal model (Sigm); a time-varying elastance model with a systolic flow-dependent resistance (Shroff) and a model with a linear systolic and an exponential diastolic relation (Burkh). Overall, the best model is LinFree (lowest AIC), closely followed by Langew. The remaining models rank: Sigm, Shroff, LinFix and Burkh. If only the shape of the PV-loops is important, all models perform nearly identically (Hamming distance between 20 and 23%). For realistic simulation of the instantaneous PV-relation a linear model suffices

Multimodal Data Fusion for Big Events

Many of the transportation problems prevalent in urban areas culminate in large-scale events. Such events generate large multimodal flows that arrive and depart within short time intervals to constrained areas. Monitoring and managing big events pose a challenge for transport planners, operators, event organizers, and city officials. In this study, data concerning multimodal flows were collected and analyzed for a so-called triple event in Amsterdam, Netherlands, where more than 60,000 people visited the Amsterdam ArenA area. The collection and fusion of large and diverse data sets provided this study a unique opportunity to reconstruct, from incomplete data, the crowds’ arrival and departure times and estimate their modal-split patterns. Considerably different arrival and departure time patterns were observed for car and public transport users. Visitors using public transport arrived approximately 45 min before the start times of the events compared with 75 min for car users. The lag between the event end time and the departure time of public transport users was approximately 20 to 50 min, whereas a lag of 20 to 80 min was observed for departing cars. The factors that possibly underlie these differences are discussed as are the limitations in the analysis. The results of this study can support decisions about the allocation of parking lots and the scheduling of public transport services.Transport and Plannin

Magnetic resonance and nuclear imaging of the right ventricle in pulmonary arterial hypertension

Many clinicians have recognized the unique possibilities of magnetic resonance imaging (MRI) for the study of right ventricular (RV) anatomy. Especially for the assessment of the RV in pulmonary hypertension, MRI has been proven to be of clinical importance. It is, however, less well known that if MRI measures of volume and flow are combined with pressure measurements, accurate description of RV function in relation to its afterload is possible. Furthermore, nuclear imaging techniques offer the opportunity to study the altered RV metabolism and to elucidate the possible contribution of ischaemia to RV failure in pulmonary hypertension. Since RV failure in pulmonary hypertension is the result of the complex interaction between geometry, structure, function, perfusion, and metabolism, MRI and nuclear imaging are promising techniques to study these mechanisms and to evaluate the effects of therapy aimed at improving RV function in pulmonary hypertension

Quantification of right ventricular afterload in patients with and without pulmonary hypertension

Right ventricular (RV) afterload is commonly defined as pulmonary vascular resistance, but this does not reflect the afterload to pulsatile flow. The purpose of this study was to quantify RV afterload more completely in patients with and without pulmonary hypertension (PH) using a three-element windkessel model. The model consists of peripheral resistance (R), pulmonary arterial compliance (C), and characteristic impedance (Z). Using pulmonary artery pressure from right-heart catheterization and pulmonary artery flow from MRI velocity quantification, we estimated the windkessel parameters in patients with chronic thromboembolic PH (CTEPH; n = 10) and idiopathic pulmonary arterial hypertension (IPAH; n = 9). Patients suspected of PH but in whom PH was not found served as controls (NONPH; n = 10). R and Z were significantly lower and C significantly higher in the NONPH group than in both the CTEPH and IPAH groups (P < 0.001). R and Z were significantly lower in the CTEPH group than in the IPAH group (P < 0.05). The parameters R and C of all patients obeyed the relationship C = 0.75/R (R(2) = 0.77), equivalent to a similar RC time in all patients. Mean pulmonary artery pressure P and C fitted well to C = 69.7/P (i.e., similar pressure dependence in all patients). Our results show that differences in RV afterload among groups with different forms of PH can be quantified with a windkessel model. Furthermore, the data suggest that the RC time and the elastic properties of the large pulmonary arteries remain unchanged in PH