A Numerical Model for Simulation of Blood Flow in Vascular Networks

An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray's Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray's Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data

A Numerical Model for Simulation of Blood Flow in Vascular Networks

An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray's Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray's Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data

A Numerical Model for Simulation of Blood Flow in Vascular Networks

An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray's Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray's Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data

A Numerical Model for Simulation of Blood Flow in Vascular Networks

An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray's Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray's Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data

A Randomized Trial of the Optimum Duration of Acoustic Pulse Thrombolysis Procedure in Acute Intermediate-Risk Pulmonary Embolism: The OPTALYSE PE Trial.

The aim of this study was to determine the lowest optimal tissue plasminogen activator (tPA) dose and delivery duration using ultrasound-facilitated catheter-directed thrombolysis (USCDT) for the treatment of acute intermediate-risk (submassive) pulmonary embolism.This article is freely available via Open Access. Click on the Additional Link above to access the full-text via the publisher's site

The Simulation of Pulmonary Arterial Vascular System - A Computational Fluid Dynamics Study

Clinical studies suggest that hemodynamic factors and biomechanical forces play key roles in pulmonary vascular disease; any condition which affects the route of blood flow between the heart and lungs. Research in this area that involves simulating large networks of pulmonary vessels using computational fluid dynamics is rare. This is because conventional visualisation techniques such as direct volume rendering and surface rendering using contrast enhanced computed tomography (CT) or magnetic resonance imaging (MRI) data fail to resolve the smaller and more extensively networked pulmonary vascular trees or recognise the complex spatial relations of the vascular tree and its surrounding structures in detail. Meanwhile, solutions to the governing equations of blood flow in the large arteries are highly dependent on the outflow boundary conditions imposed to represent the vascular bed downstream of the modelled domain. The most common outflow boundary conditions, especially for threedimensional simulations of blood flow, are prescribed constant pressure or traction and prescribed velocity profiles. In many simulations, however, the flow distribution and pressure field in the modelled domain are unknown and cannot be prescribed at the outflow boundaries. Accurate hemodynamic predictions can only be achieved by creating a model with both a region of interest and the downstream network of vessels that are an accurate reflection of the organ system in question. In this study, we introduce two different approaches to take into account feedback mechanisms of the distal networks in computational simulations

A Numerical Model for Simulation of Blood Flow in Vascular Networks

An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray's Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray's Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data

A Numerical Model for Simulation of Blood Flow in Vascular Networks

An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray's Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray's Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data

Correlation of Stroke Volume Measurement between Sonosite Portable Echocardiogram and Edwards Flotrac Sensor-Vigileo Monitor in an Intensive Care Unit

Purpose Stroke volume (SV) is a parameter that is being recognized as an endpoint in fluid resuscitation algorithms. Its role is now being realized as an important variable in hemodynamic assessment in various clinical scenarios such as septic and cardiogenic shocks. Direct measurement of stroke volume (SV) and its novel corollary, stroke volume variation (SVV) derived by proprietary software, are preferred over mean cardiac output (CO) measurements because they render a more accurate reflection of hemodynamic status independent of heart rate. Flotrac-Vigileo monitor (FTV) (Edwards Lifesciences, Irvine, CA, USA) is a system that uses a complex algorithm analyzing arterial waveform to calculate SV, SVV, and CO. We assessed the feasibility of obtaining SV measurements with a portable echocardiogram and validated its accuracy with the FTV system in mechanically ventilated patients in our intensive care unit (ICU). Furthermore, we emphasized the importance of hemodynamic measurements and familiarity with critical care echocardiography for the intensivists. Methods Ten patients who were on mechanical ventilation were studied. A femoral arterial line was connected to the FTV system monitoring SV and CO. A portable echocardiogram (M-Turbo; Sonosite, Bothell, WA) was used to measure SV. CO was calculated by multiplying SV by heart rate. No patient had arrhythmia. We used biplane Simpson's method of discs to calculate SV in which subtraction of end-systolic volume from end-diastolic volume yields the SV Results The comparison of simultaneous SV and CO measurements by echocardiography with FTV showed a strong correlation between the 2. (For SV, y = 0.9545x + 3.3, R 2 = 0.98 and for CO, y = 0.9104x + 7.7074, R 2 = 0.97). Conclusions In our small cohort, the SV and CO measured by a portable echocardiogram (Sonosite M-Turbo) appears to be closely correlated with their respective values measured by FTV. Portable echocardiography is a reliable noninvasive tool for the hemodynamic assessment of the critically ill. Its results need further validation with gold standard measures in a larger cohort of patients. However, our results suggest portable echocardiography could be an attractive tool in assessment of different hemodynamic scenarios in the critically ill