Severity parameter and global importance factor of non-newtonian models in 3D reconstructed human left coronary artery

This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the Makedonia Palace Hotel, Thessaloniki in Greece. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, Aristotle University of Thessaloniki, University of Thessaly, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute.The capabilities and limitations of various molecular viscosity models, when testing Left Coronary Artery (LCA) tree, were analyzed via: molecular viscosity, local and global non-Newtonian importance factors, Wall Shear Stress (WSS) and Wall Shear Stress Gradient (WSSG). Seven non-Newtonian molecular viscosity models, plus the Newtonian one, were compared. Dense grid of 620000 nodes located, mostly, at near to low WSS flow regions (endothelium regions) is needed for current LCA application. The WSS distribution yields a consistent LCA pattern for nearly all non-Newtonian models. High molecular viscosity, low WSS low WSSG values appear at proximal LCA regions at the outer walls of the major bifurcation. The global importance factor for the non-Newtonian power law model yields 76.7% (non-Newtonian flow), while for the Generalized power law model this value is 6.1% (Newtonian flow). The capabilities of the applied non-Newtonian law models appear at low strain rates. The Newtonian blood flow treatment is considered to be a good approximation at mid-and high-strain rates. In general, the non-Newtonian power law and the Generalized power law blood viscosity models are considered to approximate the molecular viscosity and WSS calculations in a more satisfactory way

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP

Semiautomated Skeletonization of the Pulmonary Arterial Tree in Micro-CT Images

We present a simple and robust approach that utilizes planar images at different angular rotations combined with unfiltered back-projection to locate the central axes of the pulmonary arterial tree. Three-dimensional points are selected interactively by the user. The computer calculates a sub- volume unfiltered back-projection orthogonal to the vector connecting the two points and centered on the first point. Because more x-rays are absorbed at the thickest portion of the vessel, in the unfiltered back-projection, the darkest pixel is assumed to be the center of the vessel. The computer replaces this point with the newly computer-calculated point. A second back-projection is calculated around the original point orthogonal to a vector connecting the newly-calculated first point and user-determined second point. The darkest pixel within the reconstruction is determined. The computer then replaces the second point with the XYZ coordinates of the darkest pixel within this second reconstruction. Following a vector based on a moving average of previously determined 3- dimensional points along the vessel\u27s axis, the computer continues this skeletonization process until stopped by the user. The computer estimates the vessel diameter along the set of previously determined points using a method similar to the full width-half max algorithm. On all subsequent vessels, the process works the same way except that at each point, distances between the current point and all previously determined points along different vessels are determined. If the difference is less than the previously estimated diameter, the vessels are assumed to branch. This user/computer interaction continues until the vascular tree has been skeletonized

Clinical risk factors and atherosclerotic plaque extent to define risk for major events in patients without obstructive coronary artery disease: the long-term coronary computed tomography angiography CONFIRM registry.

AimsIn patients without obstructive coronary artery disease (CAD), we examined the prognostic value of risk factors and atherosclerotic extent.Methods and resultsPatients from the long-term CONFIRM registry without prior CAD and without obstructive (≥50%) stenosis were included. Within the groups of normal coronary computed tomography angiography (CCTA) (N = 1849) and non-obstructive CAD (N = 1698), the prognostic value of traditional clinical risk factors and atherosclerotic extent (segment involvement score, SIS) was assessed with Cox models. Major adverse cardiac events (MACE) were defined as all-cause mortality, non-fatal myocardial infarction, or late revascularization. In total, 3547 patients were included (age 57.9 ± 12.1 years, 57.8% male), experiencing 460 MACE during 5.4 years of follow-up. Age, body mass index, hypertension, and diabetes were the clinical variables associated with increased MACE risk, but the magnitude of risk was higher for CCTA defined atherosclerotic extent; adjusted hazard ratio (HR) for SIS >5 was 3.4 (95% confidence interval [CI] 2.3-4.9) while HR for diabetes and hypertension were 1.7 (95% CI 1.3-2.2) and 1.4 (95% CI 1.1-1.7), respectively. Exclusion of revascularization as endpoint did not modify the results. In normal CCTA, presence of ≥1 traditional risk factors did not worsen prognosis (log-rank P = 0.248), while it did in non-obstructive CAD (log-rank P = 0.025). Adjusted for SIS, hypertension and diabetes predicted MACE risk in non-obstructive CAD, while diabetes did not increase risk in absence of CAD (P-interaction = 0.004).ConclusionAmong patients without obstructive CAD, the extent of CAD provides more prognostic information for MACE than traditional cardiovascular risk factors. An interaction was observed between risk factors and CAD burden, suggesting synergistic effects of both

Comparing stenotic blood flow in three- and two-dimensional arterial renderings using computational fluid dynamics and multiphase mean age theory.

Over one million invasive coronary angiography procedures are performed annually in patients who experience chest pain or are known to have coronary artery disease. The procedure is carried out to ascertain the degree of arterial blockage (stenosis) that hinders blood flow to the heart. A cardiologist performing the procedure determines the physiological degree of a stenosis by either visual estimation, which is routine practice, or by invasively measuring fractional flow reserve (FFR), which is the current gold standard that has been demonstrated to improve patient outcomes and temper the cost of healthcare. Nevertheless, FFR is performed in only 10–20% of patients because it is invasive, expensive, and requires more radiation exposure. New computational methods utilizing three-dimensional renderings processed from coronary angiograms can provide an accurate, highly sensitive, non-invasive method to assess stenotic significance without using FFR. While beneficial, this technique requires intensive computer processing power and calculation runtimes on the order of several hours. An approach to reduce computational time involves alike computing of two-dimensional arterial slices cut from the three-dimensional source renderings. The main objective was to determine if two-dimensional processing can also provide an accurate and highly sensitive method to assess stenotic significance at a fraction of the computational expense. Blood flow was analyzed in five patient cases below and five patient cases above the commonly accepted FFR threshold value for intervention of 0.80. Following the generation of two orthogonal slices from DICOM-derived three-dimensional renderings, pulsing blood flow was simulated with CFD, and multiphase mean age theory was applied to calculate the mean age of red blood cells as a diagnostic metric. Two-dimensional processing typically exhibited a correlation with FFR only in the geometries of vertically-oriented slices. This was ascribed to the possibility of uncaptured stenotic blood flow characteristics in the limited testing of only two angles of a full arterial segment.Mean ages for the three-dimensional cases were many orders of magnitude higher than those of the corresponding two-dimensional cases. This was attributed to red blood cell collisions and distal recirculatory eddies near a stenosisbeing less expressed in the simplicity of the two-dimensional slices when compared to the complexity of the three-dimensional source renderings. A mean age threshold for determining stent intervention was estimated for the two-dimensional cases since limited sample size disallowed rigorous statistical analysis. The data suggested an arbitrary value equal to ~2.5. Nine out of ten cases correlated with FFR, with just one false negative diagnosis. In published virtual FFR techniques, false diagnosis typically occurs in 10–13% of the cases. Computational runtime for two-dimensional cases was less than 2% of the runtime for corresponding three-dimensional cases. Preliminary results indicate two-dimensional processing may efficiently detect and assess stenoses non-invasively, provided that it holds up to rigorous statistical analysis following testing of at least 80–100 more cases, plus several additional slice angles

A one-dimensional hemodynamic model of the coronary arterial tree

One-dimensional (1D) hemodynamic models of arteries have increasingly been applied to coronary circulation. In this study, we have adopted flow and pressure profiles in Olufsen's 1D structured tree as coronary boundary conditions, with terminals coupled to the dynamic pressure feedback resulting from the intra-myocardial stress because of ventricular contraction. We model a trifurcation structure of the example coronary tree as two adjacent bifurcations. The estimated results of blood pressure and flow rate from our simulation agree well with the clinical measurements and published data. Furthermore, the 1D model enables us to use wave intensity analysis to simulate blood flow in the developed coronary model. Six characteristic waves are observed in both left and right coronary flows, though the waves' magnitudes differ from each other. We study the effects of arterial wall stiffness on coronary blood flow in the left circumflex artery (LCX). Different diseased cases indicate that distinct pathological reactions of the cardiovascular system can be better distinguished through Wave Intensity analysis, which shows agreement with clinical observations. Finally, the feedback pressure in terminal vessels and measurement deviation are also investigated by changing parameters in the LCX. We find that larger feedback pressure increases the backward wave and decreases the forward one. Although simplified, this 1D model provides new insight into coronary hemodynamics in healthy and diseased conditions. We believe that this approach offers reference resources for studies on coronary circulation disease diagnosis, treatment and simulation

Oscillating shear index, wall shear stress and low density lipoprotein accumulation in human RCAs

This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the Makedonia Palace Hotel, Thessaloniki in Greece. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, Aristotle University of Thessaloniki, University of Thessaly, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute.Atherosclerosis shows predilection in regions of coronary arteries with hemodynamic particularities as, local disturbances of Wall Shear Stress (WSS) in space and time, and locally high concentrations of lipoprotein. Six, image-based human deceased, Right Coronary Arteries (RCA) are used to elucidate, a) Low Density Lipoprotein (LDL) transport under steady flow and b) oscillating flow (no mass transfer). A semi-permeable nature of the arterial wall computational model is incorporated with hydraulic conductivity and permeability treated as WSS dependent. The 3D reconstruction technique is a combination of angiography and IVUS. LDL is elevated at locations where WSS is low. Under steady flow conditions the area-averaged normalized LDL concentration over the RCAs, using shear dependent water infiltration and endothelial permeability is 9.6 % higher than at entrance. However, under constant water infiltration and endothelial permeability this value is only 3.2 %. High Oscillating Shear Index (OSI) and low average WSS nearly co-locate. Approximately 630000 grid nodes proved to be sufficient enough to accurately describe the oscillating flow and the LDL concentration within the RCAs

Modelling and simulation of myocardial infarction in the human cardiovascular system

Modelling the physiological processes leading to myocardial infarction can help ameliorate the severity of the condition by improving early detection. Thus, the aim of this study was to model the cardiovascular system and simulate its response to myocardial infarction. Two methods were deployed for this simulation. The first method is the Computational Fluid Mechanics approach, simulated using Mathematica and the solutions of the resulting equations were obtained using Differential Transform Method. The second method is the Lumped Parameter method, simulated using MATLAB/Simulink. With Computational Fluid Mechanics, at 0% blockage within the arteries, no significant stress on the arterial wall was observed. At 10% and 50% blockage levels, a gradual increase in stress from the inlet through the entire arteries’ length was observed. 100% blockage resulted in an exponential increase in the stress. A similar output was seen with the Lumped Parameter approach. The blood flow decreases rapidly and reaches zero at a pressure of about 170mmHg. The responses of the different arteries to myocardial infarction as simulated can be applied in the early detection of heart diseases.Keywords: myocardial infarction, stress, pressure, blood flow, arterial blockag