A Computational Framework to Assess the Influence of Changes in Vascular Geometry on Blood Flow

Many vascular abnormalities, such as aneurysms or stenoses, develop gradually over time. In the early stages of their development, they require monitoring but do not pose sufficient risk to the patient for a clinician to recommend invasive treatment. With a better understanding of the interplay between hemodynamic factors and changes in blood vessel geometry, there is an opportunity to improve clinical care by earlier identification of aneurysms or stenoses with significant potential for further development. Computational fluid dynamics has shown great promise for investigating this interplay and identifying the associated underlying mechanisms, by using patient-derived geometries and modifying them to represent potential evolution of the vascular disease. However, a general, extensible framework for comparing simulation results from different vascular geometries in a direct, quantitative manner does not currently exist. As a first step toward the development of such a framework, we present a method for quantifying the relationship between changes in vascular geometry and hemodynamic factors, such as wall shear stress. We apply this framework to study the correlation between wall shear stress and geometric changes in two opposite settings: when flow properties are associated with consequent changes in the vascular geometry, as in a thoracic aortic aneurysm, and when geometric changes alter the flow, as in a worsening aortic stenosis.

[1]  Lukasz Miroslaw,et al.  Wall Orientation and Shear Stress in the Lattice Boltzmann Model , 2012, 1203.3078.

[2]  E. Edelman,et al.  Role of endothelial shear stress in the natural history of coronary atherosclerosis and vascular remodeling: molecular, cellular, and vascular behavior. , 2007, Journal of the American College of Cardiology.

[3]  D. Harrison,et al.  Endothelial dysfunction in cardiovascular diseases: the role of oxidant stress. , 2000, Circulation research.

[4]  E A Finol,et al.  The effect of asymmetry in abdominal aortic aneurysms under physiologically realistic pulsatile flow conditions. , 2003, Journal of biomechanical engineering.

[5]  M. Lawton,et al.  Correlation between lumenal geometry changes and hemodynamics in fusiform intracranial aneurysms. , 2005, AJNR. American journal of neuroradiology.

[6]  Richard J. Lozowy,et al.  Low wall shear stress predominates at sites of abdominal aortic aneurysm rupture. , 2015, Journal of vascular surgery.

[7]  Habib Samady,et al.  Focal Association Between Wall Shear Stress and Clinical Coronary Artery Disease Progression , 2014, Annals of Biomedical Engineering.

[8]  Charles A. Taylor,et al.  Computational simulations demonstrate altered wall shear stress in aortic coarctation patients treated by resection with end-to-end anastomosis. , 2011, Congenital heart disease.

[9]  Charles A. Taylor,et al.  Computational simulations for aortic coarctation: representative results from a sampling of patients. , 2011, Journal of biomechanical engineering.

[10]  Michail I. Papafaklis,et al.  Prediction of Progression of Coronary Artery Disease and Clinical Outcomes Using Vascular Profiling of Endothelial Shear Stress and Arterial Plaque Characteristics: The PREDICTION Study , 2012, Circulation.

[11]  P. Stone,et al.  Endothelial shear stress in the evolution of coronary atherosclerotic plaque and vascular remodelling: current understanding and remaining questions. , 2012, Cardiovascular research.

[12]  Alastair J. Martin,et al.  Aneurysm Growth Occurs at Region of Low Wall Shear Stress: Patient-Specific Correlation of Hemodynamics and Growth in a Longitudinal Study , 2008, Stroke.

[13]  M. Kendall A NEW MEASURE OF RANK CORRELATION , 1938 .

[14]  S. R. Parks,et al.  Evolution of the wall shear stresses during the progressive enlargement of symmetric abdominal aortic aneurysms , 2006, Journal of Fluid Mechanics.

[15]  Jean Meunier,et al.  Segmentation in Ultrasonic B-Mode Images of Healthy Carotid Arteries Using Mixtures of Nakagami Distributions and Stochastic Optimization , 2009, IEEE Transactions on Medical Imaging.

[16]  Jean Meunier,et al.  Segmentation of Plaques in Sequences of Ultrasonic B-Mode Images of Carotid Arteries Based on Motion Estimation and a Bayesian Model , 2011, IEEE Transactions on Biomedical Engineering.

[17]  Ana Maria Mendonça,et al.  Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction , 2006, IEEE Transactions on Medical Imaging.

[18]  P. Bhatnagar,et al.  A Model for Collision Processes in Gases. I. Small Amplitude Processes in Charged and Neutral One-Component Systems , 1954 .

[19]  Martin Styner,et al.  Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms , 2009, Medical Image Anal..

[20]  Krzysztof Z. Gajos,et al.  Evaluation of Artery Visualizations for Heart Disease Diagnosis , 2011, IEEE Transactions on Visualization and Computer Graphics.

[21]  Peter R. Hoskins,et al.  From Detection to Rupture: A Serial Computational Fluid Dynamics Case Study of a Rapidly Expanding, Patient-Specific, Ruptured Abdominal Aortic Aneurysm , 2014 .

[22]  Fujimaro Ishida,et al.  Low Wall Shear Stress Is Independently Associated With the Rupture Status of Middle Cerebral Artery Aneurysms , 2013, Stroke.

[23]  Erik W. Draeger,et al.  Massively parallel simulations of hemodynamics in the primary large arteries of the human vasculature , 2015, J. Comput. Sci..

[24]  David H. Frakes,et al.  Does the degree of coarctation of the aorta influence wall shear stress focal heterogeneity? , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[25]  John A. Gunnels,et al.  Massively parallel models of the human circulatory system , 2015, SC15: International Conference for High Performance Computing, Networking, Storage and Analysis.