title: Computational Study of Anatomical Risk Factors in Idealized Models of Type B Aortic Dissection.
abstract: Several risk factors have been identified in type B aortic dissection (TBAD), namely tear size, location, patency and number, and false lumen (FL) location. However, the individual impact of each of these factors is poorly understood. The impact of these factors was investigated using computational fluid dynamics (CFD).
  
  
  
  Fourteen idealized models of chronic TBAD were created of different shapes (straight vs. curved vessels), different number of proximal and distal tears, tear size (4, 10, and 20 mm diameter) and shape (circular or elliptical), FL location (inner or outer arch), treated (stented), and untreated. All models had identical length, relative size of true lumen (TL) and FL, and inlet (flow) and outlet (pressure) boundary conditions. Using validated CFD tools, inlet mean pressure (MP), pulse pressure (PP), TL and FL pressures, velocities, and flows were computed for each model.
  
  
  
  AD increased PP and MP relative to undissected aorta. Curvature did not change pressure and flow ratio between TL and FL. Inner curvature FL showed slightly larger pressures and tear velocities. Larger tears decreased hemodynamic differences between TL and FL. The combination of proximal and distal tear size determines the overall hemodynamics: larger proximal tears increased FL PP by up to 76%. Conversely, larger distal tears decreased FL PP and MP. Large proximal and distal tears decreased tear velocity (by up to 65%) and increased FL flow (up to 12 times). Proximal tear stenting resulted in a 54% reduction of PP. Conversely, distal occlusion tear increased FL PP and MP by 144% and 7%, respectively.
  
  
  
  Unfavorable hemodynamic conditions such as larger FL pressure occur when distal tear is small or absent, proximal tears are large, and FL is at the inner curvature, in agreement with previous clinical studies. CFD analysis is a powerful tool to understand the interplay between anatomy and hemodynamics in TBAD.
authors: Department of Surgery, University of Michigan, Ann Arbor, MI, USA; CHU Clermont-Ferrand, Department of Vascular Surgery, F63003 Clermont-Ferrand, France.
authors: S
authors: S
authors: Ben Ahmed
authors: Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
authors: D
authors: D
authors: Dillon-Murphy
authors: Department of Surgery, University of Michigan, Ann Arbor, MI, USA; Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA. Electronic address: figueroc@med.umich.edu.
authors: C A
authors: CA
authors: Figueroa
mesh_terms: D000784:Aortic Dissection / Q000473:pathology / Q000503:physiopathology*; D001013:Aorta, Thoracic / Q000473:pathology / Q000503:physiopathology*; D017545:Aortic Aneurysm, Thoracic / Q000473:pathology / Q000503:physiopathology*; D062186:Arterial Pressure; D001783:Blood Flow Velocity; D003198:Computer Simulation; D004108:Dilatation, Pathologic; D018450:Disease Progression; D006439:Hemodynamics; D006801:Humans; D057446:Hydrodynamics; D008955:Models, Cardiovascular; D012039:Regional Blood Flow; D018570:Risk Assessment; D012307:Risk Factors
keywords: Aortic disease; Computational fluid dynamics; Computer model; False lumen; Hemodynamics; Predictors