Computational Analysis of Anastomotic Angles by Blood Flow Conditions in Side-to-End Radio-Cephalic Fistulae Used in Hemodialysis

• 作者: Carlos Cristiano H. Borges Janaína de Andrade Silva José Karam-Filho
• 来源期刊: 生物医学工程(英文)
• 学科: 医学
• 关键词: HEMODIALYSIS Wall Shear Stress STAGNATION FLOW Finite Volume Method Blood FLOW Large Vessels
• 年，卷（期）: swyxgcyw_2015,（3）
• 页码范围: 131-141
• 页数: 11页
• 分类号: R73

摘要

Chronic renal failure is a disease that affects a considerable population percentage that requires the hemodialysis procedure which is a blood filtration. This process is extremely stressful in many cases for the patient, because there is a continuous degradation of vessels and fistulae susceptible to this process due to the alterations of the stress at the blood vessel walls and flow patterns, leading to diseases such as intimal hyperplasia and consequent stenosis. Experimental in vivo researches in this area are very difficult to perform. In this sense computational models become interesting non invasive options to understand what happens to the blood in non viscometric geometries. In this work, we analyse blood flow, through computational modeling, in arteriovenous fistulae used in hemodialysis, using geometries with dimensions close to real ones. Discretization of the governing equations was made through a finite volume technique with the PISO—Pressure Implicit with Splitting of Operators—algorithm, using as a basis the OpenFOAM software platform. Large vessel Newtonian fluid model was used to analyze six possible anastomotic angles (20。, 25。, 30。, 35。, 40。, 45。). To analyze the possibility of stenosis formation caused by hyperplasia, results for wall shear stress, oscillatory shear index (OSI), velocity and local circulation fields were obtained, showing that higher angles presented more secondary flows and larger extensions of stagnation regions near the critical areas of the junctions. Moreover, a range around 25。was identified to be the most suitable choice for clinical applications, minimizing possibility of diseases.