posted on 2022-03-28, 17:51authored byKaavya Karunanithi
The vasculature that supplies blood to the brain is tightly regulated and any abnormalities in its structure; aneurysms and Moyamoya disease (MMD) cause a multitude of complications including but not limited to Sub-arachnoid hemorrhage (SAH), transient ischemic attacks(TIA), stenosis etc. The blood flow dynamics of these vascular disorders plays a critical role in the origin and development of the disease. Computational Fluid Dynamic (CFD) techniques help us understand the underlying mechanism that promotes disease prognosis. In this study we aim to computationally analyze the hemodynamic parameters that will help assess the treatment outcome of cerebrovascular diseases such as intracranial aneurysms and MMD.
In our initial study we attempted to understand the relationship between the free segment of Flow Diverter (FD)’s angle and the Metal Coverage Rate (MCR) across the aneurysm neck and its influence on flow reduction and Energy Loss (EL). Our results from two patient specific aneurysms; A (Aspect Ratio=3.1) and B (Aspect Ratio=2.9) with three FD configurations each (0°, 10° and 25°), suggested that an optimal MCR in the range of 50-60% across the aneurysm neck brings about maximum flow reduction inside the aneurysm facilitating its occlusion. It also yielded higher percentage reduction in Energy Loss when compared to the no-stent case indicating a lower risk of rupture compared to other stent configurations.
The second part of the dissertation deals with the application of CFD principles to understand the hemodynamics of scarcely known Moyamoya disease, which is caused due to progressive occlusion of the Internal Carotid Arteries (ICA). A total of 34 adult MMD patients; 8-treated bilaterally with indirect EDAS revascularization, 26-treated unilaterally with combined direct STA-MCA bypass and indirect EDMS revascularization (18-incomplete Circle of Willis, 8-complete Circle of Willis), were computationally analyzed to identify a novel hemodynamic parameter, Pressure Drop Index (PDI) which correlated with Matsushima’s angiographic grading (A-Significant improvement; B-Limited Improvement; C-No Improvement) across all patients. We also sought to evaluate the characteristic remodeling of ICA post-surgery in the18 patients (incomplete CoW) who have undergone combined revascularization surgery to illustrate how vascular tortuosity and Wall Shear stress (WSS) affect treatment outcome.Negligible changes in WSS and a decrease in vascular tortuosity was found in patients classified A accompanied with a decrease in surgical ICA diameter. Patients from group C had an increase in wall shear stress values with severe stenotic regions developing in surgical ICA.
The results of our studies have established that parameters such as Metal Coverage Rate and Pressure Drop Index play a vital role in influencing the progression of cerebrovascular disorders. Work towards quantifying the statistical significance of the parameters of interest is currently underway. This will help us establish CFD as a non-invasive, complementary diagnostic tool to aide clinicians in the treatment planning and management of intracranial aneurysms and MMD.
History
Table of Contents
Chapter 1. Cerebrovascular diseases : an introduction -- Chapter 2. Role of Computational Fluid Dynamics (CFD) in the management of cerebrovascular diseases -- Chapter 3. The influence of flow diverter’s angle of curvature across the aneurysm neck on its hemodynamics -- Chapter 4. Identification of a hemodynamic parameter for assessing treatment outcome of EDAS in Moyamoya disease -- Chapter 5. Assessing surgical treatment outcome following superficial temporal artery to middle cerebral artery bypass based on Computational Hemodynamic Analysis -- Chapter 6. Hemodynamic assessment of surgical treatment outcome on Moyamoya disease patients with complete circle of Willis following revascularization surgery -- Chapter 7. Discussion and conclusion.
Notes
Empirical thesis.
Bibliography: pages 138-167
Awarding Institution
Macquarie University
Degree Type
Thesis PhD
Degree
PhD, Macquarie University, Faculty of Medicine and Health Sciences, Department of Biomedical Sciences