<p>Positron Emission Tomography, PET, is a noninvasive medical imaging technique to get functional information of the kinetics of radioactive compound injected in the body. The data used in this thesis comes from a total of five H₂¹⁵O PET studies of one patient. This was done in order to study the blood flow in liver metastasis of the patient, before and after treatment.</p><p>A one compartment model was used to do the ROI based analyses. With a least square method in Matlab the unknown parameters in the model, such as the kinetic rate constants, the dispersion and the fraction of blood in the tissue, was extracted. Also a brief analysis of different parts of the metastases, edge and center, was done to see the variations within the metastases. The results show some increase of the blood flow after the treatment, and two of the three studied metastases showed a distinct difference of the activity in the center versus the edge. Given in the thesis are also some basic PET and compartmental modeling theory.</p> / <p>Positronemissionstomografi, PET, är en icke-invasiv medicinsk bildteknik för att få funktionell information om kinetiken av radioaktiva föreningar injicerade i kroppen. Det data som används i denna kandidatuppsats kommer från totalt fem H₂¹⁵O PET-studier av en patient. Detta gjordes för att studera blodflödet i levermetastaser hos patienten före och efter behandling.</p><p>En 1-kompartmentmodell användes för att göra ROI-baserade analyser. Med en minsta kvadrat-metod i Matlab kunde de okända parametrarna i modellen, såsom den kinetiska hastighetskonstanten, spridningen och andelen blod i vävnaden, fås ut. En kort analys gjordes också av olika delar av metastaserna, kanten och mitten, för att se variationerna inuti metastaserna. Resultaten visar en viss ökning av blodflödet efter behandlingen, och två av de tre studerade metastaser visade en tydlig skillnad av aktiviteten i mitten jämfört med kanten. I rapporten ges också grundläggande teori om bland annat PET och kompartmentmodellering.</p>

Positron Emission Tomography, PET, is a noninvasive medical imaging technique to get functional information of the kinetics of radioactive compound injected in the body. The data used in this thesis comes from a total of five H215O PET studies of one patient. This was done in order to study the blood flow in liver metastasis of the patient, before and after treatment. A one compartment model was used to do the ROI based analyses. With a least square method in Matlab the unknown parameters in the model, such as the kinetic rate constants, the dispersion and the fraction of blood in the tissue, was extracted. Also a brief analysis of different parts of the metastases, edge and center, was done to see the variations within the metastases. The results show some increase of the blood flow after the treatment, and two of the three studied metastases showed a distinct difference of the activity in the center versus the edge. Given in the thesis are also some basic PET and compartmental modeling theory. / Positronemissionstomografi, PET, är en icke-invasiv medicinsk bildteknik för att få funktionell information om kinetiken av radioaktiva föreningar injicerade i kroppen. Det data som används i denna kandidatuppsats kommer från totalt fem H215O PET-studier av en patient. Detta gjordes för att studera blodflödet i levermetastaser hos patienten före och efter behandling. En 1-kompartmentmodell användes för att göra ROI-baserade analyser. Med en minsta kvadrat-metod i Matlab kunde de okända parametrarna i modellen, såsom den kinetiska hastighetskonstanten, spridningen och andelen blod i vävnaden, fås ut. En kort analys gjordes också av olika delar av metastaserna, kanten och mitten, för att se variationerna inuti metastaserna. Resultaten visar en viss ökning av blodflödet efter behandlingen, och två av de tre studerade metastaser visade en tydlig skillnad av aktiviteten i mitten jämfört med kanten. I rapporten ges också grundläggande teori om bland annat PET och kompartmentmodellering.

Indiana University-Purdue University Indianapolis (IUPUI) / Atherosclerotic lesions of human beings are common diagnosed in regions of arte- rial branching and curvature. The prevalence of atherosclerosis is usually associated with hardening and ballooning of aortic wall surfaces because of narrowing of flow path by the deposition of fatty materials, platelets and influx of plasma through in- timal wall of Aorta. High Wall Shear Stress (WSS) is proved to be the main cause behind all these aortic diseases by physicians and researchers. Due to the fact that the atherosclerotic regions are associated with complex blood flow patterns, it has believed that hemodynamics and fluid-structure interaction play important roles in regulating atherogenesis. As one of the most complex flow situations found in cardio- vascular system due to the strong curvature effects, irregular geometry, tapering and branching, and twisting, theoretical prediction and in vivo quantitative experimental data regarding to the complex blood flow dynamics are substantial paucity. In recent years, computational fluid dynamics (CFD) has emerged as a popular research tool to study the characteristics of aortic flow and aim to enhance the understanding of the underlying physics behind arteriosclerosis. In this research, we study the hemo- dynamics and flow-vessel interaction in patient specific normal (healthy) and dilated (diseased) aortas using Ansys-Fluent and Ansys-Workbench. The computation con- sists of three parts: segmentation of arterial geometry for the CFD simulation from computed tomography (CT) scanning data using MIMICS; finite volume simulation of hemodynamics of steady and pulsatile flow using Ansys-Fluent; an attempt to perform the Fluid Structure Simulation of the normal aorta using Ansys-Workbench. Instead of neglecting the branching or smoothing out the wall for simplification as a lot of similar computation in literature, we use the exact aortic geometry. Segmen- tation from real time CT images from two patients, one young and another old to represent healthy and diseased aorta respectively, is on MIMICS. The MIMICS seg- mentation operation includes: first cropping the required part of aorta from CT dicom data of the whole chest, masking of the aorta from coronal, axial and saggital views of the same to extract the exact 3D geometry of the aorta. Next step was to perform surface improvement using MIMICS 3-matic module to repair for holes, noise shells and overlapping triangles to create a good quality surface of the geometry. A hexahe- dral volume mesh was created in T-Grid. Since T-grid cannot recognize the geometry format created by MIMICS 3-matic; the required step geometry file was created in Pro-Engineer. After the meshing operation is performed, the mesh is exported to Ansys Fluent to perform the required fluid simulation imposing adequate boundary conditions accordingly. Two types of study are performed for hemodynamics. First is a steady flow driven by specified parabolic velocity at inlet. We captured the flow feature such as skewness of velocity around the aortic arch regions and vortices pairs, which are in good agreement with open data in literature. Second is a pulsatile flow. Two pulsatile velocity profiles are imposed at the inlet of healthy and diseased aorta respectively. The pulsatile analysis was accomplished for peak systolic, mid systolic and diastolic phase of the entire cardiac cycle. During peak systole and mid-systole, high WSS was found at the aortic branch roots and arch regions and diastole resulted in flow reversals and low WSS values due to small aortic inflow. In brief, areas of sudden geometry change, i.e. the branch roots and irregular surfaces of the geom- etry experience more WSS. Also it was found that dilated aorta has more sporadic nature of WSS in different regions than normal aorta which displays a more uniform WSS distribution all over the aorta surface. Fluid-Structure Interaction simulation is performed on Ansys-WorkBench through the coupling of fluid dynamics and solid mechanics. Focus is on the maximum displacement and equivalent stress to find out the future failure regions for the peak velocity of the cardiac cycle.