Tumors have several important hallmarks; anomalous and heterogeneous behaviors of their vascular structures, and high angiogenesis and neovascularization. Tumor tissue presents high blood flow (F) and extraction ratio (E) of contrast molecules. Consequently there is growing interest in non invasive methods for characterizing changes in tumor vasculature. Toft's model has been extensively used in the past in order to calculate Ktrans maps which take into consideration both F and E. However, in this thesis we argue that for accurate tumor characterization we need a model able to compute both F and E in tissue plasma. This project has been developed as part of a larger project, working toward building a Clinical Decision Support System (CDSS): an interactive expert computer software, that helps doctors and other health professionals make decisions regarding patient treatment progress. Using the Gamma Capillary Transit Time (GCTT) pharmacokinetic model we calculate F and E separately in a more realistic framework; unlike other models it takes into account the heterogeneity of the tumor, which depends on parameter a-1. a-1 is the width of the distribution of the capillary transit times within a tissue voxel. In more detail, a-1 expresses the heterogeneity of tissue microcirculation and microvasculature. We studied 9 patients pathologically diagnosed with glioblastoma multiforme (GBM), a common malignant type of brain tumor. Several physiological parameters including the blood flow and extraction ratio distributions were calculated for each patient. Then we investigated if these parameters can characterize early the patients' responsiveness to current treatment; we assessed the classification potential based on the actual therapy outcome. To this end, we present a novel analysis framework which exploits the new parameter a-1 and organizes each voxel into four sub-region. Our results indicate that early characterization of response based on GCCT can be significantly improved by focusing on tumor voxels from a specific sub-region.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-116822 |
Date | January 2015 |
Creators | Kanli, Georgia |
Publisher | Stockholms universitet, Fysikum |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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