Visualization of Regional Liver Function with Hepatobiliary Specific Contrast Agent Gd-EOB-DTPA

Liver biopsy is a very common, but invasive procedure for diagnosing liver disease. However, such a biopsy may result in severe complications and in some cases even death. Therefore, it would be highly desirable to develop a non-invasive method which would provide the same amount of information on staging of the disease and also the location of pathologies. This thesis describes the implementation of such a non-invasive method for visualizing and quantifying liver function by the combination of MRI (Magnetic Resonance Imaging), image reconstruction, and image analysis, and pharmacokinetic modeling. The first attempt involved automatic segmentation, functional clustering (k-means) and classification (kNN) of in-data (liver, spleen and blood vessel segments) in the pharmacokinetic model. However, after implementing and analyzing this method some important issues were identified and the image segmentation method was therefore revised. The segmentation method that was subsequently developed involved a semi-automatic procedure, based on a modified image forest transform (IFT). The data were then simulated and optimized using a pharmacokinetic model describing the pharmacokinetics of the liver specific contrast agent Gd-EOB-DTPA in the human body. The output from the modeling procedure was then further analyzed, using a least-squares method, in order to assess liver function by estimating the fractions of hepatocytes, extracellular extravascular space (EES) and blood plasma in each voxel of the image. The result were in fair agreement with literature values, although further analyses and developments will be required in order to validate and also to confirm the accuracy of the method.