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- Karlsson, Markus, 1990-
(author)
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Non-Invasive Characterization of Liver Disease : By Multimodal Quantitative Magnetic Resonance
- 2019
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Doctoral thesis (other academic/artistic)abstract
- There is a large and unmet need for diagnostic tool that can be used to characterize chronic liver diseases (CLD). In the earlier stages of CLD, much of the diagnostics involves performing biopsies, which are evaluated by a histopathologist for the presence of e.g. fat, iron, inflammation, and fibrosis. Performing biopsies, however, have two downsides: i) biopsies are invasive and carries a small but non-negligible risk for serious complications, ii) biopsies only represents a tiny portion of the liver and are thus prone to sampling error. Moreover, in the later stages of CLD, when the disease has progressed far enough, the ability of the liver to perform its basic function will be compromised. In this stage, there is a need for better methods for accurately measuring liver function. Additionally, measures of liver function can also be used when developing new drugs, as biomarkers for drug-induced liver injury (DILI), which is a serious drug-safety issue.Magnetic resonance imaging (MRI) is a non-invasive medical imaging modality, which have shown much promise with regards to characterizing liver disease in all of the abovementioned aspects. The aim of this PhD project was to develop and validate MR-based methods that can be used to non-invasively characterize liver disease.Paper I investigated if R2* mapping, a MR-method for measuring liver iron content, can be confounded by liver fat. The results show fat does affect R2*. The conclusion was therefore that fat must be taken into account when measuring small amounts of liver iron, as a small increase in R2* could be due to either small amounts of iron or large amounts of fat.Paper II examined whether T1 mapping, which is another MR-method, can be used for staging liver fibrosis. The results of previous research have been mixed; some studies have been very promising, whereas other studies have been less promising. Unfortunately, the results in Paper II belongs to the less promising studies.Paper III focused on measuring liver function by dynamic contrast-enhanced MRI (DCEMRI) using a liver specific contrast agent, which is taken up the hepatocytes and excreted to the bile. The purpose of the paper was to extend and validate a method for estimating uptake and efflux rates of the contrast agent. The method had previously only been applied in health volunteers. Paper II showed that the method can be applied to CLD patients and that the uptake of the contrast agent is lower in patients with advanced fibrosis.Paper IV also used studied liver function with DCE-MRI in patients with primary sclerosing cholangitis (PSC). PSC is a CLD where the bile ducts are attacked by the immune system. When diagnosing PSC patients, it is common to use magnetic resonance cholangiopancreatography (MRCP), which is a method for imaging the bile ducts. Paper IV examined if there was any correlation between number and severity of the morphological changes, seen on MRCP, and measures of liver function derived using DCE-MRI. However, the results showed no such correlation. The conclusion was that the results indicates that MRCP should not be used to predict parenchymal function.Paper V developed a method for translating DCE-MRI liver function parameters from rats to humans. This translation could be of value when developing new drugs, as a tool for predicting which drugs might cause drug-induced liver injury.In summary, this thesis has shown that multimodal quantitative MR has a bright future for characterizing liver disease from a range of different aspects.
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| 2. |
- Garpebring, Anders, 1980-
(author)
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Contributions to quantitative dynamic contrast-enhanced MRI
- 2011
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Doctoral thesis (other academic/artistic)abstract
- Background: Dynamic contrast-enhanced MRI (DCE-MRI) has the potential to produce images of physiological quantities such as blood flow, blood vessel volume fraction, and blood vessel permeability. Such information is highly valuable, e.g., in oncology. The focus of this work was to improve the quantitative aspects of DCE-MRI in terms of better understanding of error sources and their effect on estimated physiological quantities. Methods: Firstly, a novel parameter estimation algorithm was developed to overcome a problem with sensitivity to the initial guess in parameter estimation with a specific pharmacokinetic model. Secondly, the accuracy of the arterial input function (AIF), i.e., the estimated arterial blood contrast agent concentration, was evaluated in a phantom environment for a standard magnitude-based AIF method commonly used in vivo. The accuracy was also evaluated in vivo for a phase-based method that has previously shown very promising results in phantoms and in animal studies. Finally, a method was developed for estimation of uncertainties in the estimated physiological quantities. Results: The new parameter estimation algorithm enabled significantly faster parameter estimation, thus making it more feasible to obtain blood flow and permeability maps from a DCE-MRI study. The evaluation of the AIF measurements revealed that inflow effects and non-ideal radiofrequency spoiling seriously degrade magnitude-based AIFs and that proper slice placement and improved signal models can reduce this effect. It was also shown that phase-based AIFs can be a feasible alternative provided that the observed difficulties in quantifying low concentrations can be resolved. The uncertainty estimation method was able to accurately quantify how a variety of different errors propagate to uncertainty in the estimated physiological quantities. Conclusion: This work contributes to a better understanding of parameter estimation and AIF quantification in DCE-MRI. The proposed uncertainty estimation method can be used to efficiently calculate uncertainties in the parametric maps obtained in DCE-MRI.
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