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Title: Magnetic resonance imaging of the liver : T1 dynamics : confounders and modelling
Author: Mózes, Ferenc Emil
ISNI:       0000 0004 7966 2372
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2018
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Non-alcoholic fatty liver disease (NAFLD) is becoming increasingly prevalent in the world population. The current gold standard for diagnosing NAFLD, however, is still the liver needle biopsy, the evaluation of which can be subjective, lacks good reproducibility, and suffers from sampling bias. Multiparametric MRI exams comprising measurements of proton density fat fraction, hepatic iron concentration and liver T1 values, with iron- corrected T1 measurements correlating well with liver fibrosis and inflammation, have been suggested as a good non-invasive candidate to diagnose NAFLD. However, T1 values and T1 measurement methods are affected by more than just iron. The work presented in this thesis focussed on characterising the complex dependence of T1 values on hepatic lipid concentration when using the MOLLI methods. Dependent on field strength, magnetic field inhomogeneities, and sequence parameters (such as echo time and repetition time), the deleterious effects of fat can result in an artificial increase or decrease of measured liver T1s. An algorithm capable of reversing the effects of fat and frequency offsets was developed and tested in phantoms and in prospectively recruited participants by comparing the outcome of the algorithm to liver water T1 values measured using MR spectroscopy. Finally, two other influencing factors of liver T1 were also studied: liver glycogen concentration and body hydration status, both of which are subject to significant diurnal variation and their T1 effect has been shown earlier. A small study involving healthy vol- unteers undergoing metabolic interventions was conducted to determine the dependence of liver T1 values on liver glycogen concentration and hydration status.
Supervisor: Robson, Matthew ; Tunnicliffe, Elizabeth Sponsor: Medical Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Biophysical modelling ; Diagnostic imaging