Fat-Referenced MRI : Quantitative MRI for Tissue Characterization and Volume Measurement

The amount and distribution of adipose and lean tissues has been shown to be predictive of mortality and morbidity in metabolic disease. Traditionally these risks are assessed by anthropometric measurements based on weight, length, girths or the body mass index (BMI). These measurements are predictive of risks on a population level, where a too low or a too high BMI indicates an increased risk of both mortality and morbidity. However, today a large part of the world’s population belongs to a group with an elevated risk according to BMI, many of which will live long and healthy lives. Thus, better instruments are needed to properly direct health-care resources to those who need it the most. Medical imaging method can go beyond anthropometrics. Tomographic modalities, such as magnetic resonance imaging (MRI), can measure how we have stored fat in and around organs. These measurements can eventually lead to better individual risk predictions. For instance, a tendency to store fat as visceral adipose tissue (VAT) is associated with an increased risk of diabetes type 2, cardio-vascular disease, liver disease and certain types of cancer. Furthermore, liver fat is associated with liver disease, diabetes type 2. Brown adipose tissue (BAT), is another emerging component of body-composition analysis. While the normal white adipose tissue stores fat, BAT burns energy to produce heat. This unique property makes BAT highly interesting, from a metabolic point of view. Magnetic resonance imaging can both accurately and safely measure internal adipose tissue compartments, and the fat infiltration of organs. Which is why MRI is often considered the reference method for non-invasive body-composition analysis. The two major challenges of MRI based body-composition analysis are, the between-scanner reproducibility and a cost-effective analysis of the images. This thesis presents a complete implementation of fat-referenced MRI, a technique that produces quantitative images that can increase both inter-scanner and automation of the ...