| Popis: |
Magnetic resonance imaging (MRI) is a non-invasive, effective method for the comprehensive evaluation of disease in the human body. However, abdominal MRI presents many challenges, including the need for a high spatial resolution, large volumetric coverage, and potential for artifacts from respiratory motion. Conventional 3D abdominal quantitative mapping techniques still require breath-holds to yield images free of motion artifact, and the entire dataset can be corrupted if the subject resumes breathing during the acquisition. Furthermore, in many cases, it is not possible to collect “ground truth” images in vivo, simply because standard data collection techniques are too slow to capture images with the resolution and/or coverage of these methods. Magnetic resonance fingerprinting (MRF) is a novel approach that allows simultaneous generation of quantitative maps of multiple tissue parameters and potentially enables the development of standardized imaging biomarkers. However, in order to translate and use MRF for the generation of meaningful imaging biomarkers, the measurement of the mapped quantitative tissue properties must be repeatable and reproducible. Four main projects supporting the improvement of repeatability and reproducibility of abdominal imaging will be described in this dissertation. First, a 4D numerical abdominal phantom which includes the modeling of T1 and T2 relaxation times, proton density fat fraction, perfusion, and diffusion, as well as respiratory motion for the evaluation and comparison of acquisition and reconstruction techniques is presented. Second, a new free breathing method for 3D abdominal T1 mapping is presented. Third, a Gadgetron-based online MRF quantification framework that enables the employment of the technology in a clinical setting is presented. The fourth project presents findings from a multicenter study of repeatability and reproducibility of T1 and T2 maps generated using MRF. |
