Liver Fat and Iron Quantification MRI

This study will include on-going technical development work for the non-invasive diagnosis of liver fat or iron accumulation and other abnormalities. MRI is a non-invasive imaging technique with no known side effects. The study will utilize imaging equipment that is used routinely in numerous hospitals and clinics around the world. The project seeks to address optimization of the imaging methodology at 1.5 Tesla and 3.0 Tesla in the liver and abdomen in order to improve clinical evaluation and care of future patients. Non contrast MRI studies will be performed in normal healthy subjects. In addition, the study will include subjects with confirmed disease or who have suspicion for disease, and are undergoing contrast or non-contrast MR imaging as part of their standard of care. Up to sixty-five (65) male or female subjects eighteen years of age and older will be studied in total (number includes healthy subjects and non-healthy subjects). Currently, clinical MRI exams are of adequate spatial and temporal resolution, sufficient quantitative accuracy, and acceptable exam duration, but improvements in each of these areas would benefit the care of future patients. For example, improvements in spatial and temporal resolution may confer greater conspicuity of disease and shortening the exam duration can be expected to improve patient acceptance and minimize motion artifacts. The study explores innovative ideas about ways to improve MRI exams to have impact in all three of these areas. Current MRI techniques for fat and iron quantification in the liver and abdomen are challenged by respiratory and organ motion. As a result, imaging parameters (coverage, resolution, etc) and TE (echo time) selection for fat/iron quantification are compromised to accommodate a short breath-held 2D or 3D scan, which can still be affected by motion artifacts and even unachievable for patients with limited breath-holding capability. Therefore, the study aims to achieve robust free-breathing fat/iron quantification in the liver and abdomen using innovative MRI techniques and algorithms.