The Magnetic Resonance Imaging (MRI) Technology program is dedicated to the development and implementation of advanced MRI techniques for disease diagnosis and image guidance. The program focuses on new technologies that can broaden the use of MRI. Specifically, the aim is to leverage advanced acquisition and reconstruction techniques to improve imaging speed (real-time imaging), motion robustness (registration and correction), quantitation (parametric mapping or flow), and clinical workflow.
Two example areas of interest are pediatric imaging and interventional image guidance. MRI is an exciting imaging modality because it provides excellent soft tissue contrast and uses no ionizing radiation. It is an excellent choice for imaging children and for image guidance in lengthy interventional or surgical procedures where the long exposure to alternative imaging techniques, such as X-ray imaging, would pose a risk to the patient. However, MRI is slow and consequently exams are long and it is difficult for young children to remain still during the exam. Many MRI exams of young children are done under general anesthesia. General anesthesia is associated with some risk, increased cost, and discomfort. To enable more pediatric MRI exams to be carried out without general anesthesia faster real-time MRI is needed.
Catheter based interventions are traditionally done under X-ray fluoroscopy guidance. Some of the procedures are quite long and involves a significant radiation dose. Furthermore, X-ray fluoroscopy has relatively poor soft tissue contrast characteristic. MRI is an interesting possible alternative for interventional procedures, but faster real-time imaging methods are needed in order to guide an intervention. Additionally there is a need for better tools for interacting with the imaging system, i.e. controlling the position of imaging slices, etc.
In addition to developing specific solutions to such applications, the MRI Technology program invests time and energy in developing framework infrastructure components that can benefit other laboratories working on similar problems or on MRI in general. As an example, the program has developed a modular, open source medical image reconstruction framework called the Gadgetron (http://gadgetron.sourceforge.net) and is taking a leading role in defining a community standard for sharing MRI raw data across vendor platforms. These efforts are part of a commitment to making MRI research vendor independent and reproducible.
Dr. Michael S. Hansen is a biomedical engineer with a Ph.D. from University of Aarhus, Denmark. He works at the NHLBI, where he focuses on fast MRI techniques for real-time imaging and interventional procedures. His particular areas of interest are fast pulse sequences, non-Cartesian imaging, real-time reconstruction, GPU based reconstruction, and motion correction.
Dr. Hansen obtained his Ph.D. from Aarhus University, Denmark on the topic of fast dynamic imaging with special focus on cardiac imaging and image reconstruction. During his training, he spent time at the ETH in Zurich, Philips Research in Hamburg, King’s College London, University College of London, and Great Ormond Street Hospital for Children in London. Before coming to the NIH, he also worked as a Laboratory head at Novartis Institutes for BioMedical Research in Cambridge, MA.