Norbert Pelc

Medical imaging has made enormous strides in recent decades. In clinical medicine, imaging plays an increasingly important role in patient care. A recent study found that internists rank the development of computed tomography (CT) and magnetic resonance imaging (MRI), together, as the most important innovation in medicine (Health Affairs, Vol 20, p. 30, 2001). At the same time, experts in a completely different scientific field, the National Academy of Engineering, ranks the development of imaging as one of the top 20 greatest engineering achievements of the 20th century (www.greatachievements.org), amazingly at a rank higher than that of household appliances and nuclear technology. Imaging is also taking on an increasing role in research, improving our understanding of both normal and diseased states and as a surrogate endpoint in the evaluation of therapies. Imaging allows serial studies in the same individual, thereby increasing statistical power and reducing the number of subjects needed in a study. Imaging is also a powerful tool to guide minimally invasive therapies.

The effectiveness of imaging and the powerful impact of visual images have led to a major increase in the utilization of this strategy, a trend that will continue but will evolve in coming years. Further advances will lead to improved detection, localization, and characterization of disease which should enable more accurate selection of optimized therapies for individual subjects (personalized medicine) as well as treatments that are more effective, less expensive, and less traumatic. Imaging will also play an increasingly important role in the challenges facing biomedical research.

There are many imaging “modalities”, each acquiring data using physical mechanisms such as x-ray transmission, nuclear magnetic resonance, acoustic or optical properties, and signals from radioactive tracers. Optimal design and utilization of each requires an appreciation of the underlying physical phenomena. Each modality uses sensors to detect signals and mathematical methods to covert the measured signals to images. Additional image processing methods are used to extract physiological information from the images.

My own interests center on the physics, engineering and mathematics of medical imaging. While I have worked on many imaging modalities over the past decades, my current projects are focused on computed tomography, digital x-ray imaging, and hybrid multimodality systems. The largest project currently underway is the development of Inverse Geometry Computed Tomography (IGCT), a new CT imaging architecture that should allow volumetric imaging with outstanding image quality and lower radiation dose. The work involves research into new components, sampling strategies, and image reconstruction methods, as well as methods to characterize the performance of imaging systems. We are also interested in energy-dependent CT imaging for tissue characterization and improved efficiency.

Currently, image guided therapy is typically performed using real-time guidance from a single modality, most commonly x-ray fluoroscopy. I believe that many procedures would benefit if the physician, during the procedure, could choose from a number of imaging technologies (e.g., x-ray fluoroscopy, MRI, PET) and with minimal impact on the patient. I am interested in the development of “hybrid” platforms that would provide such access. Development of such platforms requires careful attention to allow each modality to provide its unique type of information while not interfering with the other systems.

In addition to these technical projects, I am also interested in the development of new clinical and research applications of medical imaging. This is highly interdisciplinary research, incorporating not only the latest imaging technology but also fundamental appreciation of anatomy and pathophysiology.