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The fundamental goal of medical research is the discovery and implementation of novel and more effective ways of delivering patient care. This goal is realized first by a discovery of an invention at the laboratory bench or by the formulation of a new clinical application of an existing invention, and second by evaluating its safety and efficacy in patients. The second part is called translational or clinical research and the knowledge derived from it provides the evidence for developing "best clinical practices." The goal is ultimately accomplished when these practices are integrated into the clinical care delivery system through publication, policy and education.
In medical imaging, the foremost modern inventions are new modalities for examining the body (e.g., multi-slice CT, high-field MRI), digital capabilities for all imaging modalities, and the development of picture archiving and communications systems (PACS) and radiology information systems (RIS). Today's clinical research in medical imaging therefore is the assessment of clinical applications resulting from these advances. As with all forms of progress, however, new problems need solutions. One consequence is that new applications are introduced at an alarming rate such that they are used clinically without sufficient proof of efficacy. Another difficulty is the enormous amount of images produced daily. This deluge of digital data requires innovative solutions for identifying the means for managing the data for clinics, teaching and research. Whereas PACS and RIS are ideally suited for collecting, archiving and retrieving information (including medical images) for clinical use, these databases do not provide the same functionality for teaching or research. Additionally, diagnostic imagers now are expected to look at thousands of images per day (versus tens or hundreds). As such, there is a need to identify and evaluate new search paradigms to improve efficiency and accuracy of image interpretation (e.g., 3D reconstructions, automated computer analysis).
Arising from these challenges, my scholarship focuses of two areas in veterinary imaging: 1) developing data-management resources for teaching and research and 2) using epidemiological methods for assessing the efficacy of new clinical applications and interpretation models for contemporary imaging techniques. I am particularly interested in CT and MRI as an imaging modality and diseases of the head, neck and spine (particularly neuroimaging).
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