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Dr. Kogan is an Assistant Professor with a research focus on imaging of musculoskeletal function and disease. He earned his PhD in Bioengineering at the University of Pennsylvania in 2013 during which he received a HHMI interfaces fellowship and completed the pre-clinical academic curriculum at the UPenn School of Medicine. Afterwards, he did his postdoctoral fellowship in the Radiology Department at Stanford. His group is focused on the development of early markers of disease with novel imaging methods, and the translation of these methods to produce actionable information to impact patient outcomes. He has extensive experience with cutting-edge imaging technologies including multimodal PET-MRI systems, novel quantitative imaging biomarkers and Ultra-high magnetic field (7T). In addition to research, Dr. Kogan has taught lectures in numerous courses at Stanford. He is a junior fellow of the International Society for Magnetic Resonance in Medicine and a member of Council of Early Investigators in Imaging of the Academy for Radiology & Biomedical Imaging Research.
My research is focused on the development and clinical translation of novel quantitative and molecularly specific imaging technologies geared toward detection of disease at the earliest causative stages. Specifically, I am motivated to study the causes and treatment of osteoarthritis (OA) and other musculoskeletal disorders, which have a large physical and financial impact but remain poorly understood. Research projects include development of (1) novel PET and MRI imaging methods to study early tissue changes at the cellular and molecular level, (2) functional imaging methods to study important relationships between mechanics, physiology and tissue microstructure, (3) rapid, comprehensive and quantitative MRI methods for early, low-cost, and precise detection of musculoskeletal disease.
Use of PET/MR Imaging in Chronic Pain
The investigators are studying the ability of PET/MR imaging (using the PET tracer [18F]FDG)
to objectively identify and characterize pain generators in patients suffering from chronic
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