LCSR Seminar: Michael Miga “Computational Modeling for Enabling Therapy Guidance: Applications in Soft-Tissue”
Often within the clinical domain, the practical translation of computational modeling for therapeutic benefit is criticized as being idealized or not compatible with real clinical practice. As a result, the integration of these powerful approaches within the workflow of procedural medicine has been diminished. However, with continued improvements in computing and instrumentation, the ability to translate complex models from idealized prospective predictive roles to ones that are more integrated within therapeutic and novel imaging frameworks is becoming a rapid reality. Recent advances in biophysical model-embedded systems designed to enable novel soft-tissue surgical/interventional applications are an excellent example and will be explored in this talk. The paradigm suggested is that procedural precision medicine should not be limited to only the use of patient data (e.g. imaging, biomarkers, physiological variables, etc.) for staging and conventional guidance, but, in addition, it should also serve as a patient-specific scaffold that when combined with advanced computation and instrumentation can add new enhanced capabilities to therapeutic guidance and delivery. This is a paradigm that challenges convention because it advocates a more collaborative intraoperative patient care environment with diverse teams of engineers, scientists, and physicians working together to best meet therapeutic procedural goals.
Short Biography: Michael I. Miga, Ph.D. received his B.S. and M.S. from the University of Rhode Island in Mechanical Engineering and Applied Mechanics in 1992, 1994, respectively. He received his Ph.D. from Dartmouth College in Engineering with Biomedical Specialization in 1998. The focus of his doctoral research was on computational biomechanical models of the brain for surgical applications. He stayed on for a post-doctoral training experience continuing that work and initiating projects in areas of inverse problems (elastography and epileptogenic source localization). He joined the faculty at Vanderbilt University in the Spring of 2001 and is currently Vanderbilt’s Harvie Branscomb Professor. He is a Professor of Biomedical Engineering with appointments in Radiology and Radiological Sciences, and Neurological Surgery. He is director of the Biomedical Modeling Laboratory, co-founder of the Vanderbilt Institute for Surgery and Engineering (VISE, www.vanderbilt.edu/vise ). He was a co-inventor of the first FDA approved image-guided liver surgery system. He is currently PI on several NIH research grants concerned with model-enhanced image-guided brain, liver, kidney, and breast surgery. He is also involved in modeling efforts for predictive forecasting in neoadjuvant chemotherapy outcomes for breast cancer, and differentiating brain tumor radio-necrosis from recurrence in radiosurgery. In addition, he recently created a novel NIH-T32 training program focused at training engineers to create novel technology platforms for treatment and discovery within surgery and intervention. Dr. Miga is also an American Institute for Medical and Biological Engineering Fellow and an Associate Editor for the Journal of Medical Imaging. He has also served extensively on NIH panels to include being a former charter member of the Biomedical Imaging Technology (BMIT) study section, and recently taking on a new charter member role with the Bioengineering, Technology, and Surgical Sciences (BTSS) study section. His research interests are in computational modeling for surgical and interventional applications, inverse problems in therapeutics and imaging, and image-guided surgery.