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.
It is well-established that surgical care directly affects patients’ quality of life, and that poor quality surgical care increases the risk of death and other severe complications. The process of ensuring high quality surgical care begins with educating, efficiently training, and credentialing competent surgeons. While there is currently no global consensus for surgical competency, most definitions refer to the level of skill required to safely perform a particular procedure. Most tend to think of surgical competency as relating to both technical and non-technical skill as well as judgment during a procedure, and so being able to assess and, more importantly, improve on each of these aspects ultimately drives the quality of surgical care that exists throughout the healthcare system. This talk will focus on the use of current technology available to train surgeons and explore new research strategies in computer science to improve training.
Shameema Sikder, M.D., is an assistant professor of ophthalmology and founding medical director of the Wilmer Eye Institute at Bethesda. She specializes in corneal disorders, including Fuchs dystrophy and keratoconus; complex cataracts and external eye diseases. Dr. Sikder’s clinical interests include surgical treatments for corneal diseases. Dr. Sikder is also director of the Center of Excellence for Ophthalmic Surgical Education and Training (OphSET) at the Johns Hopkins Hospital. She has a particular interest in surgical education and is working on a technologies that could be implemented at the international level to improve the level of ophthalmic surgical care. Dr. Sikder received her M.D. degree from the University of Arizona. She completed her ophthalmology residency at the Wilmer Eye Institute at Johns Hopkins and fellowship in cornea and refractive disease at the Moran Eye Institute in Salt Lake City, Utah, where she received the Claes Dohlman Fellow of the Year Award, recognizing the most distinguished cornea fellow in the nation. Dr. Sikder returned to Wilmer in 2011 and served as assistant chief of service (chief resident) and associate director of ocular trauma.
Last Seminar of the Semester.
Locomotion and perception are a common thread between robotics and biology. Understanding these phenomena at a mechanical level involves nonlinear dynamics and the coordination of many degrees of freedom. In this talk, I will discuss geometric approaches to organizing this information in two problem domains: Undulatory locomotion of snakes and swimmers, and vibration propagation in spider webs.
In the first section, I will discuss how differential geometry and Lie group theory provide insight into the locomotion of undulating systems through a vocabulary of lengths, areas, and curvatures. In particular, a tool called the *Lie bracket* combines these geometric concepts to describe the effects of cyclic changes in the locomotor’s shape, such as the gaits used by swimming or crawling systems. Building on these results, I will demonstrate that the geometric techniques are useful beyond the “clean” ideal systems on which they have traditionally been developed, and can provide insight into the motion of systems with considerably more complex dynamics, such as locomotors in granular media.
In the second section, I will turn my attention to vibration propagation through spiders’ webs. Due to poor eyesight, many spiders rely on web vibrations for situational awareness. Web-borne vibrations are used to determine the location of prey, predators, and potential mates. The influence of web geometry and composition on web vibrations is important for understanding spider’s behavior and ecology. Past studies on web vibrations have experimentally measured the frequency response of web geometries by removing threads from existing webs. The full influence of web structure and tension distribution on vibration transmission; however, has not been addressed in prior work. We have constructed physical artificial webs and computer models to better understand the effect of web structure on vibration transmission. These models provide insight into the propagation of vibrations through the webs, the frequency response of the bare web, and the influence of the spider’s mass and stiffness on the vibration transmission patterns.
Ross L. Hatton is an Assistant Professor of Robotics and Mechanical Engineering at Oregon State University, where he directs the Laboratory for Robotics and Applied Mechanics. He received PhD and MS degrees in Mechanical Engineering from Carnegie Mellon University, following an SB in the same from Massachusetts Institute of Technology. His research focuses on understanding the fundamental mechanics of locomotion and sensory perception, making advances in mathematical theory accessible to an engineering audience, and on finding abstractions that facilitate human control of unconventional locomotors. Hatton’s group also works with local industry to transfer modern developments in robotics from the lab to the factory or commercial production. Dr. Hatton is the recipient of a 2017 NSF CAREER award to further his work in the dynamics of locomotion.
Microsurgical resection, endovascular means and stereotactic radiotherapy are the major treatments of cerebral arteriovenous malformations (AVM) and each method has its own limitations. Preoperative fractionation embolization can reduce bleeding and surgical risk, however, patients have to experience repeated pain due to the repeated treatments, and face the risk of rupture of AVM during treatment. The purpose of this study is to evaluate the advantages and safety of combined surgical and endovascular. One hundred and ninety-five patients were successfully completed with combination of endovascular therapy and craniotomy in the hybrid operating room from February 2016 to July 2017 in Beijing Tiantan Hospital. We get our initial experience of combined surgical and endovascular procedures in hybrid operating room (OR) in the treatment of cerebral AVM. Hybrid operation can improve the ratio of total resection and efficacy of surgery of cerebral AVM, and reduce post-operative complications, medical costs and the repeated pain due to the repeated DSA examinations.
Professor Jizong Zhao, Academician of the Chinese Academy of Sciences. Prof. Zhao is the director, doctoral supervisor, and Chief of Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University. Prof. Zhao also serves as the Member of the Expert Group of the Academic Degrees Committee of the State Council, Director of China National Clinical Research Center for Neurological Diseases, Chairman of the 4–6th Chinese Medical Association Neurosurgery Branch, President of the Chinese Stroke Society, member of the Executive Committee of the World Neurosurgical Union (WFNS), Nomination Committee Member of the United States ANNS, Chairman of the Committee of the Dandy Neurosurgery Society of China, director of the National Higher Education Medical Textbook Research Council, chief editor of Chinese Neurosurgical Journal, deputy editor of Chinese Medical Journal and the Chinese Medical Journal (English version), editor of eight international journals in the field of neurosurgery, including Journal of Clinical Neuroscience.
Dr. Zhao’s research mainly focuses on cerebrovascular disease and brain tumor. He was the principal investigator of China’s ninth, tenth and eleventh Five-Year Plan for Science & Technology Support and honored with National Science & Technology Progress Awards. Prof. Zhao published more than 490 peer-reviewed articles papers, including over 90 SCI included articles and 9 books in the field of neurosurgery. As a world-wide recognized neurosurgeon and clinical neuroscience researcher, Dr. Zhao also serves on the editorial boards of seven scientific journals including Neurosurgical Review, Journal of Clinical Neuroscience and Neurosurgery.
This is the Fall 2018 Kick-Off Seminar, presenting an overview of LCSR, useful information, and an introduction to the faculty and labs. Guests: Sue Vazakas (Librarian) and Career Services
Come join us to meet fellow LCSR students and faculty while eating ice cream from the Charmery.
The quote: “Mathematics is the art of reducing any problem to linear algebra.” by William Stein wonderfully articulates the importance of Linear Algebraic techniques in Pure Mathematics as well as in Engineering applications. I my talk I will discuss how engineering applications as well as recent questions in machine learning have led to a considerable broadening of the linear algebraic toolkit.
Edinah Gnang is an assistant professor in the Department of Applied Mathematics and Statistics. His research interests include discrete mathematics, graph theory, multilinear algebra, image analysis, and experimental math. He earned his doctorate at Rutgers University in 2013.
There are currently over two thousand satellites catalogued on-orbit. Most of them were designed with a finite service life limited by fuel for attitude control and altitude boost. When the fuel is consumed, or a fault occurs in a satellite, we presently lack the ability to conduct on-orbit refueling and repairs. NASA’s Space Shuttle Program enabled a variety of satellite service missions, but all were performed by human spacewalks or robots controlled by crew from within the spacecraft. The most well-known examples are the Hubble Space Telescope servicing missions. However, the risks and cost of using astronauts make satellite servicing by humans prohibitive in all but a very few cases. NASA is currently developing the capabilities necessary to perform satellite servicing tasks telerobotically, with ground-based robot operators. The planned unmanned servicing spacecraft will be equipped with an array of sensors, remotely operated robotic arms, and servicing tools.
In the talk, I will give an overview of NASA’s past and future servicing missions and discuss the partnership between JHU’s Laboratory for Computational Sensing and Robotics (LCSR) and NASA’s Satellite Servicing Projects Division (SSPD) in developing novel robot control methods and robotic tools for upcoming missions. The research efforts at JHU-LCSR focus on facilitating the cutting of thermal insulation on satellites using force sensitive robotic tools and dynamical modeling of the cutting process, and improving the situational awareness of robot operators while performing complex manipulation tasks with limited visual feedback by employing mixed-reality visualization techniques.
Balazs P. Vagvolgyi is an Associate Research Scientist in the Laboratory for Computational Sensing and Robotics at the Johns Hopkins University. He holds a MSc in Computer Science. Before coming to JHU in 2006, he worked on the imaging pipeline of flat-panel interventional vascular X-ray systems at GE Healthcare. He briefly left Hopkins in 2013-2014 to build real-time imaging solutions for mobile as Chief Scientist for Spherical Inc. in San Francisco, CA. His professional interests and research focus on real-time computer vision and visualization, primarily in the context of robotics and medical interventions.