Event Location: NSH 1305
Bio: Dr. Jaydev P. Desai is currently an Associate Professor in the Department of Mechanical Engineering and a Member of the Maryland Robotics Center at the University of Maryland, College Park (UMCP). Prior to joining UMCP, he was an Associate Professor at Drexel University. He completed his undergraduate studies from the Indian Institute of Technology, Bombay, India, in 1993. He received his M.A. in Mathematics in 1997, M.S. and Ph.D. in Mechanical Engineering and Applied Mechanics in 1995 and 1998 respectively, all from the University of Pennsylvania. Prior to joining Drexel University, he was a Post-Doctoral Fellow in the Division of Engineering and Applied Sciences at Harvard University. He is a recipient several NIH R01 awards, NSF CAREER award, and was also the lead inventor on the “Outstanding Invention of 2007 in Physical Science Category” at the University of Maryland, College Park. He is also the recipient of the Ralph R. Teetor Educational Award. His research interests include image-guided surgical robotics, reality- based soft-tissue modeling for surgical simulation, grasping, haptics, and micro-scale cell and tissue characterization. He is currently an Associate Editor of IEEE Transactions on Biomedical Engineering (TBME) and the Co-Chair of Surgical Robotics Technical Committee of IEEE Robotics and Automation Society. He is also a member of the ASME and IEEE.

Abstract: Brain tumors are among the most feared complications of cancer occurring in 20–40% of adult cancer patients. Though there have been significant advances in treatment, the prognosis for these patients is poor. Whether there is a primary malignancy or a secondary malignancy, whenever the brain of the cancer patient is involved in treatment, there is a significant impact on their overall quality of life. While the most optimal treatment currently for most brain tumors involves primary surgical resection, many patients may not be able to undergo that treatment plan due to either their poor general health or an unfavorable location (either deep inside the brain or inaccessibility of the tumor) of the lesion.

Magnetic resonance imaging (MRI) provides excellent soft tissue contrast and has become a standard imaging modality for physicians in several image-guided interventions. However, the nature of MR imaging imposes several constraints on the development of a robotic system. These challenges include actuator choice, sensor choice, material choice, size of the robot, etc., to name a few.

In this talk, we will discuss our progress on the development of MINIR: Minimally Invasive Neurosurgical Intracranial Robot, and identify the challenges in the development of this meso-scale robotic system operated under MRI guidance.