A synergistic engineered 3D tissue and computational approach to surgical training
Abstract
This proposal will address the challenge of how to advance meaningful surgical training simulators. At the same time, it will contri"bute: the means to create new training simulations; the physical creation of engineered tissue structure with integrated vasculature and physiologically relevant biomechanical properties; the analytical modeling of complex biological systems under mechanical stimulation; and the computational representation and search of hard spatial planning problems.We will develop 3D engineered tissue structures with integrated vascular networks using advanced manufacturing processes through microfabrication and 3D printing of biological polymers and living cells. Modeling of tissue biomechanical behavior during surgical incision will be pursued using advanced finite element models that address the non-linear behavior of the system while accounting for important physiological structural features. These computational models will be experimentally verified by the tissue engineering studies and will feed into the virtual reality system in the options years.Computer agents will leverage the models (derived from the tissue modeling work) to search for opt"imal surgical plans. This computational approach will be accomplished through a method called shape grammars, which will intelligent"ly create a wide range of potential vascular networks as well as surgical plans. The agents will then intelligently computationally search through all of the potential outcomes and help narrow to the best solutions. This shape grammar approach will save immense amounts of time and effort to focus the experimental component on the best approaches. Agents will act on a representation based on generative shape grammars that allow for parametric and configuration variation of tissue structures to enable training simulation based on a variety of circumstances and models of specific patient configurations. These agents will also generate optimal designs of biosynthetic vascular networks that will feed directly into the state-of-the-art 3D bioprinting approach to directly manufacture 3D engineered muscle tissue for surgical planning. Our ~create-integrate-test~ approach couples physical and computational tools to en"able creation of new physical and virtual models, integrates these models with optimized surgical plans, and ultimately tests physic""al and virtual approaches to confirm effectiveness of these models and surgical plans.In the option years, user studies will be co"nducted with physicians and trainees when using the 1) the engineered 3D muscle tissue and the 2) the optimal computational models generated by the agents. Feedback from physicians will provide guidance for computational agents to solve the challenging problem of" surgical planning while accounting for muscle response along with vascular structure important to bleeding, thereby providing intel""ligent training assistance. Further in the option years, the results of this work will also be integrated into a virtual reality s""ystem that enables visual and experimental exploration and feedback, utilizing the integration of the experimental and computational"" engineered 3D tissue work in the first 3 years. The virtual structures can be more complex than the physically manufactured ones, a"llowing for more intricate physical-virtual environments for more significant surgical training capabilities. This combination will also be assessed with usability studies.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 09, 2017
- Source ID
- N000141712566
Entities
People
- Philip Leduc
Organizations
- Massachusetts Institute of Technology
- Office of Naval Research
- United States Navy