NSF Award
1722000
This SBIR Phase I project will develop the necessary technology and manufacturing workflows to provide medical professionals with extremely realistic physical models of tissues and organs. The models will be manufactured rapidly (within a few hours), inexpensively, and on-demand. They will be patient-specific based on the patient?s CT and MRI scan data. This will have profound implications on the planning of complex medical procedures such as tumor removal and will enable medical professionals and their teams to practice patient-specific surgical scenarios. This will improve surgical outcome, generate efficiencies in the operating room and decrease medical errors which, by some accounts, are the third largest cause of death in the United States. The ability to 3D print realistic human organ models will also provide medical students with a way to practice medical procedures with a wide degree of diversity. This will accelerate the learning rate and expand the breadth of training experiences. Similarly, the models will provide a way for medical professionals to practice rare, high-risk procedures on-demand. The proposed 3D models will become a central part of the medical simulation toolbox and will enable a new generation of surgical planning and education.<br/><br/>The ability to manufacture extremely realistic physical models rapidly, inexpensively, and on-demand relies on a novel multimaterial additive manufacturing process with a closed-feedback loop enabled by machine vision. This new process manufactures objects layer by layer, each layer made from a discrete set of elements, where each element is built from one material from a pallette of materials. The use of the closed-feedback loop system allows incorporating both liquids and solids with a wide range of mechanical and appearance properties. The development of a material palette that is necessary to mimic properties of real tissues will be a crucial part of the project. This material palette will be expanded by spatially combining base materials into composite structures. The second main thrust of the project relies on a software design workflow that translates geometric and material specifications describing a simulation model (e.g., an organ or a tissue) into multimaterial volumetric data. The volumetric data will be used as input to the multimaterial printing platform. The new design workflow requires development of modeling approaches that go beyond traditional, boundary-based CAD representations.
