NSF Award
2406201
This Smart and Connected Health (SCH) award will focus on creating a robotic system for diagnosis of abnormal tissues inside the abdominal cavity. Diseased abdominal organs often present a complex mixture of normal, abnormal but non-cancerous, and cancerous tissues. Existing medical imaging methods fail to offer useful diagnosis due to errors caused by breathing and the limits of imaging resolution and sensitivity. Diagnostic laparoscopy along with tissue biopsies can provide more detailed information to guide treatment but are limited due to subjective errors in visual inspection and errors from sampling a small amount of tissue. To solve these problems, this research project will develop a smart robotic system with multiple sensors and artificial intelligence. The robot will move through the abdominal cavity, analyze the size, shape, and chemical information of tissues, and identify abnormal tissues. The research will also include educational and outreach activities to promote STEM fields, especially among groups that are traditionally underrepresented in these areas.<br/><br/>The goal of the research is to design, develop, and evaluate a multimodal robotic system equipped with flexible endoscopy, ultrasound imaging, and Raman spectroscopy for comprehensive cancer diagnosis in the abdominal cavity. The project is built upon three research thrusts: 1) developing a multimodal instrument for multiscale tissue diagnosis, 2) developing a mesoscale continuum robot for tissue surface scanning, and 3) developing multimodal fusion for comprehensive diagnosis. The first thrust integrates a balloon-based ultrasonic probe with a Raman spectroscopy needle to detect, classify, and stage tissue on the surface and deep inside organs. The second thrust integrates the sensing modalities with a tendon-driven continuum robot and equips the robot with the ability to scan tissue surface through data-driven modeling and model predictive control. The third thrust combines data from multiple sources to perform tissue identification and staging and builds robust models to handle missing/occluded data and improve overall accuracy. The robotic system and its individual components will be calibrated and demonstrated by performing navigation tasks and collecting data using gelatin, tissue, and abdomen phantoms. The robotic system may not only provide comprehensive diagnosis of heterogeneous and unstructured tissue environments but also improve the safety and accuracy of surgery through intra-operative diagnosis. This project will generate new knowledge and methods in biomechanics and mechanobiology by revealing multiscale tissue information and potentially identifying new biomarkers critical to cancer treatment.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
