This dissertation addresses the development of medical devices, image-guided robots, and their application in needle-based interventions, as well as methods to improve accuracy and safety in clinical procedures. Needle access is an essential component of minimally invasive diagnostic and therapeutic procedures. Image-guiding devices are often required to help physicians handle the needle based on the images. Integrating robotic accuracy and precision with digital medical imaging has the potential to improve the clinical outcomes.
The dissertation presents two robotic devices for interventions under Magnetic Resonance Imaging (MRI) respectively Computed Tomography (CT) – Ultrasound(US) cross modality guidance. The MRI robot is a MR Safe Remote Center of Motion (RCM) robot for direct image-guided needle interventions such as brain surgery. The dissertation also presents the integration of the robot with an intraoperative MRI scanner, and preclinical tests for deep brain needle access.
The CT-Ultrasound guidance uses a robotic manipulator to handle an US probe within a CT scanner. The dissertation presents methods related to the co-registration of multi-image spaces with an intermediary frame, experiments for needle targeting.
The dissertation also presents method on using optical tracking measurements specifically for medical robots. The method was derived to test the robots presented above.
With advanced image-guidance, such as the robotic approaches, needle targeting accuracy may still be deteriorated by errors related to needle defections. Methods and associated devices for needle steering on the straight path are presented. These are a robotic approach that uses real-time ultrasound guidance to steer the needle; Modeling and testing of a method to markedly reduce targeting errors with bevel-point needles; Dynamic design, manufacturing, and testing of a novel core biopsy needle with straighter path, power assistance, reduced noise, and safer operation.
Overall, the dissertation presents several developments that contribute to the field of medical devices, image-guided robots, and needle interventions. These include robot testing methods that can be used by other researchers, needle steering methods that can be used directly by physicians or for robotic devices, as well as several methods to improve the accuracy in image-guided interventions. Collectively, these contribute to the field and may have a significant clinical impact
