Physician Assistance Technology in Image-guided Robotic Intervention of Prostate

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Recent advances in the multi-parametric MRI of the prostate have led to a surge in new research methods for the detection and diagnosis of prostate cancer - with the goal of accurate risk- stratification of prostate cancer. Specifically, a traditional Transrectal Ultrasound (TRUS)-guided biopsy tends to fail, as samples are randomly collected from the prostate without aiming at suspicious lesions often visible in MRI. Currently, several new MRI biopsy approaches have come to the forefront. They are being evaluated and adopted in clinical practice, including in-bore MRI- guided biopsy and TRUS-guided MRI-fusion biopsy, collectively called ‘MRI-targeted biopsy.’ While recent literature shows that MRI-targeted biopsies can detect more clinically significant cancer than a conventional TRUS-guided biopsy, there is still a substantial issue with the precision placement of the needle in these procedures particularly in transperineal approach, resulting in clinicians being overly conservative with the amount of tissue removal (Zhang et al., 2019). Need to address needle placement accuracy in transperineal biopsy is further heightened lately as the fluoroquinolone- resistant Escherichia coli is becoming a significant concern in public health, and clinicians are shifting to use transperineal biopsies to avoid post-biopsy infections and overuse of antibiotics. Literature, as well as our preliminary studies, found that needle deflection is a substantial obstacle for precision aiming in transperineal biopsies. Abundant literature on needle deflection analysis, needle steering, and image-guided robots are available in pre-clinical engineering studies. Yet, clinically viable or proven solutions to address the needle deflection is yet to be seen. Therefore, the objective of this application is to develop and test a cooperative robotic intervention with closed-loop error compensation in MRI targeted biopsies and focal therapies, resulting in more precisely targeted instrument placement. Accurately, we will aim to address needle deflection by the synergic use of advanced imaging and robotics. Guided by robust preliminary data, this objective is achieved by pursuing three specific aims: 1) We will develop novel tracking techniques and clinically deploy a cooperatively controlled, hands-on robotic needle placement manipulator to enable fine instrument control at the periphery of the MRI bore. 2) We will test the usefulness of a cooperatively controlled robot to increase the accuracy of needle placement in animal studies mimicking MRI-guided biopsies of the prostate. Our approach is innovative in its application of novel cooperative robotic control, in which the clinician maintains ultimate control with the direction of motion being autonomous to ensure the desired path is followed to the intended target. The proposed study is also clinically significant since the completion of this current engineering study will enable machine- assisted semi-autonomous percutaneous therapy, much discussed in the recent editorial article in Science Robotics (Yang et al., 2018). The impact of the study reaches beyond MRI-targeted prostate intervention; the technology developed can be translated into other forms of MRI-guided or ultrasound-guided intervention.