Clinical safety and efficacy of a fully automated robot for magnetic resonance imaging-guided breast biopsy.

BACKGROUND: Magnetic resonance imaging (MRI)-guided biopsies are an accurate, but technically challenging, method for screening and diagnosis of breast lesions. This study assesses the safety and efficacy of an Image Guided Automated Robot (IGAR) in performing breast biopsies compared to manual procedures. METHODS: Safety was determined from adverse events (AEs) and device deficiencies. Efficacy was assessed using targeting accuracy, number of successful biopsies, pain and scar scores, patient discomfort, and radiologist-determined ease-of-use. RESULTS: All seven procedures in phase I were successfully and safely completed with no AEs and one device deficiency. The 23 IGAR biopsies in phase II outperformed the 18 manual biopsies in 1-week pain scores (p = 0.027), scarring at 1-week (p = 0.035), 1-month (p = 0.004), and components of comfort and ease-of-use. Phase II had seven and three AEs in the IGAR and manual groups, respectively (p = 0.317), with no serious AEs and nine device deficiencies. CONCLUSIONS: The IGAR system is safe and effective for breast biopsy procedures. The results from these trials indicate the IGAR system as a potentially viable alternative to manual breast biopsy procedures.

An image-guided automated robot for MRI breast biopsy.

BACKGROUND: The IGAR (Image-guided Automated Robot) is a robotic platform capable of performing highly accurate clinical interventions under image guidance. The IGAR is unique in that it demonstrates MRI compatibility and maintains safe operation, adequate shielding, high image quality, and accurate robotic control even while in an imaging environment. The IGAR is initially intended for breast biopsy. METHODS: Tests for projectile hazards, heating, signal-to-noise ratio loss, and geometric distortion were used to demonstrate MR compatibility. Accuracy and repeatability of the robotic system were tested on benchtop models to establish a baseline of precision. RESULTS: The IGAR averaged an accuracy of 0.34 mm and a repeatability of 0.2 mm. There was no significant distortion attributable to the robot, no projectile risk, and no unacceptable levels of heating. CONCLUSION: The IGAR system is safe and effective in an MRI environment Copyright © 2016 John Wiley & Sons, Ltd.

Surgical robotics: a review and neurosurgical prototype development.

PURPOSE: The purpose of this article is to update the neurosurgical community on the expanding field of surgical robotics and to present the design of a novel neurosurgical prototype. It is intended to mimic standard technique and deploy conventional microsurgical tools. The intention is to ease its integration into the "nervous system" of both the traditional operating room and surgeon. CONCEPT: To permit benefit from updated intraoperative imaging, magnetic resonance imaging-compatible materials were incorporated into the design. Advanced haptics, optics, and auditory communication with the surgical site recreate the sight, sound, and feel of neurosurgery. RATIONALE: Magnification and advanced imaging have pushed surgeons to the limit of their dexterity and stamina. Robots, in contrast, are indefatigable and have superior spatial resolution and geometric accuracy. The use of tremor filters and motion scalers permits procedures requiring superior dexterity. DISCUSSION: Breadboard testing of the prototype components has shown spatial resolution of 30 microm, greatly exceeding our expectations. Neurosurgeons will not only be able to perform current procedures with a higher margin of safety but also must speculate on techniques that have hitherto not even been contemplated. This includes coupling the robot to intelligent tools that interrogate tissue before its manipulation and the potential of molecular imaging to transform neurosurgical research into surgical exploration of the cell, not the organ.

An image-guided magnetic resonance-compatible surgical robot.

OBJECTIVE: The past decade has witnessed the increasing application of robotics in surgery, yet there is no existing system that combines stereotaxy and microsurgery in an imaging environment. To fulfill this niche, we have designed and manufactured an image-guided robotic system that is compatible with magnetic resonance imaging. METHODS: The system conveys the sight, touch, and sound of surgery to an operator seated at a remote workstation. Motion scaling, tremor filtering, and precision robotics allow surgeons to rapidly attain technical proficiency while working at a spatial resolution of 50 to 100 microm instead of a few millimeters. This system has the potential to shift surgery from the organ toward the cellular level. RESULTS: By integrating the robot with images obtained during the procedure, the effects of surgery on both the lesion and brain are immediately revealed. CONCLUSION: We are providing technology to advance and transform surgery with the potential to improve patient outcome.