Multi-imager compatible actuation principles in surgical robotics.
Today's most successful surgical robots are perhaps surgeon-driven systems, such as the daVinci (Intuitive Surgical Inc., USA, www.intuitivesurgical.com). These have already enabled surgery that was unattainable with classic instrumentation; however, at their present level of development, they have limited utility. The drawback of these systems is that they are independent self-contained units, and as such, they do not directly take advantage of patient data. The potential of these new surgical tools lies much further ahead. Integration with medical imaging and information are needed for these devices to achieve their true potential. Surgical robots and especially their subclass of image-guided systems require special design, construction and control compared to industrial types, due to the special requirements of the medical and imaging environments. Imager compatibility raises significant engineering challenges for the development of robotic manipulators with respect to imager access, safety, ergonomics, and above all the non-interference with the functionality of the imager. These apply to all known medical imaging types, but are especially challenging for achieving compatibility with the class of MRI systems. Even though a large majority of robotic components may be redesigned to be constructed of MRI compatible materials, for other components such as the motors used in actuation, prescribing MRI compatible materials alone is not sufficient. The electromagnetic motors most commonly used in robotic actuation, for example, are incompatible by principle. As such, alternate actuation principles using "intervention friendly" energy should be adopted and/or devised for these special surgical and radiological interventions. This paper defines the new concept of Multi-Imager Compatibility of surgical manipulators and describes its requirements. Subsequently, the paper gives several recommendations and proposes new actuation principles for this concept. Several implementations have been constructed and tested, and the results are presented here. This is the first paper addressing these issues.
Stoianovici
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URobotics Lab, Urology Department, Johns Hopkins Medicine, Baltimore, USA. dss@jhu.edu
D003952:Diagnostic Imaging / Q000295:instrumentation*; D004867:Equipment Design; D006801:Humans; D008279:Magnetic Resonance Imaging; D008962:Models, Theoretical; D012371:Robotics; D013514:Surgical Procedures, Operative / Q000379:methods*