Biomedical subjects
Publications and source records attributed to Paul B McBeth.
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OBJECTIVE: Methods of evaluating surgical performance are mainly subjective. This study introduces a method of evaluating surgical performance using a quantitative analysis of tool tip kinematics. METHODS: One experienced surgeon performed eight rat microvascular anastomoses over a 2-day interval. An optoelectronic motion analysis system acquired tool tip trajectories at frequencies of 30 Hz. On the basis of a hierarchical decomposition, the procedure was segmented into specific surgical subtasks (free space movement, needle placement and knot throws) from which characteristic measures of performance (tool tip trajectory, excursion and velocity) were evaluated. Comparisons of performance measures across each procedure were indexed (D scale) using the Kolmogorov-Smirnov statistic. RESULTS: Despite the marker occlusions, tool tip data were obtained 92 +/- 7% (mean +/- SD) of the time during manipulation tasks. Missing data segments were interpolated across gaps of less than 10 sample points with errors less than 0.4 mm. The anastomoses were completed in 27 +/- 4 min (range 20.5-31.4 min) with 100% patency. Tool tip trajectories and excursions were comparable for each hand, while right and left hand differences were found for velocity. Performance measures comparisons across each procedure established the benchmark for an experienced surgeon. The D-scale range was between 0 and 0.5. CONCLUSION: The study establishes a reproducible method of quantitating surgical performance. This may enhance assessment of surgical trainees at various levels of training.
Technological developments in imaging guidance, intraoperative imaging, and microscopy have pushed neurosurgeons to the limits of their dexterity and stamina. The introduction of robotically assisted surgery has provided surgeons with improved ergonomics and enhanced visualization, dexterity, and haptic capabilities. This article provides a historical perspective on neurosurgical robots, including image-guided stereotactic and microsurgery systems. The future of robot-assisted neurosurgery, including the use of surgical simulation tools and methods to evaluate surgeon performance, is discussed.
Technological advances in the modern operating room have pushed neurosurgeons to the limits of their dexterity and stamina. Motion scalers and tremor filters on robots permit unprecedented precision of tool manipulation, upgrading the human hand, and closing the deftness deficit. The evolution of neurosurgical robots from stereotactic systems to hybrid systems capable of both stereotaxy and microsurgery is examined. The future of robot-assisted neurosurgery, including expanded tool sets and the prospect of semi-autonomous surgery, is discussed.
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.
Quantitative performance and skill assessments are critical for evaluating the progress of surgical residents and the efficacy of different training programs. Current evaluation methods are subjective and potentially unreliable, so there is a need for objective methods to evaluate surgical performance. We identify a feasible method to measure kinematic data in the live operating room setting and to assess the repeatability of an analysis method based on a hierarchical decomposition of surgical tasks. We used an optoelectronic motion analysis system to acquire postural data and tool tip trajectories of one expert surgeon over a period of four months. To assess repeatability of performance measures, we created a hierarchical decomposition diagram describing the procedure in terms of surgical tasks, tool sequences and fundamental tool actions. From the kinematic data, we extracted characteristic measures of individual tool actions and compared these measured distributions using the Kolmogorov-Smirnov statistic. The comparisons of distributions show consistent performance over time by a trained surgeon and little effect from patient variability, and so are likely reliable measures of performance. An expanded set of reliable kinematic measures will form the basis for quantifying surgical skill and should be useful in validating surgical simulations for use in training, certifying surgeons and designing and evaluating new surgical tools.
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