Understanding expertise in surgical gesture by means of Hidden Markov Models

Minimally invasive surgery (MIS) has became very widespread in the last ten years. Due to the difficulties encountered by the surgeons to learn and manage this technique, a huge importance has the improvement of training procedures, the improvement of surgical instrumentation and the robotic automation of surgical gesture. All these purposes require the analysis of surgical performance with the aim to understand it and to define what is expertise in surgical gesture. In this paper for the first time the Hidden Markov Models (HMMs) are used as a tool for the understanding of surgical performance and of the human factors that characterize it. In our experiments we used position data concerning the tools movements during exercises performed on a surgical simulator. Using Hidden Markov theory, we create a model of the expert surgeon performance able to evaluate surgical capability and to distinguish between expert and non-expert surgeons. By analyzing the trained model of the expert surgeon performance we show that it is possible to deduce information about features characterizing the surgical expertise

Comparison of Control Modes of a Hand-Held Robot for Laparoscopic Surgery

Teleoperated robots for minimally invasive surgery make surgeons loose direct contact with the patient. We are developing a handheld, dexterous surgical robot that can be controlled with one hand only, while standing at the operating table. The instrument is composed of a master part (the handle) and a slave part (the tip). This work compares the performance of different control modes, i.e. different ways to map the degrees of freedom of the handle to those of the tip. We ask users to drive the tip along complex trajectories in a virtual environment, using the real master to drive a simulated slave, and assess their performance. Results show that, concerning time, users with no training in laparoscopy prefer a direct mapping of position and orientation, like in free hand motion. However, users trained in laparoscopy perform equally fast with our hand-held robot and, concerning precision, make a smaller number of errors

Surveillance for European bat lyssavirus in Swiss bats

Most countries in Western Europe are currently free of rabies in terrestrial mammals. Nevertheless, rabies remains a residual risk to public health due to the natural circulation of bat-specific viruses, such as European bat lyssaviruses (EBLVs). European bat lyssavirus types 1 and 2 (EBLV-1 and EBLV-2) are widely distributed throughout Europe, but little is known of their true prevalence and epidemiology. We report that only three out of 837 brains taken from bats submitted to the Swiss Rabies Centre between 1976 and 2009 were found by immunofluorescence (FAT) to be positive for EBLVs. All three positive cases were in Myotis daubentoni, from 1992, 1993 and 2002. In addition to this passive surveillance, we undertook a targeted survey in 2009, aimed at detecting lyssaviruses in live bats in Switzerland. A total of 237 bats of the species M. daubentoni, Myotis myotis, Eptesicus serotinus and Nyctalus noctula were captured at different sites in western Switzerland. Oropharyngeal swabs and blood from each individual were analysed by RT-PCR and rapid fluorescent focus inhibition test (RFFIT), respectively. RNA corresponding to EBLV-2 was detected from oropharyngeal swabs of a single M. daubentoni bat, but no infectious virus was found. Molecular phylogenetic analysis revealed that the corresponding sequence was closely related to the other EBLV-2 sequences identified in previous rabies isolates from Swiss bats (particularly to that found at Geneva in 2002). Three M. daubentoni bats were found to be seropositive by RFFIT. In conclusion, even though the prevalence is low in Switzerland, continuous management and surveillance are required to assess the potential risk to public healt

Value of multidetector computed tomography image segmentation for preoperative planning in general surgery

Using practical examples, this report aims to highlight the clinical value of patient-specific three-dimensional (3D) models, obtained segmenting multidetector computed tomography (MDCT) images, for preoperative planning in general surgery.In this study, segmentation and 3D model generation were performed using a semiautomatic tool developed in the authors' laboratory. Their segmentation procedure is based on the neighborhood connected region-growing algorithm that, appropriately parameterized for the anatomy of interest and combined with the optimal segmentation sequence, generates good-quality 3D images coupled with facility of use. Using a touch screen monitor, manual refining can be added to segment structures unsuitable for automatic reconstruction. Three-dimensional models of 10 candidates for major general surgery procedures were presented to the operating surgeons for evaluation. A questionnaire then was administered after surgery to assess the perceived added value of the new technology.The questionnaire results were very positive. The authors recorded the diffuse opinion that planning the procedure using a segmented data set allows the surgeon to plan critical interventions with better awareness of the specific patient anatomy and consequently facilitates choosing the best surgical approach.The benefit shown in this report supports a wider use of segmentation software in clinical practice, even taking into account the extra time and effort required to learn and use these systems