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Surgical techniques are becoming more complex and require substantial training to master. The development of automated, objective methods to analyze and evaluate surgical skill is necessary to provide trainees with reliable and accurate feedback during their training programs. We present a system to capture, visualize, and analyze the movements of a laparoscopic surgeon for the purposes of skill evaluation. The system records the upper body movement of the surgeon, the position, and orientation of the instruments, and the force and torque applied to the instruments. An empirical study was conducted using the system to record the performances of a number of surgeons with a wide range of skill. The study validated the usefulness of the system, and demonstrated the accuracy of the measurements.

The learning curve for computer navigated total knee arthroplasty (TKA) is not well defined. We collected data prospectively on a consultant surgeon's first 50 navigated TKAs. Over the same period, matching data was taken from 50 consecutive cases performed by an expert who has performed over 1000 navigated TKAs. From the first case, the novice navigator was able to achieve the same standard as the expert in terms of post-implant mechanical alignment in the coronal and sagittal planes. Equally, at 6 weeks and one year post-surgery there was no significant difference in the mean Oxford score, mechanical axis and range of movement for the two groups of patients. Operative time was significantly longer for the novice surgeon in the first 20 cases (92 versus 73 min, p < 0.001), but by the final 20 cases there was no difference (72 versus 74 min, p = 0.944). This study shows that the learning curve for navigated TKA is approximately 20 cases and that a beginner can reproduce the results of an expert from the outset.

One of the most important advantages of computer simulators for surgical training is the opportunity they afford for independent learning. However, if the simulator does not provide useful instructional feedback to the user, this advantage is significantly blunted by the need for an instructor to supervise and tutor the trainee while using the simulator. Thus, the incorporation of relevant, intuitive metrics is essential to the development of efficient simulators. Equally as important is the presentation of such metrics to the user in such a way so as to provide constructive feedback that facilitates independent learning and improvement. This paper presents a number of novel metrics for the automated evaluation of surgical technique. The general approach was to take criteria that are intuitive to surgeons and develop ways to quantify them in a simulator. Although many of the concepts behind these metrics have wide application throughout surgery, they have been implemented specifically in the context of a simulation of mastoidectomy. First, the visuohaptic simulator itself is described, followed by the details of a wide variety of metrics designed to assess the user's performance. We present mechanisms for presenting visualizations and other feedback based on these metrics during a virtual procedure. We further describe a novel performance evaluation console that displays metric-based information during an automated debriefing session. Finally, the results of several user studies are reported, providing some preliminary validation of the simulator, the metrics, and the feedback mechanisms. Several machine learning algorithms, including Hidden Markov Models and a Naïve Bayes Classifier, are applied to our simulator data to automatically differentiate users' expertise levels.

Objective: A simulator was developed to mimic commercial CAS systems in implementing most tasks required to carry out a surgical operation. As tracking systems are generally expensive components, an alternative solution based on low-cost video-based tracking was used. Video tracking accuracy was assessed to determine whether or not this kind of approach was suitable for use in the training domain. Ultimately, video-based tracking should enable sufficiently accurate registration between a bony model and its virtual 3D representation., Materials and Methods: Video tracking was assessed using two types of camera. For each one, common accuracy tests were realized as a series of 10 trials at ranges of 0.5-1.0 m from the camera lens. The pointer used as a digitizer was equipped with tracked video markers. Three sizes of marker were evaluated to estimate the impact of marker size on accuracy., Results: For the better of the two cameras tested, results were encouraging. Results are presented as rounded whole-number values in millimeters. The noise test gave accuracies of 2 mm for the 80-mm marker, 3 mm for the 60-mm marker and 5 mm for the 40-mm marker. Relative accuracies, as evaluated on a grid of equally spaced dots, were 4 mm with the 80-mm marker, 7 mm with the 60-mm marker and 12 mm with the 40-mm marker. A pivoting test around the pointer tip gave 3 mm of accuracy for the 80-mm marker, 5 mm for the 60-mm marker and 11 mm for the 40-mm marker. An additional pivoting test was completed on increasing the distance of the marker from the pointer tip, giving accuracies of 5 mm for the 80-mm marker, 6 mm for the 60-mm marker and 13 mm for the 40-mm marker. The registration test gave accuracies of 8 mm for the 80-mm marker, 9 mm for the 60-mm marker and 11 mm for the 40-mm marker., Conclusions: The video-based approach offers sufficient accuracy to achieve registration in the domain of CAS training.

Intraoperative MRI has recently entered the operating room as a new imaging modality. Customized visualization systems might further facilitate the use of this imaging technology. A visualization system for use in the interventional MRI has been developed, providing a virtual environment for surgical navigation using real-time images and for controlling the scanner. The visualization system has customized features for certain clinical applications. A training and testing facility has also been established. The introduction of the visualization system in the interventional MRI overcame several ambiguities and inconsistencies that were previously present, and resulted in a more transparent man-machine interface approach. A pilot study using the software to place cryoprobes in an animal liver showed promising results. Augmentation of real-time MR images with 3D rendering and customized navigation features opens new possibilities in intraoperative MRI. The described system can also be extended to other intraoperative imaging modalities., (Copyright 2002 Wiley-Liss, Inc.)