Evaluating surgical skills from kinematic data using convolutional neural networks

The need for automatic surgical skills assessment is increasing, especially because manual feedback from senior surgeons observing junior surgeons is prone to subjectivity and time consuming. Thus, automating surgical skills evaluation is a very important step towards improving surgical practice. In this paper, we designed a Convolutional Neural Network (CNN) to evaluate surgeon skills by extracting patterns in the surgeon motions performed in robotic surgery. The proposed method is validated on the JIGSAWS dataset and achieved very competitive results with 100% accuracy on the suturing and needle passing tasks. While we leveraged from the CNNs efficiency, we also managed to mitigate its black-box effect using class activation map. This feature allows our method to automatically highlight which parts of the surgical task influenced the skill prediction and can be used to explain the classification and to provide personalized feedback to the trainee.Comment: Accepted at MICCAI 201

TIMS: A Tactile Internet-Based Micromanipulation System with Haptic Guidance for Surgical Training

Microsurgery involves the dexterous manipulation of delicate tissue or fragile structures such as small blood vessels, nerves, etc., under a microscope. To address the limitation of imprecise manipulation of human hands, robotic systems have been developed to assist surgeons in performing complex microsurgical tasks with greater precision and safety. However, the steep learning curve for robot-assisted microsurgery (RAMS) and the shortage of well-trained surgeons pose significant challenges to the widespread adoption of RAMS. Therefore, the development of a versatile training system for RAMS is necessary, which can bring tangible benefits to both surgeons and patients. In this paper, we present a Tactile Internet-Based Micromanipulation System (TIMS) based on a ROS-Django web-based architecture for microsurgical training. This system can provide tactile feedback to operators via a wearable tactile display (WTD), while real-time data is transmitted through the internet via a ROS-Django framework. In addition, TIMS integrates haptic guidance to `guide' the trainees to follow a desired trajectory provided by expert surgeons. Learning from demonstration based on Gaussian Process Regression (GPR) was used to generate the desired trajectory. User studies were also conducted to verify the effectiveness of our proposed TIMS, comparing users' performance with and without tactile feedback and/or haptic guidance.Comment: 8 pages, 7 figures. For more details of this project, please view our website: https://sites.google.com/view/viewtims/hom

Technical skill assessment in minimally invasive surgery using artificial intelligence: a systematic review.

BACKGROUND Technical skill assessment in surgery relies on expert opinion. Therefore, it is time-consuming, costly, and often lacks objectivity. Analysis of intraoperative data by artificial intelligence (AI) has the potential for automated technical skill assessment. The aim of this systematic review was to analyze the performance, external validity, and generalizability of AI models for technical skill assessment in minimally invasive surgery. METHODS A systematic search of Medline, Embase, Web of Science, and IEEE Xplore was performed to identify original articles reporting the use of AI in the assessment of technical skill in minimally invasive surgery. Risk of bias (RoB) and quality of the included studies were analyzed according to Quality Assessment of Diagnostic Accuracy Studies criteria and the modified Joanna Briggs Institute checklists, respectively. Findings were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. RESULTS In total, 1958 articles were identified, 50 articles met eligibility criteria and were analyzed. Motion data extracted from surgical videos (n = 25) or kinematic data from robotic systems or sensors (n = 22) were the most frequent input data for AI. Most studies used deep learning (n = 34) and predicted technical skills using an ordinal assessment scale (n = 36) with good accuracies in simulated settings. However, all proposed models were in development stage, only 4 studies were externally validated and 8 showed a low RoB. CONCLUSION AI showed good performance in technical skill assessment in minimally invasive surgery. However, models often lacked external validity and generalizability. Therefore, models should be benchmarked using predefined performance metrics and tested in clinical implementation studies

Medical students' comfort levels with performing the basic head and neck examination in practice: follow-up during the core clerkship year.

ObjectiveFollowing our preliminary study on junior medical students' comfort levels in performing the head and neck physical examination (H&NPE) before and after a department-led teaching session, we assessed the longitudinal effect of this session on students during the core clinical clerkship year, in which these skills were performed on real patients.DesignAnonymous cross-sectional survey study as a follow-up to previous intervention.MethodsOverall, 101 and 90 second-year medical students participated in an H&NPE teaching session 1 year before the current survey administration in 2 consecutive years. The same cohorts of students, as third years, were asked to rate their comfort levels (0-5-point Likert scale) in performing the H&NPE and the importance of otolaryngology rotations in medical school and primary care residency training.ResultsOf the 101 and 90 students, 53 and 46 medical students completed the follow-up survey in each respective year. For both classes, compared with before the teaching session, students reported an average comfort level of 2.8 (somewhat to moderately comfortable) in performing the complete H&NPE (p < 0.0001) during the core clinical clerkship year. Similar changes were observed for the individual ear, nose, mouth, and neck components of the examination (all p's < 0.0002). Students at follow-up reported statistically similar comfort levels when compared with immediately after the teaching session for the ear, oral cavity, and neck examinations.ConclusionThe initial teaching session persistently improved medical students' comfort levels in performing the H&NPE, with some attrition in comfort levels with performing the nasal examination and complete H&NPE. An otolaryngologist-directed, practical educational intervention may permanently reinforce the acquisition of complex skills such as the H&NPE

Systems and technologies for objective evaluation of technical skills in laparoscopic surgery

Minimally invasive surgery is a highly demanding surgical approach regarding technical requirements for the surgeon, who must be trained in order to perform a safe surgical intervention. Traditional surgical education in minimally invasive surgery is commonly based on subjective criteria to quantify and evaluate surgical abilities, which could be potentially unsafe for the patient. Authors, surgeons and associations are increasingly demanding the development of more objective assessment tools that can accredit surgeons as technically competent. This paper describes the state of the art in objective assessment methods of surgical skills. It gives an overview on assessment systems based on structured checklists and rating scales, surgical simulators, and instrument motion analysis. As a future work, an objective and automatic assessment method of surgical skills should be standardized as a means towards proficiency-based curricula for training in laparoscopic surgery and its certification

Virtual reality and serious gaming in re-engineering clinical teaching: A review of literature of the experiences and perspectives of clinical trainers

Re-engineer clinical teaching through innovative approaches such as virtual reality (VR) and Serious Gaming (SG) may increase patient safety. While several studies have focused on the experiences and perceptions of learners about VR and SG, few have if any have focused on the instructors. We reviewed and appraised published evidence to establish the experiences and intention to adopt VR and SG in clinical teaching. Relevant articles were sourced from five databases (PubMed/Medline, Informit, +A Education, ProQuest-ERIC, and CINHAL-EBSCO host). Experiences of clinical trainers were reported using the technological, pedagogical, and content knowledge (TPACK) model. The intention to adopt VR and SG was synthesized using the Technology Adoption Model (TAM). Clinical trainers had a positive attitude towards VR and SG. Those with longer professional experience were less likely to adopt VR and SG, while more experienced trainers were more likely to benefit from VR and SG. VR and SG are practical pedagogies for clinical instruction, but training is required for novice users. Cost-benefit analysis of VR and SG as clinical training approaches is needed

Design and Evaluation of Neurosurgical Training Simulator

Surgical simulators are becoming more important in surgical training. Consumer smartphone technology has improved to allow deployment of VR applications and are now being targeted for medical training simulators. A surgical simulator has been designed using a smartphone, Google cardboard 3D glasses, and the Leap Motion (LM) hand controller. Two expert and 16 novice users were tasked with completing the same pointing tasks using both the LM and the medical simulator NeuroTouch. The novice users had an accuracy of 0.2717 bits (SD 0.3899) and the experts had an accuracy of 0.0925 bits (SD 0.1210) while using the NeuroTouch. Novices and experts improved their accuracy to 0.3585 bits (SD 0.4474) and 0.4581 bits (SD 0.3501) while using the LM. There were some tracking problems with the AR display and LM. Users were intrigued by the AR display and most preferred the LM, as they found it to have better usability

State Strategies to Improve Quality and Efficiency: Making the Most of Opportunities in National Health Reform

Examines ten states' initiatives to address key components of quality and efficiency improvement, including data collection, aggregation, and standardization; public reporting; payment reform; consumer engagement; and provider engagement