Using computerized assessment in simulated colonoscopy: a validation study

Development of a synchronous motion-tracking and video capture tool for flexible ureteroscopy

INTRODUCTION

Hand/instrument motion-tracking in surgical simulation provides valuable data to improve psychomotor skills and can serve as a formative evaluation tool. Motion analysis has been well-studied in laparoscopic surgery; however, there are essentially no studies looking at motion-tracking for flexible ureteroscopy (fURS ), a common surgical procedure requiring hand dexterity and 3D spatial awareness. We aimed to design a synchronized motion-tracking and video capture system for fURS capable of collecting objective metrics for use in surgical skills training.

METHODS

Motion tracking of the ureteroscope was performed using a motion-tracking platform, inertial measurement units (IMUs), and an optical sensor. Position (x, y, z) and orientation (roll, pitch, yaw) of the ureteroscope handle, lever deflection, and translation of the scope insertion point were collected. Video capture of the operator's hands was collected with a Raspberry Pi camera. All peripherals were controlled on a Raspberry Pi 4 and synchronized to its system clock.

RESULTS

Our system demonstrated good accuracy in detecting translation of the ureteroscope in the x- and y-axes, and yaw, pitch and roll of the ureteroscope at discrete orientations of 0, ±30, ±60, and ±90 degrees. Unique to fURS, deflection of the lever was captured by the difference in IMU static accelerations with good accuracy. The optical sensor detected translation of the ureteroscope at the insertion point with good precision and an average error of 5.51%.

CONCLUSIONS

We successfully developed a motion-tracking and video-capture system capable of collecting motion-analysis parameters unique to fURS . Future studies will focus on establishing the construct validity of this tool.

Acquisition and usage of robotic surgical data for machine learning analysis

BACKGROUND

The increasing use of robot-assisted surgery (RAS) has led to the need for new methods of assessing whether new surgeons are qualified to perform RAS, without the resource-demanding process of having expert surgeons do the assessment. Computer-based automation and artificial intelligence (AI) are seen as promising alternatives to expert-based surgical assessment. However, no standard protocols or methods for preparing data and implementing AI are available for clinicians. This may be among the reasons for the impediment to the use of AI in the clinical setting.

METHOD

We tested our method on porcine models with both the da Vinci Si and the da Vinci Xi. We sought to capture raw video data from the surgical robots and 3D movement data from the surgeons and prepared the data for the use in AI by a structured guide to acquire and prepare video data using the following steps: 'Capturing image data from the surgical robot', 'Extracting event data', 'Capturing movement data of the surgeon', 'Annotation of image data'.

RESULTS

15 participant (11 novices and 4 experienced) performed 10 different intraabdominal RAS procedures. Using this method we captured 188 videos (94 from the surgical robot, and 94 corresponding movement videos of the surgeons' arms and hands). Event data, movement data, and labels were extracted from the raw material and prepared for use in AI.

CONCLUSION

With our described methods, we could collect, prepare, and annotate images, events, and motion data from surgical robotic systems in preparation for its use in AI.

Methods for Gastrointestinal Endoscopy Quantification: A Focus on Hands and Fingers Kinematics

Gastrointestinal endoscopy is a complex procedure requiring the mastery of several competencies and skills. This procedure is in increasing demand, but there exist important management and ethical issues regarding the training of new endoscopists. Nowadays, this requires the direct involvement of real patients and a high chance of the endoscopists themselves suffering from musculoskeletal conditions. Colonoscopy quantification can be useful for improving these two issues. This paper reviews the literature regarding efforts to quantify gastrointestinal procedures and focuses on the capture of hand and finger kinematics. Current technologies to support the capture of data from hand and finger movements are analyzed and tested, considering smart gloves and vision-based solutions. Manus VR Prime II and Stretch Sense MoCap reveal the main problems with smart gloves related to the adaptation of the gloves to different hand sizes and comfortability. Regarding vision-based solutions, Vero Vicon cameras show the main problem in gastrointestinal procedure scenarios: occlusion. In both cases, calibration and data interoperability are also key issues that limit possible applications. In conclusion, new advances are needed to quantify hand and finger kinematics in an appropriate way to support further developments.

Colonoscope retraction technique and predicting adenoma detection rate: a multicenter study

BACKGROUND AND AIMS

The success of preventing colorectal cancer relies on the expertise of the colonoscopists. Studies suggest that the retraction technique is a powerful indicator of expertise in distinguishing endoscopists with various adenoma detection rates (ADRs). We aimed to develop a retraction technique score and explore the correlation between endoscopists' retraction technique and their ADRs.

METHODS

In a prospective, multicenter study, 8 colonoscopist nurses and physicians with various ADRs were included. Data from patients admitted for a colonoscopy, as part of the Danish nationwide screening program, were gathered directly from the Olympus ScopeGuide system (UPD-3; Olympus Optical, Tokyo, Japan) providing XYZ-coordinates from the coils along the length of the colonoscope. Motor skill measures were developed based on tip retraction, retraction efficiency, and retraction distance. The principal component analysis was used to study the association among the 3 measures and the historical ADR to create a combined score, the colonoscopy retraction score (CoRS).

RESULTS

Three hundred thirty-three recordings were analyzed. We demonstrated a significant and strong correlation between CoRS and ADR (.90, P < .01). Conversely, withdrawal time did not correlate significantly with ADR (.33, P = .42). In procedures without polypectomies or biopsy sampling, a significant and strong correlation was found between CoRS and ADR (.88, P < .01) and between withdrawal time and ADR (.75, P = .03).

CONCLUSIONS

This study presents a novel, real-time computerized and unbiased assessment tool for colonoscopy withdrawal. CoRS strongly correlated with ADR with and without therapeutic interventions during withdrawal and could be used to ensure quality instead of minimal withdrawal time. (Clinical trial registration number: NCT03587935.).

Expertise in colonoscopy intubation does not predict diagnostic accuracy: a simulation-based study

Background and study aims  Studies have linked cecal intubation rate with adenoma detection rate; however, the direct association between technical performance during colonoscopy intubation and withdrawal has never been explored. Thus, it remains unclear whether gentle and efficient intubation predicts superior mucosal inspection. The aim of this study was to investigate the correlation between performance during intubation and withdrawal in a simulation-based setup. Methods  Twenty-four physicians with various experience in colonoscopy performed twice on the Endoscopy Training System (ETS). Intubation skills were evaluated by assessing tasks on the ETS related to intubation (scope manipulation and loop management) and use of a computerized assessment tool called the 3D-Colonoscopy Progression Score (3D-CoPS). Diagnostic accuracy was defined by the number of polyps found during the ETS task of mucosal inspection. Pearson's correlations were calculated to explore associations between intubation skill and diagnostic accuracy. Results  The correlation analysis between 3D-CoPS and number of polyps found during mucosal inspection revealed a weak and insignificant correlation (0.157, P  = 0.3). Likewise, an insignificant correlation was seen between ETS intubation and number of polyps found (0.149, P  = 0.32). Conclusions  We found no evidence to support that technical performance during intubation is correlated with mucosal inspection performance in a simulation-based setting.

Simulation-based VATS resection of the five lung lobes: a technical skills test

BACKGROUND

Video-Assisted Thoracoscopic Surgery (VATS) lobectomy is an advanced procedure and to maximize patient safety it is important to ensure the competency of thoracic surgeons before performing the procedure. The objective of this study was to investigate validity evidence for a virtual reality simulator-based test including multiple lobes of the lungs.

METHOD

VATS experts from the department of Cardiothoracic Surgery at Rigshospitalet, Copenhagen, Denmark, worked with Surgical Science (Gothenburg, Sweden) to develop VATS lobectomy modules for the LapSim^® virtual reality simulator covering all five lobes of the lungs. Participants with varying experience in VATS were recruited and classified as either novice, intermediate, or experienced surgeons. Each participant performed VATS lobectomy on the simulator for three different randomly chosen lobes. Nine predefined simulator metrics were automatically recorded on the simulator.

RESULTS

Twenty-two novice, ten intermediate, and nine experienced surgeons performed the test resulting in a total of 123 lobectomies. Analysis of Variances (ANOVA) found significant differences between the three groups for parameters: blood loss (p < 0.001), procedure time (p < 0.001), and total instrument path length (p = 0.03). These three metrics demonstrated high internal consistency and significant test-retest reliability was found between each of them. Relevant pass/fail levels were established for each of the three metrics, 541 ml, 30 min, and 71 m, respectively.

CONCLUSION

This study provides validity evidence for a simulator-based test of VATS lobectomy competence including multiple lobes of the lungs. The test can be used to ensure basic competence at the end of a simulation-based training program for thoracic surgery trainees.