Kinematic metrics and surgeon experience in robotic cholecystectomies: a pilot study on breaking down technical performance.

BACKGROUND: Recent studies have correlated surgical skill measured by video-based assessment with improved clinical outcomes. Certain automated measures of operative performance in robotic surgery can be gathered beyond video review called objective performance indicators (OPIs). We explore the relationship between OPIs, surgeon experience, and postoperative recovery, hypothesizing that more efficient dissection will be associated with experience. METHODS: Fifty-six robotic cholecystectomies between February 2022 and March 2023 were recorded at a large tertiary referral center. Surgeon experience and clinical outcomes data from the EMR were obtained for all 56 cases with 10 completing the QOL survey. Two steps of robotic cholecystectomies were reviewed: dissection of Calot's triangle (DCT) and dissection of the gallbladder from the liver (DGL). Postoperative recovery was measured using the SF-36 well-being survey. Univariate analysis was conducted using Pearson's coefficient. RESULTS: Increased operative experience was associated with more efficient camera and instrument movements. DCT had 7 and DGL had 31 of 41 OPIs that correlated with experience. With respect to DGL, more experienced surgeons had reduced step duration and instrument path length and increased camera and instrument speeds. CONCLUSIONS: Several OPIs correlate with surgical experience and may form the basis of more instructive feedback for trainees and less experienced surgeons in improving intraoperative technique.

Kinematic data profile and clinical outcomes in robotic inguinal hernia repairs: a pilot study.

BACKGROUND: Surgical training requires clinical knowledge and technical skills to operate safely and optimize clinical outcomes. Technical skills are hard to measure. The Intuitive Data Recorder (IDR), (Sunnyvale, CA) allows for the measurement of technical skills using objective performance indicators (OPIs) from kinematic event data. Our goal was to determine whether OPIs improve with surgeon experience and whether they are correlated with clinical outcomes for robotic inguinal hernia repair (RIHR). METHODS: The IDR was used to record RIHRs from six surgeons. Data were obtained from 98 inguinal hernia repairs from February 2022 to February 2023. Patients were called on postoperative days 5-10 and asked to take the Carolina Comfort Scale (CCS) survey to evaluate acute clinical outcomes. A Pearson test was run to determine correlations between OPIs from the IDR with a surgeon's yearly RIHR experience and with CCS scores. Linear regression was then run for correlated OPIs. RESULTS: Multiple OPIs were correlated with surgeon experience. Specifically, for the task of peritoneal flap exploration, we found that 23 OPIs were significantly correlated with surgeons' 1-year RIHR case number. Total angular motion distance of the left arm instrument had a correlation of - 0.238 (95% CI - 0.417, - 0.042) for RIHR yearly case number. Total angular motion distance of right arm instrument was also negatively correlated with RIHR in 1 year with a correlation of - 0.242 (95% CI - 0.420, - 0.046). For clinical outcomes, wrist articulation of the surgeon's console positively correlated with acute sensation scores from the CCS with a correlation of 0.453 (95% CI 0.013, 0.746). CONCLUSIONS: This study defines multiple OPIs that correlate with surgeon experience and with outcomes. Using this knowledge, surgical simulation platforms can be designed to teach patterns to surgical trainees that are associated with increased surgical experience and with improved postoperative outcomes.

Tailored Feedback Based on Clinically Relevant Performance Metrics Expedites the Acquisition of Robotic Suturing Skills-An Unblinded Pilot Randomized Controlled Trial.

PURPOSE: Previously, we identified 8 objective suturing performance metrics highly predictive of urinary continence recovery after robotic-assisted radical prostatectomy. Here, we aimed to test the feasibility of providing tailored feedback based upon these clinically relevant metrics and explore the impact on the acquisition of robotic suturing skills. MATERIALS AND METHODS: Training surgeons were recruited and randomized to a feedback group or a control group. Both groups completed a baseline, midterm and final dry laboratory vesicourethral anastomosis (VUA) and underwent 4 intervening training sessions each, consisting of 3 suturing exercises. Eight performance metrics were recorded during each exercise: 4 automated performance metrics (derived from kinematic and system events data of the da Vinci® Robotic System) representing efficiency and console manipulation competency, and 4 suturing technical skill scores. The feedback group received tailored feedback (a visual diagram+verbal instructions+video examples) based on these metrics after each session. Generalized linear mixed model was used to compare metric improvement (Δ) from baseline to the midterm and final VUA. RESULTS: Twenty-three participants were randomized to the feedback group (11) or the control group (12). Demographic data and baseline VUA metrics were comparable between groups. The feedback group showed greater improvement than the control group in aggregate suturing scores at midterm (mean Δ feedback group 4.5 vs Δ control group 1.1) and final VUA (Δ feedback group 5.3 vs Δ control group 4.9). The feedback group also showed greater improvement in the majority of the included metrics at midterm and final VUA. CONCLUSIONS: Tailored feedback based on specific, clinically relevant performance metrics is feasible and may expedite the acquisition of robotic suturing skills.

Experts vs super-experts: differences in automated performance metrics and clinical outcomes for robot-assisted radical prostatectomy.

OBJECTIVES: To evaluate automated performance metrics (APMs) and clinical data of experts and super-experts for four cardinal steps of robot-assisted radical prostatectomy (RARP): bladder neck dissection; pedicle dissection; prostate apex dissection; and vesico-urethral anastomosis. SUBJECTS AND METHODS: We captured APMs (motion tracking and system events data) and synchronized surgical video during RARP. APMs were compared between two experience levels: experts (100-750 cases) and super-experts (2100-3500 cases). Clinical outcomes (peri-operative, oncological and functional) were then compared between the two groups. APMs and outcomes were analysed for 125 RARPs using multi-level mixed-effect modelling. RESULTS: For the four cardinal steps selected, super-experts showed differences in select APMs compared with experts (P < 0.05). Despite similar PSA and Gleason scores, super-experts outperformed experts clinically with regard to peri-operative outcomes, with a greater lymph node yield of 22.6 vs 14.9 nodes, respectively (P < 0.01), less blood loss (125 vs 130 mL, respectively; P < 0.01), and fewer readmissions at 30 days (1% vs 13%, respectively; P = 0.02). A similar but nonsignificant trend was seen for oncological and functional outcomes, with super-experts having a lower rate of biochemical recurrence compared with experts (5% vs 15%, respectively; P = 0.13) and a higher continence rate at 3 months (36% vs 18%, respectively; P = 0.14). CONCLUSION: We found that experts and super-experts differed significantly in select APMs for the four cardinal steps of RARP, indicating that surgeons do continue to improve in performance even after achieving expertise. We hope ultimately to identify associations between APMs and clinical outcomes to tailor interventions to surgeons and optimize patient outcomes.

Development and Validation of Objective Performance Metrics for Robot-Assisted Radical Prostatectomy: A Pilot Study.

PURPOSE: We explore and validate objective surgeon performance metrics using a novel recorder ("dVLogger") to directly capture surgeon manipulations on the da Vinci® Surgical System. We present the initial construct and concurrent validation study of objective metrics during preselected steps of robot-assisted radical prostatectomy. MATERIALS AND METHODS: Kinematic and events data were recorded for expert (100 or more cases) and novice (less than 100 cases) surgeons performing bladder mobilization, seminal vesicle dissection, anterior vesicourethral anastomosis and right pelvic lymphadenectomy. Expert/novice metrics were compared using mixed effect statistical modeling (construct validation). Expert reviewers blindly rated seminal vesicle dissection and anterior vesicourethral anastomosis using GEARS (Global Evaluative Assessment of Robotic Skills). Intraclass correlation measured inter-rater variability. Objective metrics were correlated to corresponding GEARS metrics using Spearman's test (concurrent validation). RESULTS: The performance of 10 experts (mean 810 cases, range 100 to 2,000) and 10 novices (mean 35 cases, range 5 to 80) was evaluated in 100 robot-assisted radical prostatectomy cases. For construct validation the experts completed operative steps faster (p <0.001) with less instrument travel distance (p <0.01), less aggregate instrument idle time (p <0.001), shorter camera path length (p <0.001) and more frequent camera movements (p <0.03). Experts had a greater ratio of dominant-to-nondominant instrument path distance for all steps (p <0.04) except anterior vesicourethral anastomosis. For concurrent validation the median experience of 3 expert reviewers was 300 cases (range 200 to 500). Intraclass correlation among reviewers was 0.6-0.7. For anterior vesicourethral anastomosis and seminal vesicle dissection, kinematic metrics had low associations with GEARS metrics. CONCLUSIONS: Objective metrics revealed experts to be more efficient and directed during preselected steps of robot-assisted radical prostatectomy. Objective metrics had limited associations to GEARS. These findings lay the foundation for developing standardized metrics for surgeon training and assessment.

Use of Automated Performance Metrics to Measure Surgeon Performance during Robotic Vesicourethral Anastomosis and Methodical Development of a Training Tutorial.

PURPOSE: We sought to develop and validate automated performance metrics to measure surgeon performance of vesicourethral anastomosis during robotic assisted radical prostatectomy. Furthermore, we sought to methodically develop a standardized training tutorial for robotic vesicourethral anastomosis. MATERIALS AND METHODS: We captured automated performance metrics for motion tracking and system events data, and synchronized surgical video during robotic assisted radical prostatectomy. Nonautomated performance metrics were manually annotated by video review. Automated and nonautomated performance metrics were compared between experts with 100 or more console cases and novices with fewer than 100 cases. Needle driving gestures were classified and compared. We then applied task deconstruction, cognitive task analysis and Delphi methodology to develop a standardized robotic vesicourethral anastomosis tutorial. RESULTS: We analyzed 70 vesicourethral anastomoses with a total of 1,745 stitches. For automated performance metrics experts outperformed novices in completion time (p <0.01), EndoWrist® articulation (p <0.03), instrument movement efficiency (p <0.02) and camera manipulation (p <0.01). For nonautomated performance metrics experts had more optimal needle to needle driver positioning, fewer needle driving attempts, a more optimal needle entry angle and less tissue trauma (each p <0.01). We identified 14 common robotic needle driving gestures. Random gestures were associated with lower efficiency (p <0.01), more attempts (p <0.04) and more trauma (p <0.01). The finalized tutorial contained 66 statements and figures. Consensus among 8 expert surgeons was achieved after 2 rounds, including among 58 (88%) after round 1 and 8 (12%) after round 2. CONCLUSIONS: Automated performance metrics can distinguish surgeon expertise during vesicourethral anastomosis. The expert vesicourethral anastomosis technique was associated with more efficient movement and less tissue trauma. Standardizing robotic vesicourethral anastomosis and using a methodically developed tutorial may help improve robotic surgical training.

Proctors exploit three-dimensional ghost tools during clinical-like training scenarios: a preliminary study.

PURPOSE: In this study, we examine three-dimensional (3D) proctoring tools (i.e., semitransparent ghost tools overlaid on the surgeon's field of view) on realistic surgical tasks. Additionally, we develop novel, quantitative measures of whether proctors exploit the additional capabilities offered by ghost tools. METHODS: Seven proctor-trainee pairs completed realistic surgical tasks such as tissue dissection and suturing in a live porcine model using 3D ghost tools on the da Vinci Xi Surgical System. The usability and effectiveness of 3D ghost tools were evaluated using objective measures of proctor performance based on proctor hand movements and button presses, as well as post-study questionnaires. RESULTS: Proctors exploited the capabilities of ghost tools, such as 3D hand movement (p < 0.001), wristedness (p < 0.001), finger pinch gestures (p < 0.001), and bimanual hand motions (p < 0.001). The median ghost tool excursion distances across proctors in the x-, y-, and z-directions were 57.6, 31.9, and 50.7, respectively. Proctors and trainees consistently evaluated the ghost tools as effective across multiple categories of mentoring. Trainees found ghost tools more helpful than proctors across all categories (p < 0.05). CONCLUSIONS: Proctors exploit the augmented capabilities of 3D ghost tools during clinical-like training scenarios. Additionally, both proctors and trainees evaluated ghost tools as effective mentoring tools, thereby confirming previous studies on simple, inanimate tasks. Based on this preliminary work, advanced mentoring technologies, such as 3D ghost tools, stand to improve current telementoring and training technologies in robot-assisted minimally invasive surgery.

Viewpoint matters: objective performance metrics for surgeon endoscope control during robot-assisted surgery.

BACKGROUND: Effective visualization of the operative field is vital to surgical safety and education. However, additional metrics for visualization are needed to complement other common measures of surgeon proficiency, such as time or errors. Unlike other surgical modalities, robot-assisted minimally invasive surgery (RAMIS) enables data-driven feedback to trainees through measurement of camera adjustments. The purpose of this study was to validate and quantify the importance of novel camera metrics during RAMIS. METHODS: New (n = 18), intermediate (n = 8), and experienced (n = 13) surgeons completed 25 virtual reality simulation exercises on the da Vinci Surgical System. Three camera metrics were computed for all exercises and compared to conventional efficiency measures. RESULTS: Both camera metrics and efficiency metrics showed construct validity (p < 0.05) across most exercises (camera movement frequency 23/25, camera movement duration 22/25, camera movement interval 19/25, overall score 24/25, completion time 25/25). Camera metrics differentiated new and experienced surgeons across all tasks as well as efficiency metrics. Finally, camera metrics significantly (p < 0.05) correlated with completion time (camera movement frequency 21/25, camera movement duration 21/25, camera movement interval 20/25) and overall score (camera movement frequency 20/25, camera movement duration 19/25, camera movement interval 20/25) for most exercises. CONCLUSIONS: We demonstrate construct validity of novel camera metrics and correlation between camera metrics and efficiency metrics across many simulation exercises. We believe camera metrics could be used to improve RAMIS proficiency-based curricula.

Face, content, and construct validity of four, inanimate training exercises using the da Vinci ® Si surgical system configured with Single-Site ™ instrumentation.

BACKGROUND: Validated training exercises are essential tools for surgeons as they develop technical skills to use robot-assisted minimally invasive surgical systems. The purpose of this study was to show face, content, and construct validity of four, inanimate training exercises using the da Vinci (®) Si surgical system configured with Single-Site (™) instrumentation. METHODS: New (N = 21) and experienced (N = 6) surgeons participated in the study. New surgeons (11 Gynecology [GYN] and 10 General Surgery [GEN]) had not completed any da Vinci Single-Site cases but may have completed multiport cases using the da Vinci system. They participated in this study prior to attending a certification course focused on da Vinci Single-Site instrumentation. Experienced surgeons (5 GYN and 1 GEN) had completed at least 25 da Vinci Single-Site cases. The surgeons completed four inanimate training exercises and then rated them with a questionnaire. Raw metrics and overall normalized scores were computed using both video recordings and kinematic data collected from the surgical system. RESULTS: The experienced surgeons significantly outperformed new surgeons for many raw metrics and the overall normalized scores derived from video review (p < 0.05). Only one exercise did not achieve a significant difference between new and experienced surgeons (p = 0.08) when calculating an overall normalized score using both video and advanced metrics derived from kinematic data. Both new and experienced surgeons rated the training exercises as appearing, to train and measure technical skills used during da Vinci Single-Site surgery and actually testing the technical skills used during da Vinci Single-Site surgery. CONCLUSIONS: In summary, the four training exercises showed face, content, and construct validity. Improved overall scores could be developed using additional metrics not included in this study. The results suggest that the training exercises could be used in an overall training curriculum aimed at developing proficiency in technical skills for surgeons new to da Vinci Single-Site instrumentation.

Construct validity of nine new inanimate exercises for robotic surgeon training using a standardized setup.

BACKGROUND: As more surgeons choose to complete procedures robotically, validated training tools are needed so that they can acquire and maintain the technical skills required to proficiently use robotic systems. The purpose of this study was to show construct validity of nine new inanimate training exercises for robot-assisted surgery. The inanimate training exercises were designed to span several core technical skills required to use a robotic system. METHODS: New (n = 30) and experienced (n = 11) robotic surgeons participated in the study. New robotic surgeons had not yet completed their first robotic surgery case and participated in this study before attending their robotic certification course. Experienced robotic surgeons had completed more than 200 robotic surgery cases. The raw scores from the exercises were reported so that other research groups could easily define custom proficiency levels. Example normalized scores that could be used in proficiency-based curricula were computed. These normalized scores balanced efficiency (completion time) and accuracy (exercise-specific errors) to measure performance. Finally, the setup was standardized using a custom docking model, which enabled consistent and repeatable completion of the inanimate exercises across surgeons. RESULTS: For all nine exercises, experienced robotic surgeons completed the exercises significantly faster than new robotic surgeons (p < 0.01). Similarly, experienced robotic surgeons achieved higher normalized scores than new robotic surgeons for all nine exercises (p < 0.01). Finally, consistent robot setup was achieved using the custom docking model based on an analysis of the robot kinematic data. CONCLUSIONS: In summary, all nine inanimate exercises showed construct validity. The results suggest that the inanimate exercises along with the custom docking model can be used as part of proficiency-based curricula to improve robotic surgeon training.

Objective performance indicators versus GEARS: an opportunity for more accurate assessment of surgical skill.

PURPOSE: Surgical skill evaluation that relies on subjective scoring of surgical videos can be time-consuming and inconsistent across raters. We demonstrate differentiated opportunities for objective evaluation to improve surgeon training and performance. METHODS: Subjective evaluation was performed using the Global evaluative assessment of robotic skills (GEARS) from both expert and crowd raters; whereas, objective evaluation used objective performance indicators (OPIs) derived from da Vinci surgical systems. Classifiers were trained for each evaluation method to distinguish between surgical expertise levels. This study includes one clinical task from a case series of robotic-assisted sleeve gastrectomy procedures performed by a single surgeon, and two training tasks performed by novice and expert surgeons, i.e., surgeons with no experience in robotic-assisted surgery (RAS) and those with more than 500 RAS procedures. RESULTS: When comparing expert and novice skill levels, OPI-based classifier showed significantly higher accuracy than GEARS-based classifier on the more complex dissection task (OPI 0.93 ± 0.08 vs. GEARS 0.67 ± 0.18; 95% CI, 0.16-0.37; p = 0.02), but no significant difference was shown on the simpler suturing task. For the single-surgeon case series, both classifiers performed well when differentiating between early and late group cases with smaller group sizes and larger intervals between groups (OPI 0.9 ± 0.08; GEARS 0.87 ± 0.12; 95% CI, 0.02-0.04; p = 0.67). When increasing the group size to include more cases, thereby having smaller intervals between groups, OPIs demonstrated significantly higher accuracy (OPI 0.97 ± 0.06; GEARS 0.76 ± 0.07; 95% CI, 0.12-0.28; p = 0.004) in differentiating between the early/late cases. CONCLUSIONS: Objective methods for skill evaluation in RAS outperform subjective methods when (1) differentiating expertise in a technically challenging training task, and (2) identifying more granular differences along early versus late phases of a surgeon learning curve within a clinical task. Objective methods offer an opportunity for more accessible and scalable skill evaluation in RAS.

Quantification of surgical workflow during robotic proctectomy.

BACKGROUND: Surgical workflow assessments offer insight regarding procedure variability. We utilised an objective method to evaluate workflow during robotic proctectomy (RP). METHODS: We annotated 31 RPs and used Spearman's correlation to measure the correlation of step time and step visit frequency with console time (CT) and total operative time (TOT). RESULTS: Strong correlations were seen with CT and step times for inferior mesenteric vein dissection and ligation (ρ = 0.60, ρ = 0.60), lateral-to-medial splenic flexure mobilisation (SFM) (ρ = 0.63), left rectal dissection (ρ = 0.64) and mesorectal division (ρ = 0.71). CT correlated strongly with medial-to-lateral (ρ = 0.75) and supracolic SFM visit frequency (ρ = 0.65). TOT correlated strongly with initial exposure time (ρ = 0.60), and medial-to-lateral (ρ = 0.67) and supracolic SFM visit frequency (ρ = 0.65). CONCLUSION: This study correlates surgical steps with CT and TOT through standardised annotation, providing an objective approach to quantify workflow.

Haptic Guidance and Haptic Error Amplification in a Virtual Surgical Robotic Training Environment.

Teleoperated robotic systems have introduced more intuitive control for minimally invasive surgery, but the optimal method for training remains unknown. Recent motor learning studies have demonstrated that exaggeration of errors helps trainees learn to perform tasks with greater speed and accuracy. We hypothesized that training in a force field that pushes the user away from a desired path would improve their performance on a virtual reality ring-on-wire task. Thirty-eight surgical novices trained under a no-force, guidance, or error-amplifying force field over five days. Completion time, translational and rotational path error, and combined error-time were evaluated under no force field on the final day. The groups significantly differed in combined error-time, with the guidance group performing the worst. Error-amplifying field participants did not plateau in their performance during training, suggesting that learning was still ongoing. Guidance field participants had the worst performance on the final day, confirming the guidance hypothesis. Observed trends also suggested that participants who had high initial path error benefited more from guidance. Error-amplifying and error-reducing haptic training for robot-assisted telesurgery benefits trainees of different abilities differently, with our results indicating that participants with high initial combined error-time benefited more from guidance and error-amplifying force field training.

A novel approach to quantifying surgical workflow in robotic-assisted lobectomy.

INTRODUCTION: Understanding surgical workflow is critical for optimizing efficiencies and outcomes; however, most research evaluating workflow is impacted by observer subjectivity, limiting its reproducibility, scalability, and actionability. To address this, we developed a novel approach to quantitatively describe workflow within robotic-assisted lobectomy (RL). We demonstrate the utility of this approach by analysing features of surgical workflow that correlate with procedure duration. METHODS: RL was deconstructed into 12 tasks by expert thoracic surgeons. Task start and stop times were annotated across videos of 10 upper RLs (5 right and 5 left). Markov Networks were used to estimate both the likelihood of transitioning from one task to another and each task-transition entropy (i.e. complexity). Associations between the frequency with which each task was revisited intraoperatively and procedure duration were assessed using Pearson's correlation coefficient. RESULTS: Entropy calculations identified fissure dissection and hilar node dissection as tasks with especially complex transitions, while mediastinal lymph node dissection and division of pulmonary veins were less complex. The number of transitions to three tasks significantly correlated with case duration (fissure dissection (R = 0.69, p = 0.01), dissect arteries (R = 0.59, p = 0.03), and divide arteries (R = 0.63, p = 0.03)). CONCLUSION: This pilot demonstrates the feasibility of objectively quantifying workflow between RL tasks and introduces entropy as a new metric of task-transition complexity. These innovative measures of surgical workflow enable detailed characterization of a given surgery and might indicate behaviour that impacts case progression. We discuss how these measures can serve as a foundation and be combined with relevant clinical information to better understand factors influencing surgical inefficiency.

Quantification of Surgical Workflow during Robotic Proctectomy.

Aim: Assessments of surgical workflow offer insight regarding procedure variability, case complexity and surgeon proficiency. We utilize an objective method to evaluate step-by-step workflow and step transitions during robotic proctectomy (RP). Methods: We annotated 31 RPs using a procedure-specific annotation card. Using Spearman's correlation, we measured strength of association of step time and step visit frequency with console time (CT) and total operative time (TOT). Results: Across 31 RPs, a mean (± standard deviation) of 49.0 (± 20.3) steps occurred per procedure. Mean CT and TOT were 213 (± 90) and 283 (± 108) minutes. Posterior mesorectal dissection required most visits (8.7 ± 5.0), while anastomosis required most time (18.0 [± 8.5] minutes). Inferior mesenteric vein (IMV) ligation required least visits (1.0 ± 0.0) and lowest duration (0.9 [± 0.5] minutes). Strong correlations were seen with CT and step times for IMV dissection and ligation (ρ = 0.60 for both), lateral-to-medial splenic flexure mobilization (SFM) (ρ = 0.63), left rectal dissection (ρ = 0.64) and mesorectal division (ρ = 0.71). CT correlated strongly with medial-to-lateral and supracolic SFM visit frequency (ρ = 0.75 and ρ = 0.65). There were strong correlations with TOT and initial exposure time (ρ = 0.60), as well as visit frequency for medial-to-lateral (ρ = 0.67) and supracolic SFM (ρ = 0.65). Descending colon mobilization was nodal, rectal mobilization convergent and rectal transection divergent. Conclusion: This study correlates individual surgical steps with CT and TOT through standardized annotation. It provides an objective approach to quantify workflow.

Differences Between Attending and Trainee Surgeon Performance Using Objective Performance Indicators During Robot-Assisted Lobectomy.

OBJECTIVE: Existing approaches for assessing surgical performance are subjective and prone to bias. In contrast, utilizing digital kinematic and system data from the surgical robot allows the calculation of objective performance indicators (OPIs) that may differentiate technical skill and competency. This study compared OPIs of trainees and attending surgeons to assess differences during robotic lobectomy (RL). METHODS: There were 50 cardiothoracic surgery residents and 7 attending surgeons who performed RL on a left upper lobectomy of an ex vivo perfused model. A novel recorder simultaneously captured video and data from the system and instruments. The lobectomy was annotated into discrete tasks, and OPIs were analyzed for both hands during 6 tasks: exposure of the superior pulmonary vein, upper division of the pulmonary artery and bronchus, and the stapling of these structures. RESULTS: There were significant differences between attendings and trainees in all tasks. Among 20 OPIs during exposure tasks, significant differences were observed for the left hand in 31 of 60 (52%) of OPIs and for the right hand in 42 of 60 (70%). During stapling tasks, significant differences were observed for the stapling hand in 28 of 60 (47%) of OPIs and for the nonstapling hand in 14 of 60 (25%). CONCLUSIONS: Use of a novel data and video recorder to generate OPIs for both hands revealed significant differences in the operative gestures performed by trainees compared to attendings during RL. This method of assessing performance has potential for establishing objective competency benchmarks and use for tracking progress.

Objective performance indicators of cardiothoracic residents are associated with vascular injury during robotic-assisted lobectomy on porcine models.

Surgical training relies on subjective feedback on resident technical performance by attending surgeons. A novel data recorder connected to a robotic-assisted surgical platform captures synchronized kinematic and video data during an operation to calculate quantitative, objective performance indicators (OPIs). The aim of this study was to determine if OPIs during initial task of a resident's robotic-assisted lobectomy (RL) correlated with bleeding during the procedure. Forty-six residents from the 2019 Thoracic Surgery Directors Association Resident Boot Camp completed RL on an ex vivo perfused porcine model while continuous video and kinematic data were recorded. For this pilot study, RL was segmented into 12 tasks and OPIs were calculated for the initial major task. Cases were reviewed for major bleeding events and OPIs of bleeding cases were compared to those who did not. Data from 42 residents were complete and included in the analysis. 10/42 residents (23.8%) encountered bleeding: 10/40 residents who started with superior pulmonary vein exposure and 0/2 residents who started with pulmonary artery exposure. Twenty OPIs for both hands were assessed during the initial task. Six OPIs related to instrument usage or smoothness of motion were significant for bleeding. Differences were statistically significant for both hands (p < 0.05). OPIs showing bimanual asymmetry indicated lower proficiency. This study demonstrates that kinematic and video analytics can establish a correlation between objective performance metrics and bleeding events in an ex vivo perfused lobectomy. Further study could assist in the development of focused exercises and simulation on objective domains to help improve overall performance and reducing complications during RL.

Ratio of Economy of Motion: A New Objective Performance Indicator to Assign Consoles During Dual-Console Robotic Proctectomy.

BACKGROUND: Our group investigates objective performance indicators (OPIs) to analyze robotic colorectal surgery. Analyses of OPI data are difficult in dual-console procedures (DCPs) as there is currently no reliable, efficient, or scalable technique to assign console-specific OPIs during a DCP. We developed and validated a novel metric to assign tasks to appropriate surgeons during DCPs. METHODS: A colorectal surgeon and fellow reviewed 21 unedited, dual-console proctectomy videos with no information to identify the operating surgeons. The reviewers watched a small number of random tasks and assigned "attending" or "trainee" to each task. Based on this sampling, the remainder of task assignments for each procedure was extrapolated. In parallel, we applied our newly developed OPI, ratio of economy of motion (rEOM), to assign consoles. Results from the 2 methods were compared. RESULTS: A total of 1811 individual surgical tasks were recorded during 21 proctectomy videos. A median of 6.5 random tasks (137 total) were reviewed during each video, and the remainder of task assignments were extrapolated based on the 7.6% of tasks audited. The task assignment agreement was 91.2% for video review vs rEOM, with rEOM providing ground truth. It took 2.5 hours to manually review video and assign tasks. Ratio of economy of motion task assignment was immediately available based on OPI recordings and automated calculation. DISCUSSION: We developed and validated rEOM as an accurate, efficient, and scalable OPI to assign individual surgical tasks to appropriate surgeons during DCPs. This new resource will be useful to everyone involved in OPI research across all surgical specialties.

Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics.

The basic hypothesis of producing a range of behaviors using a small set of motor commands has been proposed in various forms to explain motor behaviors ranging from basic reflexes to complex voluntary movements. Yet many fundamental questions regarding this long-standing hypothesis remain unanswered. Indeed, given the prominent nonlinearities and high dimensionality inherent in the control of biological limbs, the basic feasibility of a low-dimensional controller and an underlying principle for its creation has remained elusive. We propose a principle for the design of such a controller, that it endeavors to control the natural dynamics of the limb, taking into account the nature of the task being performed. Using this principle, we obtained a low-dimensional model of the hindlimb and a set of muscle synergies to command it. We demonstrate that this set of synergies was capable of producing effective control, establishing the viability of this muscle synergy hypothesis. Finally, by combining the low-dimensional model and the muscle synergies we were able to build a relatively simple controller whose overall performance was close to that of the system's full-dimensional nonlinear controller. Taken together, the results of this study establish that a low-dimensional controller is capable of simplifying control without degrading performance.

A Probabilistic Approach to Surgical Tasks and Skill Metrics.

Identifying and quantifying the activities that compose surgery is essential for effective interventions, computer-aided analyses and the advancement of surgical data science. For example, recent studies have shown that objective metrics (referred to as objective performance indicators, OPIs) computed during key surgical tasks correlate with surgeon skill and clinical outcomes. Unambiguous identification of these surgical tasks can be particularly challenging for both human annotators and algorithms. Each surgical procedure has multiple approaches, each surgeon has their own level of skill, and the initiation and termination of surgical tasks can be subject to interpretation. As such, human annotators and machine learning models face the same basic problem, accurately identifying the boundaries of surgical tasks despite variable and unstructured information. For use in surgeon feedback, OPIs should also be robust to the variability and diversity in this data. To mitigate this difficulty, we propose a probabilistic approach to surgical task identification and calculation of OPIs. Rather than relying on tasks that are identified by hard temporal boundaries, we demonstrate an approach that relies on distributions of start and stop times, for a probabilistic interpretation of when the task was performed. We first use hypothetical data to outline how this approach is superior to other conventional approaches. Then we present similar analyses on surgical data. We find that when surgical tasks are identified by their individual probabilities, the resulting OPIs are less sensitive to noise in the identification of the start and stop times. These results suggest that this probabilistic approach holds promise for the future of surgical data science.