Surgeon Performance Predicts Early Continence After Robot-Assisted Radical Prostatectomy

Nationwide Association of Surgical Performance of Minimally Invasive Esophagectomy With Patient Outcomes

Importance

Suboptimal surgical performance is hypothesized to be associated with less favorable patient outcomes in minimally invasive esophagectomy (MIE). Establishing this association may lead to programs that promote better surgical performance of MIE and improve patient outcomes.

Objective

To investigate associations between surgical performance and postoperative outcomes after MIE.

Design, Setting, and Participants

In this nationwide cohort study of 15 Dutch hospitals that perform more than 20 MIEs per year, 7 masked expert MIE surgeons assessed surgical performance using videos and a previously developed and validated competency assessment tool (CAT). Each hospital submitted 2 representative videos of MIEs performed between November 4, 2021, and September 13, 2022. Patients registered in the Dutch Upper Gastrointestinal Cancer Audit between January 1, 2020, and December 31, 2021, were included to examine patient outcomes.

Exposure

Hospitals were divided into quartiles based on their MIE-CAT performance score. Outcomes were compared between highest (top 25%) and lowest (bottom 25%) performing quartiles. Transthoracic MIE with gastric tube reconstruction.

Main Outcome and Measure

The primary outcome was severe postoperative complications (Clavien-Dindo ≥3) within 30 days after surgery. Multilevel logistic regression, with clustering of patients within hospitals, was used to analyze associations between performance and outcomes.

Results

In total, 30 videos and 970 patients (mean [SD] age, 66.6 [9.1] years; 719 men [74.1%]) were included. The mean (SD) MIE-CAT score was 113.6 (5.5) in the highest performance quartile vs 94.1 (5.9) in the lowest. Severe postoperative complications occurred in 18.7% (41 of 219) of patients in the highest performance quartile vs 39.2% (40 of 102) in the lowest (risk ratio [RR], 0.50; 95% CI, 0.24-0.99). The highest vs the lowest performance quartile showed lower rates of conversions (1.8% vs 8.9%; RR, 0.21; 95% CI, 0.21-0.21), intraoperative complications (2.7% vs 7.8%; RR, 0.21; 95% CI, 0.04-0.94), and overall postoperative complications (46.1% vs 65.7%; RR, 0.54; 95% CI, 0.24-0.96). The R0 resection rate (96.8% vs 94.2%; RR, 1.03; 95% CI, 0.97-1.05) and lymph node yield (mean [SD], 38.9 [14.7] vs 26.2 [9.0]; RR, 3.20; 95% CI, 0.27-3.21) increased with oncologic-specific performance (eg, hiatus dissection, lymph node dissection). In addition, a high anastomotic phase score was associated with a lower anastomotic leakage rate (4.6% vs 17.7%; RR, 0.14; 95% CI, 0.06-0.31).

Conclusions and Relevance

These findings suggest that better surgical performance is associated with fewer perioperative complications for patients with esophageal cancer on a national level. If surgical performance of MIE can be improved with MIE-CAT implementation, substantially better patient outcomes may be achievable.

Surgical Artificial Intelligence in Urology: Educational Applications

Surgical education has seen immense change recently. Increased demand for iterative evaluation of trainees from medical school to independent practice has led to the generation of an overwhelming amount of data related to an individual's competency. Artificial intelligence has been proposed as a solution to automate and standardize the ability of stakeholders to assess the technical and nontechnical abilities of a surgical trainee. In both the simulation and clinical environments, evidence supports the use of machine learning algorithms to both evaluate trainee skill and provide real-time and automated feedback, enabling a shortened learning curve for many key procedural skills and ensuring patient safety.

Surgical gestures can be used to assess surgical competence in robot-assisted surgery : A validity investigating study of simulated RARP

To collect validity evidence for the assessment of surgical competence through the classification of general surgical gestures for a simulated robot-assisted radical prostatectomy (RARP). We used 165 video recordings of novice and experienced RARP surgeons performing three parts of the RARP procedure on the RobotiX Mentor. We annotated the surgical tasks with different surgical gestures: dissection, hemostatic control, application of clips, needle handling, and suturing. The gestures were analyzed using idle time (periods with minimal instrument movements) and active time (whenever a surgical gesture was annotated). The distribution of surgical gestures was described using a one-dimensional heat map, snail tracks. All surgeons had a similar percentage of idle time but novices had longer phases of idle time (mean time: 21 vs. 15 s, p < 0.001). Novices used a higher total number of surgical gestures (number of phases: 45 vs. 35, p < 0.001) and each phase was longer compared with those of the experienced surgeons (mean time: 10 vs. 8 s, p < 0.001). There was a different pattern of gestures between novices and experienced surgeons as seen by a different distribution of the phases. General surgical gestures can be used to assess surgical competence in simulated RARP and can be displayed as a visual tool to show how performance is improving. The established pass/fail level may be used to ensure the competence of the residents before proceeding with supervised real-life surgery. The next step is to investigate if the developed tool can optimize automated feedback during simulator training.

Measures of performance and proficiency in robotic assisted surgery: a systematic review

Robotic assisted surgery (RAS) has seen a global rise in adoption. Despite this, there is not a standardised training curricula nor a standardised measure of performance. We performed a systematic review across the surgical specialties in RAS and evaluated tools used to assess surgeons' technical performance. Using the PRISMA 2020 guidelines, Pubmed, Embase and the Cochrane Library were searched systematically for full texts published on or after January 2020-January 2022. Observational studies and RCTs were included; review articles and systematic reviews were excluded. The papers' quality and bias score were assessed using the Newcastle Ottawa Score for the observational studies and Cochrane Risk Tool for the RCTs. The initial search yielded 1189 papers of which 72 fit the eligibility criteria. 27 unique performance metrics were identified. Global assessments were the most common tool of assessment (n = 13); the most used was GEARS (Global Evaluative Assessment of Robotic Skills). 11 metrics (42%) were objective tools of performance. Automated performance metrics (APMs) were the most widely used objective metrics whilst the remaining (n = 15, 58%) were subjective. The results demonstrate variation in tools used to assess technical performance in RAS. A large proportion of the metrics are subjective measures which increases the risk of bias amongst users. A standardised objective metric which measures all domains of technical performance from global to cognitive is required. The metric should be applicable to all RAS procedures and easily implementable. Automated performance metrics (APMs) have demonstrated promise in their wide use of accurate measures.

Navigating Now and Next: Recent Advances and Future Horizons in Robotic Radical Prostatectomy

Robotic-assisted radical prostatectomy (RARP) has become the leading approach for radical prostatectomy driven by innovations aimed at improving functional and oncological outcomes. The initial advancement in this field was transperitoneal multiport robotics, which has since undergone numerous technical modifications. These enhancements include the development of extraperitoneal, transperineal, and transvesical approaches to radical prostatectomy, greatly facilitated by the advent of the Single Port (SP) robot. This review offers a comprehensive analysis of these evolving techniques and their impact on RARP. Additionally, we explore the transformative role of artificial intelligence (AI) in digitizing robotic prostatectomy. AI advancements, particularly in automated surgical video analysis using computer vision technology, are unprecedented in their scope. These developments hold the potential to revolutionize surgeon feedback and assessment and transform surgical documentation, and they could lay the groundwork for real-time AI decision support during surgical procedures in the future. Furthermore, we discuss future robotic platforms and their potential to further enhance the field of RARP. Overall, the field of minimally invasive radical prostatectomy for prostate cancer has been an incubator of innovation over the last two decades. This review focuses on some recent developments in robotic prostatectomy, provides an overview of the next frontier in AI innovation during prostate cancer surgery, and highlights novel robotic platforms that may play an increasing role in prostate cancer surgery in the future.

Evaluation of objective tools and artificial intelligence in robotic surgery technical skills assessment: a systematic review

BACKGROUND

There is a need to standardize training in robotic surgery, including objective assessment for accreditation. This systematic review aimed to identify objective tools for technical skills assessment, providing evaluation statuses to guide research and inform implementation into training curricula.

METHODS

A systematic literature search was conducted in accordance with the PRISMA guidelines. Ovid Embase/Medline, PubMed and Web of Science were searched. Inclusion criterion: robotic surgery technical skills tools. Exclusion criteria: non-technical, laparoscopy or open skills only. Manual tools and automated performance metrics (APMs) were analysed using Messick's concept of validity and the Oxford Centre of Evidence-Based Medicine (OCEBM) Levels of Evidence and Recommendation (LoR). A bespoke tool analysed artificial intelligence (AI) studies. The Modified Downs-Black checklist was used to assess risk of bias.

RESULTS

Two hundred and forty-seven studies were analysed, identifying: 8 global rating scales, 26 procedure-/task-specific tools, 3 main error-based methods, 10 simulators, 28 studies analysing APMs and 53 AI studies. Global Evaluative Assessment of Robotic Skills and the da Vinci Skills Simulator were the most evaluated tools at LoR 1 (OCEBM). Three procedure-specific tools, 3 error-based methods and 1 non-simulator APMs reached LoR 2. AI models estimated outcomes (skill or clinical), demonstrating superior accuracy rates in the laboratory with 60 per cent of methods reporting accuracies over 90 per cent, compared to real surgery ranging from 67 to 100 per cent.

CONCLUSIONS

Manual and automated assessment tools for robotic surgery are not well validated and require further evaluation before use in accreditation processes.PROSPERO: registration ID CRD42022304901.

Technical surgical skill assessment of neurovascular bundle dissection and urinary continence recovery after robotic-assisted radical prostatectomy

Purpose

To examine the association between the quality of neurovascular bundle dissection and urinary continence recovery after robotic-assisted radical prostatectomy.

Materials and Methods

Patients who underwent RARPs from 2016 to 2018 in two institutions with ≥1-year postoperative follow-up were included. The primary outcomes were time to urinary continence recovery. Surgical videos were independently assessed by 3 blinded raters using the validated Dissection Assessment for Robotic Technique (DART) tool after standardized training. Cox regression was used to test the association between DART scores and urinary continence recovery while adjusting for relevant patient features.

Results

121 RARP performed by 23 surgeons with various experience levels were included. The median follow-up was 24 months (95% CI 20 - 28 months). The median time to continence recovery was 7.3 months (95% CI 4.7 - 9.8 months). After adjusting for patient age, higher scores of certain DART domains, specifically tissue retraction and efficiency, were significantly associated with increased odds of continence recovery (p<0.05).

Conclusions

Technical skill scores of neurovascular bundle dissection vary among surgeons and correlate with urinary continence recovery. Unveiling the specific robotic dissection skillsets which impact patient outcomes has the potential to focus surgical training.

The effect of bedside assistant technical performance on outcomes in robotic surgery

Technical performance in surgery has been associated with patient outcomes. Robotic surgery is unique in that both a console surgeon and bedside surgeon are required. A systematic review according to PRISMA guidelines identified all pertinent literature regarding skill level of the bedside assistant with regards to patient outcomes in robotic surgery. 10 studies met inclusion criteria. In all studies, the skill level of the assistant was based on experience, either by post-graduate year of the resident or number of cases previously performed by the assistant. Five studies reported significant, shorter operative times with increasing experience of the bedside assistant. No study reported a significant difference in postoperative outcomes. The existing literature fails to show improved patient outcomes with more experienced bedside assistants in robotic surgery. Metrics should be developed to measure actual technical performance of the bedside assistant rather than using arbitrary assessments of experience in future studies.

Assessing endovascular team performances in a hybrid room using the Black Box system: a prospective cohort study

BACKGROUND

The hybrid room (HR) is a complex, high-risk environment, requiring teams (surgeons, anesthesiologists, nurses, technologists) to master various skills, including the 'As Low As Reasonably Achievable' principle of radiation safety. This prospective single center cohort reports the first use of the Operating Room Black Box (ORBB) in a HR. This medical data recording system captures procedural and audio-visual data to facilitate structured team performance analysis.

METHODS

Patients planned for endovascular repair of an infrarenal abdominal aortic aneurysm (EVAR) or treatment of symptomatic iliac-femoral-popliteal atherosclerotic disease (Peripheral Vascular Interventions or PVI) were included. Validated measures and established assessment tools were used to assess (non-)technical skills, radiation safety performance and environmental distractions.

RESULTS

Six EVAR and sixteen PVI procedures were captured. Technical performance for one EVAR was rated 19/35 on the procedure-specific scale, below the 'acceptable' score of 21. Technical skills were rated above acceptable in all PVI procedures. Shared decision making and leadership were rated highly in 12/22 cases, whereas surgical communication and nurses' task management were rated low in 14/22 cases. Team members rarely stepped back from the C-arm during digital subtraction angiography. Radiation safety behavior was scored below 'acceptable' in 14/22 cases. A median (interquartile range) number of 12 (6-23) auditory distractions was observed per procedure.

CONCLUSIONS

The ORBB facilitates holistic workplace-based assessment of endovascular performance in a HR by combining objective assessment parameters and rating scale-based evaluations. Strengths and weaknesses were identified in team members' (non-)technical and radiation safety practices. This technology has the potential to improve vascular surgical practice, though human input remains crucial. (NCT04854278).

Surgomics: personalized prediction of morbidity, mortality and long-term outcome in surgery using machine learning on multimodal data

BACKGROUND

Personalized medicine requires the integration and analysis of vast amounts of patient data to realize individualized care. With Surgomics, we aim to facilitate personalized therapy recommendations in surgery by integration of intraoperative surgical data and their analysis with machine learning methods to leverage the potential of this data in analogy to Radiomics and Genomics.

METHODS

We defined Surgomics as the entirety of surgomic features that are process characteristics of a surgical procedure automatically derived from multimodal intraoperative data to quantify processes in the operating room. In a multidisciplinary team we discussed potential data sources like endoscopic videos, vital sign monitoring, medical devices and instruments and respective surgomic features. Subsequently, an online questionnaire was sent to experts from surgery and (computer) science at multiple centers for rating the features' clinical relevance and technical feasibility.

RESULTS

In total, 52 surgomic features were identified and assigned to eight feature categories. Based on the expert survey (n = 66 participants) the feature category with the highest clinical relevance as rated by surgeons was "surgical skill and quality of performance" for morbidity and mortality (9.0 ± 1.3 on a numerical rating scale from 1 to 10) as well as for long-term (oncological) outcome (8.2 ± 1.8). The feature category with the highest feasibility to be automatically extracted as rated by (computer) scientists was "Instrument" (8.5 ± 1.7). Among the surgomic features ranked as most relevant in their respective category were "intraoperative adverse events", "action performed with instruments", "vital sign monitoring", and "difficulty of surgery".

CONCLUSION

Surgomics is a promising concept for the analysis of intraoperative data. Surgomics may be used together with preoperative features from clinical data and Radiomics to predict postoperative morbidity, mortality and long-term outcome, as well as to provide tailored feedback for surgeons.

The association between video-based assessment of intraoperative technical performance and patient outcomes: a systematic review

BACKGROUND

Efforts to improve surgical safety and outcomes have traditionally placed little emphasis on intraoperative performance, partly due to difficulties in measurement. Video-based assessment (VBA) provides an opportunity for blinded and unbiased appraisal of surgeon performance. Therefore, we aimed to systematically review the existing literature on the association between intraoperative technical performance, measured using VBA, and patient outcomes.

METHODS

Major databases (Medline, Embase, Cochrane Database, and Web of Science) were systematically searched for studies assessing the association of intraoperative technical performance measured by tools supported by validity evidence with short-term (≤ 30 days) and/or long-term postoperative outcomes. Study quality was assessed using the Newcastle-Ottawa Scale. Results were appraised descriptively as study heterogeneity precluded meta-analysis.

RESULTS

A total of 11 observational studies were identified involving 8 different procedures in foregut/bariatric (n = 4), colorectal (n = 4), urologic (n = 2), and hepatobiliary surgery (n = 1). The number of surgeons assessed ranged from 1 to 34; patient sample size ranged from 47 to 10,242. High risk of bias was present in 5 of 8 studies assessing short-term outcomes and 2 of 6 studies assessing long-term outcomes. Short-term outcomes were reported in 8 studies (i.e., morbidity, mortality, and readmission), while 6 reported long-term outcomes (i.e., cancer outcomes, weight loss, and urinary continence). Better intraoperative performance was associated with fewer postoperative complications (6 of 7 studies), reoperations (3 of 4 studies), and readmissions (1 of 4 studies). Long-term outcomes were less commonly investigated, with mixed results.

CONCLUSION

Current evidence supports an association between superior intraoperative technical performance measured using surgical videos and improved short-term postoperative outcomes. Intraoperative performance analysis using video-based assessment represents a promising approach to surgical quality-improvement.

Association of Suturing Technical Skill Assessment Scores Between Virtual Reality Simulation and Live Surgery

Introduction: Robotic surgical performance, in particular suturing, has been linked to postoperative clinical outcomes. Before attempting live surgery, virtual reality (VR) simulators afford opportunities for training surgeons to learn fundamental technical skills. Herein, we evaluate the association of suturing technical skill assessments between VR simulation and live surgery, and functional clinical outcomes. Materials and Methods: Twenty surgeons completed a VR suturing exercise on the Mimic™ Flex VR simulator and the anterior vesicourethral anastomosis during robot-assisted radical prostatectomy (RARP). Three independent and blinded graders provided technical skill scores using a validated assessment tool. Correlations between VR and live scores were assessed by Spearman's correlation coefficients (ρ). In addition, 117 historic RARP cases from participating surgeons were extracted, and the association between VR technical skill scores and urinary continence recovery was assessed by a multilevel mixed-effects model. Results: A total of 20 (6 training and 14 expert) surgeons participated. Statistically significant correlations for scores provided between VR simulation and live surgery were found for overall and needle driving scores (ρ = 0.555, p = 0.011; ρ = 0.570, p = 0.009, respectively). A subanalysis performed on training surgeons found significant correlations for overall scores between VR simulation and live surgery (ρ = 0.828, p = 0.042). Expert cases with high VR needle driving scores had significantly greater continence recovery rates at 24 months after RARP (98.5% vs 84.9%, p = 0.028). Conclusions: Our study found significant correlations in technical scores between VR and live surgery, especially among training surgeons. In addition, we found that VR needle driving scores were associated with continence recovery after RARP. Our data support the association of skill assessments between VR simulation and live surgery and potential implications for clinical outcomes.

Bladder neck size and its association with urinary continence after robot-assisted radical prostatectomy

Objectives

This study aims to determine whether bladder neck size (BNS) measured during surgery is associated with urinary continence after robot-assisted radical prostatectomy.

Patients and Methods

Between June 2015 and March 2019, 365 consecutive eligible patients undergoing robot-assisted radical prostatectomy were enrolled into a prospective observational cohort study. The primary outcome was patient-reported urinary continence status at 1, 3, 6, 12 and 24 months postoperatively, with continence defined as 0 pad/day. The primary exposure was BNS (largest diameter) measured intraoperatively just before performance of vesicourethral anastomosis. Other covariates included age, body mass index, NCCN risk category, nerve-sparing, membranous urethral length measured intraoperatively and weight of the resected specimen.

Results

Well-preserved neurovascular bundle (bilateral/unilateral/none) was highly correlated with urinary continence status at every point after surgery. No difference could be seen between the group with BNS ≤17 mm and the >17-mm group at 1, 3 and 6 months after surgery, but there was better urinary rate of continence in narrow BNS group (≤17 mm) at 12 and 24 months after surgery. Multivariate analysis showed both nerve sparing and bladder neck diameter to be independent factors affecting urinary continence at 12 and 24 months after surgery.

Conclusion

Preservation of neurovascular bundles was associated with better urinary continence after surgery. Smaller BNS was associated with better urinary continence in late stages after surgery (12-24 months after surgery).

Outcome prediction in bariatric surgery through video-based assessment

INTRODUCTION

The relationship between intraoperative surgical performance scores and patient outcomes has not been demonstrated at a single-case level. The GEARS score is a Likert-based scale that quantifies robotic surgical proficiency in 5 domains. Given that even highly skilled surgeons can have variability in their skill among their cases, we hypothesized that at a patient level, higher surgical skill as determined by the GEARS score will predict individual patient outcomes.

METHODS

Patients undergoing robotic sleeve gastrectomy between July 2018 and January 2021 at a single-health care system were captured in a prospective database. Bivariate Pearson's correlation was used to compare continuous variables, one-way ANOVA for categorical variables compared with a continuous variable, and chi-square for two categorical variables. Significant variables in the univariable screen were included in a multivariable linear regression model. Two-tailed p-value < 0.05 was considered significant.

RESULTS

Of 162 patients included, 9 patients (5.5%) experienced a serious morbidity within 30 days. The average excess weight loss (EWL) was 72 ± 12% at 6 months and 74 ± 15% at 12 months. GEARS score was not significantly correlated with EWL at 6 months (p = 0.349), 12 months (p = 0.468), or serious morbidity (p = 0.848) on unadjusted analysis. After adjusting, total GEARS score was not correlated with serious morbidity (p = 0.914); however, GEARS score did predict EWL at 6 (p < 0.001) and 12 months (p < 0.001). All GEARS subcomponent scores, bimanual dexterity, depth perception, efficiency, force sensitivity, and robotic control were predictive of EWL at 6 months (p < 0.001) and 12 months (p < 0.001) on multivariable analysis.

CONCLUSION

For patients undergoing sleeve gastrectomy, surgical skill as assessed by the GEARS score was correlated with EWL, suggesting that better performance of a sleeve gastrectomy can result in improved postoperative weight loss.

Survival Analysis Using Surgeon Skill Metrics and Patient Factors to Predict Urinary Continence Recovery After Robot-assisted Radical Prostatectomy

BACKGROUND

It has been shown that metrics recorded for instrument kinematics during robotic surgery can predict urinary continence outcomes.

OBJECTIVE

To evaluate the contributions of patient and treatment factors, surgeon efficiency metrics, and surgeon technical skill scores, especially for vesicourethral anastomosis (VUA), to models predicting urinary continence recovery following robot-assisted radical prostatectomy (RARP).

DESIGN, SETTING, AND PARTICIPANTS

Automated performance metrics (APMs; instrument kinematics and system events) and patient data were collected for RARPs performed from July 2016 to December 2017. Robotic Anastomosis Competency Evaluation (RACE) scores during VUA were manually evaluated. Training datasets included: (1) patient factors; (2) summarized APMs (reported over RARP steps); (3) detailed APMs (reported over suturing phases of VUA); and (4) technical skills (RACE). Feature selection was used to compress the dimensionality of the inputs.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The study outcome was urinary continence recovery, defined as use of 0 or 1 safety pads per day. Two predictive models (Cox proportional hazards [CoxPH] and deep learning survival analysis [DeepSurv]) were used.

RESULTS AND LIMITATIONS

Of 115 patients undergoing RARP, 89 (77.4%) recovered their urinary continence and the median recovery time was 166 d (interquartile range [IQR] 82-337). VUAs were performed by 23 surgeons. The median RACE score was 28/30 (IQR 27-29). Among the individual datasets, technical skills (RACE) produced the best models (C index: CoxPH 0.695, DeepSurv: 0.708). Among summary APMs, posterior/anterior VUA yielded superior model performance over other RARP steps (C index 0.543-0.592). Among detailed APMs, metrics for needle driving yielded top-performing models (C index 0.614-0.655) over other suturing phases. DeepSurv models consistently outperformed CoxPH; both approaches performed best when provided with all the datasets. Limitations include feature selection, which may have excluded relevant information but prevented overfitting.

CONCLUSIONS

Technical skills and "needle driving" APMs during VUA were most contributory. The best-performing model used synergistic data from all datasets.

PATIENT SUMMARY

One of the steps in robot-assisted surgical removal of the prostate involves joining the bladder to the urethra. Detailed information on surgeon performance for this step improved the accuracy of predicting recovery of urinary continence among men undergoing this operation for prostate cancer.

The performance and optimum cutoff value for pelvic cavity index as a predictor of early continence after extraperitoneal single-port robotic radical prostatectomy: Role of pelvic anatomical characteristics

PURPOSE

To assess the value of pelvic cavity index (PCI), as an objective pelvimetry feature, to predict operative time, margin status and early urine continence after extraperitoneal single-port robotic radical prostatectomy (RP). We sought to define an optimal cutoff point for PCI in predicting postoperative outcomes.

METHODS

Data on 94 patients who underwent extraperitoneal single-port robotic RP and had preoperative cross-sectional imaging were enrolled. PCI was calculated as (Pelvic inlet diameter×Pelvic outlet diameter)/(Pelvic depth). The predictive value of PCI on operative time, surgical margin status and 3-month urinary continence recovery was assessed using regression models. To report the optimum cutoff value, on ROC analysis, we calculated the performance of PCI cutoff points ranging from 5.56 to 10.80 cm by every 0.01 increment.

RESULTS

No significant associations were noted between clinical characteristics (including PCI) and operative time. Similarly, other than pathological stage, no clinical variables (including PCI) were predictive of positive surgical margin. However, a higher PCI was associated with a significantly higher rates of continence 3-month after surgery (OR 2.44 (1.75 - 5.33); p= 0.01). On ROC- analysis, a PCI cutoff value=8.21 cm yielded the best accuracy (AUC= 0.733, %95 CI 0.615-0.851; p=0.001). No association was noted between variables and 6-month continence rate.

CONCLUSION

Using a single-port robotic system, operative time, positive surgical margin rate and long-term continence after prostatectomy would be independent of bony pelvis cavity. However, a higher PCI is associated with a higher rate of early continence after the surgery. PCI at a cutoff of 8.21 cm has the optimum performance to predict postoperative urine continence recovery. If validated, this information may be helpful regarding patient counseling before single-port robotic RP.

Comparison of urinary and sexual patient-reported outcomes between open radical prostatectomy and robot-assisted radical prostatectomy: a propensity score matched, population-based study in Victoria

Background

Robot-assisted radical prostatectomy (RARP) rates have been increasing worldwide despite a lack of evidence of superior patient-reported outcomes (PROs) compared to open radical prostatectomy (ORP).

Methods

This retrospective study included men who contributed data to the Prostate Cancer Outcomes Registry-Victoria (PCOR-Vic), underwent ORP or RARP between January 2014 and May 2018, and completed the EPIC-26 questionnaire 12 months post-surgery. Urinary and sexual bother items, the urinary incontinence domain score, the urinary irritative/obstructive domain score, the sexual domain score and the pad usage item from the EPIC-26 questionnaire were compared between the two cohorts. Unmatched and propensity score matched cohorts were used to determine if there were differences in urinary and sexual PROs between ORP and RARP after accounting for the patient case-mix and surgeon characteristics.

Results

Of 3826 patients undergoing radical prostatectomy (RP), 1047 received ORP and 2779 received RARP. Propensity score matching reduced the magnitude of the observed differences in four out of six outcomes (urinary bother, urinary incontinence domain, pad usage and sexual domain). Using a propensity score matched cohort, there were no statistically significant differences for RARP patients, compared to ORP patients, in terms of urinary bother (Rd = 0.47%, P = 0.707), urinary incontinence domain scores (Coeff = − 0.84, P = 0.506), urinary irritative/obstructive domain scores (Coeff = 1.03, P = 0.105), pad usage (Rd = − 0.75%, P = 0.771) and sexual bother (Rd = − 0.89%, P = 0.731). RARP patients had slightly higher sexual domain scores (Coeff = 3.65, P = 0.005).

Conclusion

There were no differences in urinary PROs between ORP and RARP when assessed 12 months post-surgery. The sexual domain slightly favoured RARP, however this was not deemed clinically significant.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-00966-0.

The role of AI technology in prediction, diagnosis and treatment of colorectal cancer

Artificial intelligence (AI) is a fascinating new technology that incorporates machine learning and neural networks to improve existing technology or create new ones. Potential applications of AI are introduced to aid in the fight against colorectal cancer (CRC). This includes how AI will affect the epidemiology of colorectal cancer and the new methods of mass information gathering like GeoAI, digital epidemiology and real-time information collection. Meanwhile, this review also examines existing tools for diagnosing disease like CT/MRI, endoscopes, genetics, and pathological assessments also benefitted greatly from implementation of deep learning. Finally, how treatment and treatment approaches to CRC can be enhanced when applying AI is under discussion. The power of AI regarding the therapeutic recommendation in colorectal cancer demonstrates much promise in clinical and translational field of oncology, which means better and personalized treatments for those in need.

The influence of reviewer's occupation on the skill assessment of urethrovesical anastomosis in robot-assisted radical prostatectomy

INTRODUCTION

In recent years, crowd-sourced assessments have been reported as a timesaving, cost-efficient, and practicable method of surgical skill evaluation. However, the differences in the assessment of surgical skills by the individual reviewers cannot be further examined in terms of characteristics of the reviewers because they are usually anonymously and randomly selected. This study aimed to reveal the effects of reviewers' occupations on their assessment of a surgeon's skill.

METHODS

In total, 42 urologists, 19 paramedics, 73 medical students, and 28 non-medical personnel used the Global Evaluative Assessment of Robotic Skills (GEARS) validated robotic surgery rating tool to assess the surgical skill of surgeons in nine edited video clips of complete urethrovesical anastomosis during a robot-assisted radical prostatectomy. The total GEARS scores of the four groups of reviewers were compared, and the similarities and the differences between the ratings of the urologists group and those of the other three groups were subsequently investigated.

RESULTS

The rankings of video clips in the order of GEARS scores were very similar in each group, and a strong positive correlation (R² values >0.8) was observed between the scores assigned by the urologists group and those assigned by the other three groups.

CONCLUSION

Our findings indicate that the crude evaluation of robot-assisted urethrovesical anastomosis is not affected by the reviewers' occupations. Non-medical personnel may be able to provide a rudimentary screening evaluation of surgical skill.

Innovations in Urologic Surgical Training

PURPOSE OF REVIEW

This review aims to summarize innovations in urologic surgical training in the past 5 years.

RECENT FINDINGS

Many assessment tools have been developed to objectively evaluate surgical skills and provide structured feedback to urologic trainees. A variety of simulation modalities (i.e., virtual/augmented reality, dry-lab, animal, and cadaver) have been utilized to facilitate the acquisition of surgical skills outside the high-stakes operating room environment. Three-dimensional printing has been used to create high-fidelity, immersive dry-lab models at a reasonable cost. Non-technical skills such as teamwork and decision-making have gained more attention. Structured surgical video review has been shown to improve surgical skills not only for trainees but also for qualified surgeons. Research and development in urologic surgical training has been active in the past 5 years. Despite these advances, there is still an unfulfilled need for a standardized surgical training program covering both technical and non-technical skills.

Quantifying the "Assistant Effect" in Robotic-Assisted Radical Prostatectomy (RARP): Measures of Technical Performance

PURPOSE

Surgeons are reliant on the bedside assistant during robotic surgeries. Using a modified global rating scale (GRS), we aim to assess the association between an assistant's technical skill on surgeon performance in Robotic-Assisted Radical Prostatectomy (RARP).

METHODS

Prospective, intraoperative video from RARP cases at three centers were collected. Baseline demographic and RARP-experience data were collected from participating surgeons and trainees. The dissection of the prostatic pedicle and neurovascular bundle step (NVB) was analyzed. Expert analysts scored the console surgeon performance using the Global Evaluative Assessment of Robotic Skills (GEARS), and the bedside assistant performance using a modified Objective Structured Assessment of Technical Skills (aOSATS). The primary outcome is the association between console surgeon performance, as measured by GEARS, and assistant skill, as measured by aOSATS. Spearman's rho correlations were used to test the relationship between assistant and surgeon technical performance, and a multivariable linear regression model was created to test this association while controlling for patient factors.

RESULTS

92 RARP cases were available for the analysis, comprising 14 console surgeons and 22 different bedside assistants. In only 5 (5.4%) cases, the neurovascular bundle step was completed by a trainee, and in 13 (14.1%) of cases, a staff-level surgeon acted as the bedside assistant. aOSATS score was significantly associated with robotic console experience (P = 0.011), and prior laparoscopic experience (P < 0.001). Assistant aOSATS score showed a weak but significant correlation with surgeon GEARS score during the neurovascular bundle step (spearman's rho = 0.248, P = 0.028). On linear regression, aOSATS remained a significant predictor of console surgeon performance (P = 0.016), after controlling for patient age and BMI, prostate volume, tumor stage, and presence of nerve-sparing.

CONCLUSIONS

This is the first study to assess the association between assistant technical skill and surgeon performance in RARP. Additionally, we have provided validity evidence for a modified OSATS global rating scale for training and assessing bedside assistant performance.

Surgical techniques to improve continence recovery after robot-assisted radical prostatectomy

Radical prostatectomy directly affects urinary continence dynamics with incontinence being a major factor in patients’ quality of life, social and psychological status. In order to help maintain continence after robot-assisted radical prostatectomy (RARP), a number of surgical techniques have been described. In the present narrative review, we summarize the surgical techniques that have been applied during RARP and their effects on incontinence rates and time to continence recovery.

Surgical techniques to improve continence recovery after robot-assisted radical prostatectomy

Radical prostatectomy directly affects urinary continence dynamics with incontinence being a major factor in patients' quality of life, social and psychological status. In order to help maintain continence after robot-assisted radical prostatectomy (RARP), a number of surgical techniques have been described. In the present narrative review, we summarize the surgical techniques that have been applied during RARP and their effects on incontinence rates and time to continence recovery.

Current Trends in Artificial Intelligence Application for Endourology and Robotic Surgery

With the advent of electronic medical records and digitalization of health care over the past 2 decades, artificial intelligence (AI) has emerged as an enabling tool to manage complex datasets and deliver streamlined data-driven patient care. AI algorithms have the ability to extract meaningful signal from complex datasets through an iterative process akin to human learning. Through advancements over the past decade in deep learning, AI-driven innovations have accelerated applications in health care. Herein, the authors explore the development of these emerging AI technologies, focusing on the application of AI to endourology and robotic surgery.

Machine learning analyses of automated performance metrics during granular sub-stitch phases predict surgeon experience

Automated performance metrics objectively measure surgeon performance during a robot-assisted radical prostatectomy. Machine learning has demonstrated that automated performance metrics, especially during the vesico-urethral anastomosis of the robot-assisted radical prostatectomy, are predictive of long-term outcomes such as continence recovery time. This study focuses on automated performance metrics during the vesico-urethral anastomosis, specifically on stitch versus sub-stitch levels, to distinguish surgeon experience. During the vesico-urethral anastomosis, automated performance metrics, recorded by a systems data recorder (Intuitive Surgical, Sunnyvale, CA, USA), were reported for each overall stitch (C^total) and its individual components: needle handling/targeting (C¹), needle driving (C²), and suture cinching (C³) (Fig 1, A). These metrics were organized into three datasets (GlobalSet [whole stitch], RowSet [independent sub-stitches], and ColumnSet [associated sub-stitches] (Fig 1, B) and applied to three machine learning models (AdaBoost, gradient boosting, and random forest) to solve two classifications tasks: experts (≥100 cases) versus novices (<100 cases) and ordinary experts (≥100 and <2,000 cases) versus super experts (≥2,000 cases). Classification accuracy was determined using analysis of variance. Input features were evaluated through a Jaccard index. From 68 vesico-urethral anastomoses, we analyzed 1,570 stitches broken down into 4,708 sub-stitches. For both classification tasks, ColumnSet best distinguished experts (n = 8) versus novices (n = 9) and ordinary experts (n = 5) versus super experts (n = 3) at an accuracy of 0.774 and 0.844, respectively. Feature ranking highlighted Endowrist articulation and needle handling/targeting as most important in classification. Surgeon performance measured by automated performance metrics on a granular sub-stitch level more accurately distinguishes expertise when compared with summary automated performance metrics over whole stitches.

The Effect of Feedback on Surgeon Performance: A Narrative Review

Surgeons play a critical role in the healthcare community and provide a service that can tremendously impact patients' livelihood. However, there are relatively few means for monitoring surgeons' performance quality and seeking improvement. Surgeon-level data provide an important metric for quality improvement and future training. A narrative review was conducted to analyze the utility of providing surgeons direct feedback on their individual performance. The articles selected identified means of collecting surgeon-specific data, suggested ways to report this information, identified pertinent gaps in the field, and concluded the results of giving feedback to surgeons. There is a relative sparsity of data pertaining to the effect of providing surgeons with information regarding their individual performance. However, the literature available does suggest that providing surgeons with individualized feedback can help make meaningful improvements in the quality of practice and can be done in a way that is safe for the surgeons' reputation.

Development and Evaluation of a Novel Instrument to Measure Severity of Intraoperative Events Using Video Data

OBJECTIVE

To develop and evaluate a novel instrument to measure SEVERE processes using video data.

BACKGROUND

Surgical video data can serve an important role in understanding the relationship between intraoperative events and postoperative outcomes. However, a standard tool to measure severity of intraoperative events is not yet available.

METHODS

Items to be included in the instrument were identified through literature and video reviews. A committee of experts guided item reduction, including pilot tests and revisions, and determined weighted scores. Content validity was evaluated using a validated sensibility questionnaire. Inter-rater reliability was assessed by calculating intraclass correlation coefficient. Construct validity was evaluated on a sample of 120 patients who underwent laparoscopic Roux-en-Y gastric bypass procedure, in which comprehensive video data was obtained.

RESULTS

SEVERE index measures severity of 5 event types using ordinal scales. Each intraoperative event is given a weighted score out of 10. Inter-rater reliability was excellent [0.87 (95%-confidence interval, 0.77-0.92)]. In a sample of consecutive 120 patients undergoing gastric bypass procedures, a median of 12 events [interquartile range (IQR) 9-18] occurred per patient and bleeding was the most frequent type (median 10, IQR 7-14). The median SEVERE score per case was 11.3 (IQR 8.3-16.9). In risk-adjusted multivariable regression models, history of previous abdominal surgery (P = 0.02) and body mass index (P = 0.005) were associated with SEVERE scores, demonstrating construct validity evidence.

CONCLUSION

The SEVERE index may prove to be a useful instrument in identifying patients with high risk of developing postoperative complications.

A Prospective, Observational, Multicentre Study Concerning Nontechnical Skills in Robot-assisted Radical Cystectomy Versus Open Radical Cystectomy

Introduction and hypotheses

valuation of surgical skills, both technical and nontechnical, is possible through observations and video analysis. Besides technical failures, adverse outcomes in surgery can also be related to hampered communication, moderate teamwork, lack of leadership, and loss of situational awareness. Even though some surgeons are convinced about nontechnical skills being an important part of their professionalisation, there is paucity of data about a possible relationship between nontechnical skills and surgical outcome. In robot-assisted surgery, the surgeon sits behind the console and is at a remote position from the surgical field and team, making communication more important than in open surgery and conventional laparoscopy. A lack of structured research makes it difficult to assess the value of the different analysis methods for nontechnical skills, particularly in robot-assisted surgery. Our hypothesis includes the following: (1) introduction of robot-assisted surgery leads to an initial decay in nontechnical skills behaviour during the learning curve of the team, (2) nontechnical skills behaviour is more explicitly expressed in experienced robot-assisted surgery teams than in experienced open surgery teams, and (3) introduction of robot-assisted surgery leads to the development of different forms of nontechnical skills behaviour compared with open surgery.

Design

This study is a prospective, observational, multicentre, nonrandomised, case-control study including bladder cancer patients undergoing either an open radical cystectomy or a robot-assisted radical cystectomy at the Catharina Hospital Eindhoven, the Netherlands, or at the Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital Amsterdam. All patients are eligible for inclusion; there are no exclusion criteria. The Catharina Hospital Eindhoven, the Netherlands, performs on average 35 radical cystectomies a year. The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital Amsterdam, performs on average 100 radical cystectomies a year.

Protocol overview

The choice of treatment is at the discretion of the patient and the surgeon. Patient results will be obtained prospectively. Pathology results as well as complications occurring within 90 d following surgery will be registered. Surgical complications will be registered according to the Clavien-Dindo system.

Measurements

Nontechnical skills will be observed using five different methods: (1) NOTSS: Nontechnical Skills for Surgeons; (2) Oxford NOTECHS II: a modified theatre team nontechnical skills scoring system; (3) OTAS: Observational Teamwork Assessment for Surgery; (4) Interpersonal and Cognitive Assessment for Robotic Surgery (ICARS): evaluation of nontechnical skills in robotic surgery; and (5) analysis of human factors. Technical skills in robot-assisted radical cystectomy will be analysed using two different methods: (1) GEARS: Global Evaluative Assessment of Robotic Skill and (2) GERT: Generic Error Rating Tool.

Safety criteria and reporting

Formal ethical approval has been provided by Medical research Ethics Committees United (MEC-U), The Netherlands (reference number W19.048). We hope to present the results of this study to the scientific community at conferences and in peer-reviewed journals.

Statistical analysis

Frequency statistics will be calculated for patient demographical data, and a Shapiro-Wilk test with p > 0.05 will be used to define normal distribution. Univariate analysis will be conducted to test for statistically significant differences in observation scores between open radical cystectomy and robot-assisted radical cystectomy cohorts across all variables, using independent sample t tests and Mann-Whitney U testing, as appropriate. A variable-selection strategy will be used to create multivariate models. Binary logistic regression will be conducted to calculate odds ratios and 95% confidence intervals for significant predictors on univariate analysis and clinically relevant covariates. Statistical significance is set at p < 0.05 based on a two-tailed comparison.

Summary

This study uses a structured approach to the analysis of nontechnical skills using extracorporeal videos of both open radical cystectomy and robot-assisted radical cystectomy surgeries, in order to obtain detailed data on nontechnical skills during open and minimally invasive surgeries. The results of this study could possibly be used to develop team-training programmes, specifically for the introduction of the surgical robot in relation to changes in nontechnical skills. Additional analysis of technical skills using the intracorporeal footage of the surgical robot will be used to elucidate the role of surgical skills and surgical events in nontechnical skills.

Are basic robotic surgical skills transferable from the simulator to the operating room? A randomized, prospective, educational study

INTRODUCTION

We aimed to assess the transferability of basic robotic skills from the simulator to the operating room (OR) while performing robotic-assisted radical prostatectomy (RARP).

METHODS

Fourteen urology residents were randomized into two groups: group A was required to practice three sessions (nine tasks each) on the simulator, whereas group B was required to practice (same nine tasks) until they reached competency. Both groups were recorded while practicing on the da Vinci Surgical Skills Simulator. Both groups were then recorded while performing bladder mobilization during RARP. Senior residents from both groups were also recorded while performing urethro-vesical anastomosis during RARP. Recordings were assessed blindly using the validated Global Evaluative Assessment of Robotic Skills (GEARS) tool by C-SATS. Spearman's correlation coefficient (rho) was used to assess correlation between GEARS scores from practice sessions on the da Vinci Simulator and the GEARS scores from bladder mobilization and urethro-vesical anastomosis during RARP.

RESULTS

There was no difference in total GEARS scores between the two groups in the OR. Total GEARS scores for "ring and rail 2" and "suture sponge" tasks correlated with the total GEARS scores during urethro-vesical anastomosis (rho=0.86, p=0.007; rho=0.90, p=0.002, respectively). GEARS' efficiency component during "energy and dissection" task on the da Vinci Simulator correlated with GEARS' efficiency component during bladder mobilization (rho=0.62, p=0.03). GEARS' force sensitivity component during "ring and rail 2" and "dots and needles" tasks on the da Vinci Simulator correlated with GEARS' force sensitivity component during bladder mobilization (rho=0.58, p=0.047; rho =0.65, p=0.02, respectively).

CONCLUSIONS

Objective assessments of urology residents on the da Vinci Surgical Skills Simulator tasks ring and rail 2 and suture sponge correlated with their objective assessments of bladder mobilization and urethro-vesical anastomosis. Therefore, basic robotic skills could be transferred from the simulator to the OR.

Current Educational Interventions for Improving Technical Skills of Urology Trainees in Endourological Procedures: A Systematic Review

Objective: Endourology continues to grow with the introduction of new technologies into clinical practice. Simulators and training models have been developed to improve comfort and proficiency in endoscopic procedures. The purpose of this systematic review was to examine the current educational interventions utilized to improve the performance of endourology trainees and to critically appraise the strengths and limitations of each. Methods: A search of the Ovid MEDLINE, EMBASE, PsycINFO, and the Cochrane Library databases was performed to identify literature focused on current educational interventions for improving technical skills of trainees in endourologic procedures. The Medical Education Research Study Quality Instrument (MERSQI) was used to evaluate the methodological quality of the abstracted articles. Results: Of the 2236 articles identified, 22 met the inclusion criteria. The types of educational interventions included: bench/wet lab models, virtual reality simulators, and instructional courses. Metrics used to quantify the impact of these interventions include global rating scales, Objective Structured Assessment of Technical Skills (OSATS) scores, and task-specific checklists. The setting of these evaluations comprises both virtual reality simulators and live surgery. Conclusions: In the surgical education literature, simulation-based training and assessment continues to play a prominent role in urologic training. The educational interventions highlighted in this review address various aspects of endourology, from stone management to transurethral resection. Additional work is needed to correlate technical performance in clinical and nonclinical settings with patient outcomes and develop a focused approach to nontechnical skill training.

Analysis of the video motion tracking system "Kinovea" to assess surgical movements during robot-assisted radical prostatectomy

BACKGROUNDS

Robot-assisted surgery facilitated the possibility to evaluate the surgeon's skills by recording and evaluating the robot surgical images. The aim of this study was to investigate the possibility of using a computer programme (Kinovea) for objective assessment of surgical movements in previously recorded in existing robot-assisted radical prostatectomy (RARP) videos.

METHODS

Twelve entire RARP procedures were analysed by a trained researcher using the computer programme "Kinovea" to perform semi-automated assessment of surgical movements.

RESULTS

Data analysis showed Kinovea was on average able to automatically assess only 22% of the total surgical duration per video of the robot-assisted surgery. On average, it lasted 4 hours of continued monitoring by the researcher to assess one RARP using Kinovea.

CONCLUSION

Although we proved it is technically possible to use the Kinovea system in retrospective analysis of surgical movement in robot-assisted surgery, the acquired data do not give a comprehensive enough analysis of the video to be used in skills assessment.

Video review for measuring and improving skill in urological surgery

Interest is growing within the urological surgery community for objective assessments of technical skill. Surgical video review relies on the use of objective assessment tools to evaluate both global and procedure-specific skill. These evaluations provide structured feedback to surgeons with the aim of improving technique, which has been associated with patient outcomes. Currently, skill assessments can be performed by using expert peer-review, crowdsourcing or computer-based methods. Given the relationship between skill and patient outcomes, surgeons might be required in the future to provide empirical evidence of their technical skill for certification, employment, credentialing and quality improvement. Interventions such as coaching and skills workshops incorporating video review might help surgeons improve their skill, with the ultimate goal of improving patient outcomes.

Incorporation and validation of clinically relevant performance metrics of simulation (CRPMS) into a novel full-immersion simulation platform for nerve-sparing robot-assisted radical prostatectomy (NS-RARP) utilizing three-dimensional printing and hydrogel casting technology

OBJECTIVES

To incorporate and validate clinically relevant performance metrics of simulation (CRPMS) into a hydrogel model for nerve-sparing robot-assisted radical prostatectomy (NS-RARP).

MATERIALS AND METHODS

Anatomically accurate models of the human pelvis, bladder, prostate, urethra, neurovascular bundle (NVB) and relevant adjacent structures were created from patient MRI by injecting polyvinyl alcohol (PVA) hydrogels into three-dimensionally printed injection molds. The following steps of NS-RARP were simulated: bladder neck dissection; seminal vesicle mobilization; NVB dissection; and urethrovesical anastomosis (UVA). Five experts (caseload >500) and nine novices (caseload <50) completed the simulation. Force applied to the NVB during the dissection was quantified by a novel tension wire sensor system fabricated into the NVB. Post-simulation margin status (assessed by induction of chemiluminescent reaction with fluorescent dye mixed into the prostate PVA) and UVA weathertightness (via a standard 180-mL leak test) were also assessed. Objective scoring, using Global Evaluative Assessment of Robotic Skills (GEARS) and Robotic Anastomosis Competency Evaluation (RACE), was performed by two blinded surgeons. GEARS scores were correlated with forces applied to the NVB, and RACE scores were correlated with UVA leak rates.

RESULTS

The expert group achieved faster task-specific times for nerve-sparing (P = 0.007) and superior surgical margin results (P = 0.011). Nerve forces applied were significantly lower for the expert group with regard to maximum force (P = 0.011), average force (P = 0.011), peak frequency (P = 0.027) and total energy (P = 0.003). Higher force sensitivity (subcategory of GEARS score) and total GEARS score correlated with lower nerve forces (total energy in Joules) applied to NVB during the simulation with a correlation coefficient (r value) of -0.66 (P = 0.019) and -0.87 (P = 0.000), respectively. Both total and force sensitivity GEARS scores were significantly higher in the expert group compared to the novice group (P = 0.003). UVA leak rate highly correlated with total RACE score r value = -0.86 (P = 0.000). Mean RACE scores were also significantly different between novices and experts (P = 0.003).

CONCLUSION

We present a realistic, feedback-driven, full-immersion simulation platform for the development and evaluation of surgical skills pertinent to NS-RARP. The correlation of validated objective metrics (GEARS and RACE) with our CRPMS suggests their application as a novel method for real-time assessment and feedback during robotic surgery training. Further work is required to assess the ability to predict live surgical outcomes.

Artificial intelligence and robotics: a combination that is changing the operating room

PURPOSE

The aim of the current narrative review was to summarize the available evidence in the literature on artificial intelligence (AI) methods that have been applied during robotic surgery.

METHODS

A narrative review of the literature was performed on MEDLINE/Pubmed and Scopus database on the topics of artificial intelligence, autonomous surgery, machine learning, robotic surgery, and surgical navigation, focusing on articles published between January 2015 and June 2019. All available evidences were analyzed and summarized herein after an interactive peer-review process of the panel.

LITERATURE REVIEW

The preliminary results of the implementation of AI in clinical setting are encouraging. By providing a readout of the full telemetry and a sophisticated viewing console, robot-assisted surgery can be used to study and refine the application of AI in surgical practice. Machine learning approaches strengthen the feedback regarding surgical skills acquisition, efficiency of the surgical process, surgical guidance and prediction of postoperative outcomes. Tension-sensors on the robotic arms and the integration of augmented reality methods can help enhance the surgical experience and monitor organ movements.

CONCLUSIONS

The use of AI in robotic surgery is expected to have a significant impact on future surgical training as well as enhance the surgical experience during a procedure. Both aim to realize precision surgery and thus to increase the quality of the surgical care. Implementation of AI in master-slave robotic surgery may allow for the careful, step-by-step consideration of autonomous robotic surgery.

A deep-learning model using automated performance metrics and clinical features to predict urinary continence recovery after robot-assisted radical prostatectomy

OBJECTIVES

To predict urinary continence recovery after robot-assisted radical prostatectomy (RARP) using a deep learning (DL) model, which was then used to evaluate surgeon's historical patient outcomes.

SUBJECTS AND METHODS

Robotic surgical automated performance metrics (APMs) during RARP, and patient clinicopathological and continence data were captured prospectively from 100 contemporary RARPs. We used a DL model (DeepSurv) to predict postoperative urinary continence. Model features were ranked based on their importance in prediction. We stratified eight surgeons based on the five top-ranked features. The top four surgeons were categorized in 'Group 1/APMs', while the remaining four were categorized in 'Group 2/APMs'. A separate historical cohort of RARPs (January 2015 to August 2016) performed by these two surgeon groups was then used for comparison. Concordance index (C-index) and mean absolute error (MAE) were used to measure the model's prediction performance. Outcomes of historical cases were compared using the Kruskal-Wallis, chi-squared and Fisher's exact tests.

RESULTS

Continence was attained in 79 patients (79%) after a median of 126 days. The DL model achieved a C-index of 0.6 and an MAE of 85.9 in predicting continence. APMs were ranked higher by the model than clinicopathological features. In the historical cohort, patients in Group 1/APMs had superior rates of urinary continence at 3 and 6 months postoperatively (47.5 vs 36.7%, P = 0.034, and 68.3 vs 59.2%, P = 0.047, respectively).

CONCLUSION

Using APMs and clinicopathological data, the DeepSurv DL model was able to predict continence after RARP. In this feasibility study, surgeons with more efficient APMs achieved higher continence rates at 3 and 6 months after RARP.

The safety of urologic robotic surgery depends on the skills of the surgeon

PURPOSE

To assess the available literature evidence that discusses the effect of surgical experience on patient outcomes in robotic setting. This information is used to help understand how we can develop a learning process that allows surgeons to maximally accommodate patient safety.

METHODS

A literature search of the MEDLINE/PubMed and Scopus database was performed. Original and review articles published in the English language were included after an interactive peer-review process of the panel.

RESULTS

Robotic surgical procedures require high level of experience to guarantee patient safety. This means that, for some procedures, the learning process might be longer than originally expected. In this context, structured training programs that assist surgeons to improve outcomes during their learning processes were extensively discussed. We identified few structured robotic curricula and demonstrated that for some procedures, curriculum trained surgeons can achieve outcomes rates during their initial learning phases that are at least comparable to those of experienced surgeons from high-volume centres. Finally, the importance of non-technical skills on patient safety and of their inclusion in robotic training programs was also assessed.

CONCLUSION

To guarantee safe robotic surgery and to optimize patient outcomes during the learning process, standardized and validated training programs are instrumental. To date, only few structured validated curricula exist for standardized training and further efforts are needed in this direction.

Effect of surgeon experience and bony pelvic dimensions on surgical performance and patient outcomes in robot-assisted radical prostatectomy

OBJECTIVES

To evaluate the effects of surgeon experience, body habitus, and bony pelvic dimensions on surgeon performance and patient outcomes after robot-assisted radical prostatectomy (RARP).

PATIENTS, SUBJECTS AND METHODS

The pelvic dimensions of 78 RARP patients were measured on preoperative magnetic resonance imaging and computed tomography by three radiologists. Surgeon automated performance metrics (APMs [instrument motion tracking and system events data, i.e., camera movement, third-arm swap, energy use]) were obtained by a systems data recorder (Intuitive Surgical, Sunnyvale, CA, USA) during RARP. Two analyses were performed: Analysis 1, examined effects of patient characteristics, pelvic dimensions and prior surgeon RARP caseload on APMs using linear regression; Analysis 2, the effects of patient body habitus, bony pelvic measurement, and surgeon experience on short- and long-term outcomes were analysed by multivariable regression.

RESULTS

Analysis 1 showed that while surgeon experience affected the greatest number of APMs (P < 0.044), the patient's body mass index, bony pelvic dimensions, and prostate size also affected APMs during each surgical step (P < 0.043, P < 0.046, P < 0.034, respectively). Analysis 2 showed that RARP duration was significantly affected by pelvic depth (β = 13.7, P = 0.039) and prostate volume (β = 0.5, P = 0.024). A wider and shallower pelvis was less likely to result in a positive margin (odds ratio 0.25, 95% confidence interval [CI] 0.09-0.72). On multivariate analysis, urinary continence recovery was associated with surgeon's prior RARP experience (hazard ratio [HR] 2.38, 95% CI 1.18-4.81; P = 0.015), but not on pelvic dimensions (HR 1.44, 95% CI 0.95-2.17).

CONCLUSION

Limited surgical workspace, due to a narrower and deeper pelvis, does affect surgeon performance and patient outcomes, most notably in longer surgery time and an increased positive margin rate.

Evidence that surgical performance predicts clinical outcomes

PURPOSE

Assessment of surgeon performance in the operating room has been identified as a direct method of measuring surgical quality. Studies published in urology and other surgical disciplines have investigated this link directly by measuring surgeon and team performance using methodology supported by validity evidence. This article highlights the key findings of these studies and associated underlying concepts.

METHODS

​Seminal literature from urology and related areas of research was used to inform this review of the performance-outcome relationship in surgery. Current efforts to further our understanding of this concept are discussed, including relevant quality improvement and educational interventions that utilize this relationship.

RESULTS

Evidence from multiple surgical specialties and procedures has established the association between surgeon skill and clinically significant patient outcomes. Novel methods of measuring performance utilize surgeon kinematics and artificial intelligence techniques to more reliably and objectively quantify surgical performance.

CONCLUSIONS

Future directions include the use of this data to create interventions for quality improvement, as well as innovate the credentialing and recertification process for practicing surgeons.

Linking surgical skills to postoperative outcomes: a Delphi study on the robot-assisted radical prostatectomy

OBJECTIVE

To develop an assessment instrument for the evaluation of surgical videos to elucidate the association between surgical skills and postoperative outcomes after a robot-assisted radical prostatectomy (RARP).

DESIGN

A Delphi study consisting of two consecutive online surveys and a consensus group meeting.

SETTING

Urology departments of general, teaching and university hospitals in the Netherlands.

PARTICIPANTS

All Dutch urologists with a specialization in RARP.

RESULTS

Of 18 invited experts, 12 (67%) participated in the first online survey. In the second round, 9 of the 18 invited experts participated (50%). The Delphi meeting was attended by 5 of the 18 (27%) invited experts. The panel identified seven surgical steps with a possible association to postoperative outcomes. The experts also expected an association between adverse postoperative outcomes and the frequency of camera removals, the number of stitches placed, the amount of bleeding, and the extent of coagulation. These factors were incorporated into an assessment instrument.

CONCLUSIONS

Experts in the field of RARP achieved consensus on 7 surgical steps and 4 aspects of the RARP procedure that may be related to adverse postoperative outcomes. The resulting assessment instrument will be tested in future research to determine its validity.

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.

Implementing assessments of robot-assisted technical skill in urological education: a systematic review and synthesis of the validity evidence

OBJECTIVES

To systematically review and synthesise the validity evidence supporting intraoperative and simulation-based assessments of technical skill in urological robot-assisted surgery (RAS), and make evidence-based recommendations for the implementation of these assessments in urological training.

MATERIALS AND METHODS

A literature search of the Medline, PsycINFO and Embase databases was performed. Articles using technical skill and simulation-based assessments in RAS were abstracted. Only studies involving urology trainees or faculty were included in the final analysis.

RESULTS

Multiple tools for the assessment of technical robotic skill have been published, with mixed sources of validity evidence to support their use. These evaluations have been used in both the ex vivo and in vivo settings. Performance evaluations range from global rating scales to psychometrics, and assessments are carried out through automation, expert analysts, and crowdsourcing.

CONCLUSION

There have been rapid expansions in approaches to RAS technical skills assessment, both in simulated and clinical settings. Alternative approaches to assessment in RAS, such as crowdsourcing and psychometrics, remain under investigation. Evidence to support the use of these metrics in high-stakes decisions is likely insufficient at present.

Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes

PURPOSE

Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP).

MATERIALS AND METHODS

We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2 days) from 78 RARP cases, and selected the algorithm with the best performance. The selected algorithm categorized the cases as "Predicted as expected LOS (pExp-LOS)" and "Predicted as extended LOS (pExt-LOS)." We compared postoperative outcomes of the two groups (Kruskal-Wallis/Fisher's exact tests). The algorithm then predicted individual clinical outcomes, which we compared with actual outcomes (Spearman's correlation/Fisher's exact tests). Finally, we identified five most relevant APMs adopted by the algorithm during predicting.

RESULTS

The "Random Forest-50" (RF-50) algorithm had the best performance, reaching 87.2% accuracy in predicting LOS (73 cases as "pExp-LOS" and 5 cases as "pExt-LOS"). The "pExp-LOS" cases outperformed the "pExt-LOS" cases in surgery time (3.7 hours vs 4.6 hours, p = 0.007), LOS (2 days vs 4 days, p = 0.02), and Foley duration (9 days vs 14 days, p = 0.02). Patient outcomes predicted by the algorithm had significant association with the "ground truth" in surgery time (p < 0.001, r = 0.73), LOS (p = 0.05, r = 0.52), and Foley duration (p < 0.001, r = 0.45). The five most relevant APMs, adopted by the RF-50 algorithm in predicting, were largely related to camera manipulation.

CONCLUSION

To our knowledge, ours is the first study to show that APMs and ML algorithms may help assess surgical RARP performance and predict clinical outcomes. With further accrual of clinical data (oncologic and functional data), this process will become increasingly relevant and valuable in surgical assessment and training.

Novel robotic systems and future directions

Robot-assistance is increasingly used in surgical practice. We performed a nonsystematic literature review using PubMed/MEDLINE and Google for robotic surgical systems and compiled information on their current status. We also used this information to predict future about the direction of robotic systems based on various robotic systems currently being developed. Currently, various modifications are being made in the consoles, robotic arms, cameras, handles and instruments, and other specific functions (haptic feedback and eye tracking) that make up the robotic surgery system. In addition, research for automated surgery is actively being carried out. The development of future robots will be directed to decrease the number of incisions and improve precision. With the advent of artificial intelligence, a more practical form of robotic surgery system can be introduced and will ultimately lead to the development of automated robotic surgery system.

A Novel Method of Setting Performance Standards in Surgery Using Patient Outcomes

OBJECTIVE

To describe a novel, outcome-based method of standard setting that differentiates between clinical outcomes rather than arbitrary educational goals.

BACKGROUND

Standard setting methods used in assessments of procedural skill are currently not evidence-driven or outcome-based. This represents a potential obstacle for the broad implementation of these evaluations in summative assessments such as certification and credentialing.

METHODS

The concept is based on deriving a receiver operating characteristic curve from a regression model that incorporates measures of intraoperative surgeon performance and confounding patient characteristics. This allows the creation of a performance standard that best predicts a clinically significant outcome of interest. The discovery cohort used to create the predictive model was derived from pilot data that used the Global Evaluative Assessment of Robotic Skill assessment tool to predict patient urinary continence 3 months following robotic-assisted radical prostatectomy.

RESULTS

A receiver operating characteristic curve with an area under the curve of 0.75 was created from predicted probability statistic generated by the predictive model. We chose a predicted probability of 0.35, based on an optimal tradeoff in sensitivity and specificity (Youden Index). Rearranging the regression equation, we determined the performance score required to predict a 35%, patient-adjusted probability of postoperative urinary incontinence.

CONCLUSIONS

This novel methodology is context, patient, and assessment-specific. Current standard setting methods do not account for the heterogeneity of the clinical environment. Workplace-based assessments in competency-based medical education require standards that are credible to the educator and the trainee. High-stakes assessments must ensure that surgeons have been evaluated to a standard that prioritizes satisfactory patient outcomes and safety.