Evaluation of Mixed Reality Technologies for Remote Feedback and Guidance During Transrectal Ultrasound Biopsy Simulation: A Prospective, Randomized, Crossover Study.

OBJECTIVE: To compare equivalency of remote to in-person training during simulated transrectal ultrasound-guided prostate biopsy, we combined three technologies (mixed reality [MR] software, smart glasses, and hydrogel simulation model). Taken together, telemonitoring harnesses data streaming to provide real-time supervision and technical assistance for surgical procedures from an expert at a remote geographical location. METHODS: Nineteen students were randomized into two groups (MR-first and in-person-first) and proctored to measure prostate volume and perform 14-biopsies over seven sessions: pretest, two MR/in-person-guided training sessions, mid-test, crossover into two in-person/MR-guided training sessions, and post-test. MR sessions utilized Vuzix smart glasses with MR software (HelpLightning) to share the student's first-person perspective and Zoom to project the ultrasound screen to a remote instructor. Training and test sessions utilized single-color and seven-color prostate models, respectively. Accuracy of biopsy cores from test sessions were compared. Perception of instruction following each training session using 5-point Likert scales across five domains was assessed. Preference of instruction modality was assessed qualitatively. RESULTS: Comparison of mid-test performance following two training sessions was similar across the two groups (MR-first 63.8% vs in-person-first 57.6%, P = .340). Following crossover, difference in post-test performance of the MR-first group and the in-person-first group approached significance (MR-first 80.2% vs in-person-first 70.8%, P = .050). Student evaluation of MR and in-person instruction following training sessions was similar across the five metrics. CONCLUSION: MR-based remote learning is equally effective when compared to traditional in-person instruction.

Three-dimensional printed hydrogel model vs cadaver: comparing inflatable penile prosthesis training and evaluation.

BACKGROUND: Penile prosthesis implantation offers a durable, safe, and effective treatment option for male erectile dysfunction; however, many urologists feel apprehensive and uncomfortable placing penile prostheses due to limited training, low surgical experience, and intra- and postoperative complication management. AIM: To compare a previously validated hydrogel inflatable penile prosthesis (IPP) training model with cadaver simulations across 4 main categories: anatomic replication and realism, procedural replication and realism, educational effectiveness, and efficacy and safety. METHODS: An overall 88 participants (15 attendings, 18 fellows, and 55 residents) performed guided IPP placements on a cadaver and a hydrogel model. Based on a 5-point Likert scale, postsurveys were used to assess the participants' opinions regarding anatomic replication and realism, procedural replication and realism, educational effectiveness, and safety between the hydrogel model and cadavers. OUTCOMES: A direct head-to-head scenario was created, allowing participants to fully utilize the hydrogel model and cadaver, which ensured the most accurate comparison possible. RESULTS: A total of 84% agreed that the hydrogel model replicates the relevant human cadaveric anatomy for the procedure, whereas 69% agreed that the hydrogel tissue resembles the appearance of cadaveric tissue. Regarding the pubic bone, outer skin, corporal bodies, dartos layer, and scrotum, 79%, 74%, 82%, 46%, and 30% respectively agreed that the hydrogel tissue resembled the texture/behavior of cadavers. Furthermore, 66% of participants agreed that the hydrogel model replicates all the procedural steps. Specifically, participants agreed that the model replicates the skin incision/dartos dissection (74%), placement of stay suture and corporotomy (92%), corporal dilation (81%), measurement of prosthetic size (98%), reservoir placement (43%), IPP placement (91%), scrotal pump placement (48%), and skin closure (51%). Finally, 86%, 93%, and 78% agreed that the hydrogel model is useful for improving technical skills, as a teaching/practicing tool, and as an evaluation tool, respectively. To conclude, 81% of participants stated that they would include the hydrogel model platform in their current training. CLINICAL IMPLICATIONS: By replicating the IPP procedure, the hydrogel model offers an additional high-fidelity training opportunity for urologists, allowing them to improve their skills and confidence in placing penile prostheses, with the goal of improving patient surgical outcomes. STRENGTHS AND LIMITATIONS: The hydrogel training model allows users to perform the entire IPP placement procedure with high anatomic realism and educational effectiveness, maintaining many of the high-fidelity benefits seen in cadavers while improving safety and accessibility. CONCLUSION: Ultimately, this high-fidelity nonbiohazardous training model can be used to supplement and bolster current IPP training curriculums.

Predicting Surgical Experience After Robotic Nerve-sparing Radical Prostatectomy Simulation Using a Machine Learning-based Multimodal Analysis of Objective Performance Metrics.

INTRODUCTION: Machine learning methods have emerged as objective tools to evaluate operative performance in urological procedures. Our objectives were to establish machine learning-based methods for predicting surgeon caseload for nerve-sparing robot-assisted radical prostatectomy using our validated hydrogel-based simulation platform and identify potential metrics of surgical expertise. METHODS: Video, robotic kinematics, and force sensor data were collected from 35 board-certified urologists at the 2022 AUA conference. Video was annotated for surgical gestures. Objective performance indicators were derived from robotic system kinematic data. Force metrics were calculated from hydrogel model integrated sensors. Data were fitted to 3 supervised machine learning models-logistic regression, support vector machine, and k-nearest neighbors-which were used to predict procedure-specific learning curve proficiency. Recursive feature elimination was used to optimize the best performing model. RESULTS: Logistic regression predicted caseload with the highest AUC score for 5/7 possible data combinations (force, 64%; objective performance indicators + gestures, 94%; objective performance indicators + force, 90%; gestures + force, 93%; objective performance indicators + gestures + force, 94%). Support vector machine predicted the highest AUC score for objective performance indicators (82%) and gestures (94%). Logistic regression with recursive feature elimination was the most effective model reaching 96% AUC in predicting case-specific experience. Most contributory features were identified across all model types. CONCLUSIONS: We have created a machine learning-based algorithm utilizing a novel combination of objective performance indicators, gesture analysis, and integrated force metrics to predict surgical experience, capable of discriminating between surgeons with low or high robot-assisted radical prostatectomy caseload with 96% AUC in a standardized, simulation-based environment.

Do Skills Naturally Transfer Between Multiport and Single-Port Robotic Platforms? A Comparative Study in a Simulated Environment.

Introduction and Objective: With introduction of the da Vinci single-port (SP) system, we evaluated which multiport (MP) robotic skills are naturally transferable to the SP platform. Methods: Three groups of urologists: Group 1 (5 inexperienced in MP and SP), Group 2 (5 experienced in MP without SP experience), and Group 3 (2 experienced in both MP and SP) were recruited to complete a validated urethrovesical anastomosis simulation using MP followed by SP robots. Performance was graded using both GEARS and RACE scales. Subjective cognitive load measurements (Surg-TLX and difficulty ratings [/20] of instrument collisions camera and EndoWrist movement) were collected. Results: GEARS and RACE scores for Groups 1 and 3 were maintained on switching from MP to SP (Group 3 scored significantly higher on both systems). Surg-TLX and difficulty scores were also maintained for both groups on switching from MP and SP except for a significant increase in SP camera movement (+7.2, p = 0.03) in Group 1 compared to Group 3 that maintained low scores on both. Group 2 demonstrated significant lower GEARS (-2.9, p = 0.047) and RACE (-5.1, p = 0.011) scores on SP vs MP. On subanalysis, GEARS subscores for force sensitivity and robotic control (-0.7, p = 0.04; -0.9, p = 0.02) and RACE subscores for needle entry, needle driving, and tissue approximation (-0.9, p = 0.01; -1.0, p = 0.02; -1.0, p < 0.01) significantly decreased. GEARS (depth perception, bimanual dexterity, and efficiency) and RACE subscores (needle positioning and suture placement) were maintained. All participants scored significantly lower in knot tying on the SP robot (-1.0, p = 0.03; -1.2, p = 0.02, respectively). Group 2 reported higher Surg-TLX (+13 pts, p = 0.015) and difficulty ratings on SP vs MP (+11.8, p < 0.01; +13.6, p < 0.01; +14 pts, p < 0.01). Conclusions: The partial skill transference across robots raises the question regarding SP-specific training for urologists proficient in MP. Novices maintained difficulty scores and cognitive load across platforms, suggesting that concurrent SP and MP training may be preferred.

Utilizing head-mounted eye trackers to analyze patterns and decision-making strategies of 3D virtual modelling platform (IRIS™) during preoperative planning for renal cancer surgeries.

PURPOSE: IRIS™ provides interactive, 3D anatomical visualizations of renal anatomy for pre-operative planning that can be manipulated by altering transparency, rotating, zooming, panning, and overlaying the CT scan. Our objective was to analyze how eye tracking metrics and utilization patterns differ between preoperative surgical planning of renal masses using IRIS and CT scans. METHODS: Seven surgeons randomly reviewed IRIS and CT images of 9 patients with renal masses [5 high complexity (RENAL score ≥ 8), 4 low complexity (≤ 7)]. Surgeons answered a series of questions regarding patient anatomy, perceived difficulty (/100), confidence (/100), and surgical plan. Eye tracking metrics (mean pupil diameter, number of fixations, and gaze duration) were collected. RESULTS: Surgeons spent significantly less time interpreting data from IRIS than CT scans (- 67.1 s, p < 0.01) and had higher inter-rater agreement of surgical approach after viewing IRIS (α = 0.16-0.34). After viewing IRIS, surgical plans although not statistically significant demonstrated a greater tendency towards a more selective ischemia approaches which positively correlated with improved identification of vascular anatomy. Planned surgical approach changed in 22/59 of the cases. Compared to viewing the CT scan, left and right mean pupil diameter and number/duration of fixations were significantly lower when using IRIS (p < 0.01, p < 0.01, p = 0.42, p < 0.01, respectively), indicating interpreting information from IRIS required less mental effort despite under-utilizing its interactive features. CONCLUSIONS: Surgeons extrapolated more detailed information in less time with less mental effort using IRIS than CT scans and proposed surgical approaches with potential to enhanced surgical outcomes.

Validity of a patient-specific percutaneous nephrolithotomy (PCNL) simulated surgical rehearsal platform: impact on patient and surgical outcomes.

INTRODUCTION: Simulators provide a safe method for improving surgical skills without the associated patient risks. Advances in rapid prototyping technology have permitted the reconstruction of patient imaging into patient-specific surgical simulations that require advanced expertise, potentially continuing the learning curve. OBJECTIVES: To evaluate the impact of preoperative high-fidelity patient-specific percutaneous nephrolithotomy hydrogel simulations on surgical and patient outcomes. MATERIALS AND METHODS: Between 2016 and 2017, a fellowship-trained endourologist performed 20 consecutive percutaneous nephrolithotomy procedures at an academic referral center. For the first ten patients, only standard review of patient imaging was completed. For the next ten patients, patient imaging was utilized to fabricate patient-specific models including pelvicalyceal system, kidney, stone, and relevant adjacent structures from hydrogel. The models were tested to confirm anatomic accuracy and material properties similar to live tissue. Full procedural rehearsals were completed 24-48 h before the real case. Surgical metrics and patient outcomes from both groups (rehearsal vs. standard) were compared. RESULTS: Significant improvements in mean fluoroscopy time, percutaneous needle access attempts, complications, and additional procedures were significantly lower in the rehearsal group (184.8 vs. 365.7 s, p < 0.001; 1.9 vs. 3.6 attempts, p < 0.001; 1 vs. 5, p < 0.001; and 1 vs. 5, p < 0.001, respectively). There were no differences in stone free rates, mean patient age, body mass index, or stone size between the two groups. CONCLUSION: This study demonstrates that patient-specific procedural rehearsal is effective reducing the experience curve for a complex endourological procedure, resulting in improved surgical performance and patient outcomes.

Design and Implementation of an Emergency Undocking Curriculum for Robotic Surgery.

INTRODUCTION: Current training for robotic surgery crisis management, specifically emergency robotic undocking protocol (ERUP), remains limited to anecdotal experience. A curriculum to impart the skills and knowledge necessary to recognize and complete a successful ERUP was developed using an education approach then evaluated. METHODS: Baseline knowledge and confidence regarding ERUP were established for 5 robotic teams before completing 2 full-immersion simulations separated by an online self-paced learning module. In each simulation, teams operated on a perfused hydrogel model and were tasked to dissect a retroperitoneal tumor abutting a major vessel. During vascular pedicle ligation, a major vascular bleed and nonrecoverable robotic fault were remotely induced, necessitating ERUP with open conversion. After the simulation, participants completed surgery task load index (cognitive load assessment) and realism surveys. Weighted checklists scored participants' actions during each simulation. Surgical metrics including estimated blood loss, time to control bleeding, and undocking time were recorded. Curriculum retention was assessed by repeating the exercise at 6 months. RESULTS: Participants experienced high levels of cognitive demand and agreed that the simulation's realism and stress mimicked live surgery. Longitudinal analysis showed significant knowledge (+37.5 points, p = 0.004) and confidence (+15.3 points, p < 0.001) improvements from baseline to completion. Between simulations, checklist errors, undocking time, and estimated blood loss decreased (38⇾17, -40 seconds, and -500 mL, respectively), whereas action scores increased significantly (+27 points, p = 0.008). At 6 months, insignificant changes from curriculum completion were seen in knowledge (-4.8 points, p = 0.36) and confidence (+3.7 points, p = 0.1). CONCLUSIONS: This simulation-based curriculum successfully improves operative team's confidence, knowledge, and skills required to manage robotic crisis events.

Comparison of Multi-Parametric MRI of the Prostate to 3D Prostate Computer Aided Designs and 3D-Printed Prostate Models for Pre-Operative Planning of Radical Prostatectomies: A Pilot Study.

OBJECTIVE: To evaluate the use of 3D computed aided designs and 3D-printed models as pre-operative planning tools for urologists, in addition to radiologist interpreted mp-MRIS, prior to radical prostatectomy procedures. METHODS: Ten patients with biopsy-positive lesions detected on mp-MRI were retrospectively selected. Radiologists identified lesion locations using a Prostate Imaging-Reporting and Data System (PI-RADS) map and segmented the prostate, lesion(s), and surrounding anatomy to create 3D-CADs and 3D-printed models for each patient. 6 uro-oncologists randomly reviewed three modalities (mp-MRI, 3D-CAD, and 3D-printed models) for each patient and identified lesion locations which were graded for accuracy against the radiologists' answers. Questionnaires assessed decision confidence, ease-of-interpretation, and usefulness for preoperative planning for each modality. RESULTS: Using 3D-CADs and 3D-printed models compared to mp-MRI, urologists were 2.4x and 2.8x more accurate at identifying the lesion(s), 2.7x and 3.2x faster, 1.6x and 1.63x more confident, and reported it was 1.6x and 1.7x easier to interpret. 3D-CADs and 3D-printed models were reported significantly more useful for overall pre-operative planning, identifying lesion location(s), determining degree of nerve sparing, obtaining negative margins, and patient counseling. Sub-analysis showed 3D-printed models demonstrated significant improvements in ease-of-interpretation, speed, usefulness for obtaining negative margins, and patient counseling compared to 3D-CADs. CONCLUSION: 3D-CADs and 3D-printed models are useful adjuncts to mp-MRI in providing urologists with more practical, accurate, and efficient pre-operative planning.

Application of IRIS Three-Dimensional Anatomical Models As Preoperative Surgical Planning Tools in the Management of Localized Renal Masses.

Introduction: The use of volume-rendered images is gaining popularity in the surgical planning for complex procedures. IRIS™ is an interactive software that delivers three-dimensional (3D) virtual anatomical models. We aimed to evaluate the preoperative clinical utility of IRIS for patients with ≤T2 localized renal tumors who underwent either partial nephrectomy (PN) or radical nephrectomy (RN). Patients and Methods: Six urologists (four faculty and two trainees) reviewed CT scans of 40 cases over 2 study phases, using conventional two-dimensional (2D) CT alone (Phase-I), followed by the CT + IRIS 3D model (Phase-II). After each review, surgeons reported their decision on performing a PN or an RN and rated (Likert scale) their confidence in completing the procedure as well as how the imaging modality influenced specific procedural decisions. Modifications to the choice of procedure and confidence in decisions between both phases were compared for the same surgeon. Concordance between surgeons was also evaluated. Results: A total of 462 reviews were included in the analysis (231 in each phase). In 64% (95% CI: 58-70%) of reviews, surgeons reported that IRIS achieved a better spatial orientation, understanding of the anatomy, and offered additional information compared with 2D CT alone. IRIS impacted the planned procedure in 20% of the reviews (3.5% changed decision from PN to RN and 16.5% changed from RN to PN). In the remaining 80% of reviews, surgeons' confidence increased from 78% (95% CI: 72-84%) with 2D CT, to 87% (95% CI: 82-92%) with IRIS (p = 0.02); this confidence change was more pronounced in cases with a high RENAL score (p = 0.009). In 99% of the reviews, surgeons rated that the IRIS accurately represented the anatomical details of all kidney components. Conclusion: Application of IRIS 3D models could influence the surgical decision-making process and improve surgeons' confidence, especially for robot-assisted management of complex renal tumors.

See Like an Expert: Gaze-Augmented Training Enhances Skill Acquisition in a Virtual Reality Robotic Suturing Task.

Introduction: The da Vinci Skills Simulator (DVSS) is an effective platform for robotic skills training. Novel training methods using expert gaze patterns to guide trainees have demonstrated superiority to traditional instruction. Portable head-mounted eye-trackers (HMET) offer the opportunity for eye tracking technology to enhance surgical robotic simulation training. Objective: To evaluate if training guided by expert gaze patterns can improve trainee performance over standard movement training techniques during robotic simulation. Methods: Medical students were recruited and randomized into gaze training (GT, n = 9) and movement training (MT, n = 8) groups. First, the participants reviewed an instructional video, with the GT group emulating expert gaze patterns and the MT group (n = 8) standard movement-based instruction. Training consisted of 10 repetitions of "Suture Sponge 3" on the DVSS while wearing HMET; the first three repetitions were followed by group-appropriate video coaching (gaze vs movement feedback), while the remaining repetitions were without feedback. Finally, two multitasking repetitions with a secondary bell-counting task were completed. Primary outcomes included DVSS scores during training and multitasking. Secondary outcomes included metrics collected from the HMET (gaze patterns and gaze entropy). Results: Total score, efficiency, and penalties improved significantly over the training in both groups; the GT group achieved higher scores on every attempt. Total scores in the GT group were higher than the MT group postvideo review (20.3 ± 21.8 vs 3.0 ± 6.2, p = 0.047), after coaching repetitions (61.8 ± 18.8 vs 30.1 ± 26.2, p = 0.01), and at the last training attempt (73.0 ± 16.5 vs 63.1 ± 17.4, p = 0.247). During multitasking, the GT group maintained higher total scores (75 ± 10.1 vs 63.3 ± 15.3, p = 0.01), efficiency (86.3 ± 7.4 vs 77.4 ± 11.2, p = 0.009), and superior secondary task performance (error: 6.3% ± 0.06 vs 10.7% ± 0.11, p = 0.20). Gaze entropy (cognitive-load indicator) and gaze pattern analysis showed similar trends. Conclusion: Gaze-augmented training leads to more efficient movements through adoption of expert gaze patterns that withstand additional stressors.