Human AI collaboration for unsupervised categorization of live surgical feedback.

Formative verbal feedback during live surgery is essential for adjusting trainee behavior and accelerating skill acquisition. Despite its importance, understanding optimal feedback is challenging due to the difficulty of capturing and categorizing feedback at scale. We propose a Human-AI Collaborative Refinement Process that uses unsupervised machine learning (Topic Modeling) with human refinement to discover feedback categories from surgical transcripts.

Capturing relationships between suturing sub-skills to improve automatic suturing assessment.

Suturing skill scores have demonstrated strong predictive capabilities for patient functional recovery. The suturing can be broken down into several substep components, including needle repositioning, needle entry angle, etc. Artificial intelligence (AI) systems have been explored to automate suturing skill scoring.

Surgical gestures to evaluate apical dissection of robot-assisted radical prostatectomy.

Previously, our group established a surgical gesture classification system that deconstructs robotic tissue dissection into basic surgical maneuvers. Here, we evaluate gestures by correlating the metric with surgeon experience and technical skill assessment scores in the apical dissection (AD) of robotic-assisted radical prostatectomy (RARP). Additionally, we explore the association between AD performance and early continence recovery following RARP.

The effect of enhanced recovery after surgery on oncologic outcome following radical cystectomy for urothelial bladder carcinoma.

Introduction: Limited data are available regarding the effect of enhanced recovery after surgery (ERAS) protocols on the long-term outcomes of radical cystectomy (RC) in bladder cancer patients. The aim of this study is to evaluate the oncological outcomes in patients who underwent RC with ERAS protocol.

Methods: We reviewed the records of patients who underwent RC for primary urothelial bladder carcinoma with curative intent from January 2003 to August 2022.

Clinical applications of artificial intelligence in robotic surgery.

Artificial intelligence (AI) is revolutionizing nearly every aspect of modern life. In the medical field, robotic surgery is the sector with some of the most innovative and impactful advancements. In this narrative review, we outline recent contributions of AI to the field of robotic surgery with a particular focus on intraoperative enhancement.

Competency in Robotic Surgery: Standard Setting for Robotic Suturing Using Objective Assessment and Expert Evaluation.

Objective: Surgical skill assessment tools such as the End-to-End Assessment of Suturing Expertise (EASE) can differentiate a surgeon's experience level. In this simulation-based study, we define a competency benchmark for intraoperative robotic suturing using EASE as a validated measure of performance.

Design: Participants conducted a dry-lab vesicourethral anastomosis (VUA) exercise.

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

Purpose: To examine the association between the 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.

Artificial Intelligence in Pathomics and Genomics of Renal Cell Carcinoma.

The integration of artificial intelligence (AI) with histopathology images and gene expression patterns has led to the emergence of the dynamic fields of pathomics and genomics. These fields have revolutionized renal cell carcinoma (RCC) diagnosis and subtyping and improved survival prediction models. Machine learning has identified unique gene patterns across RCC subtypes and grades, providing insights into RCC origins and potential treatments, as targeted therapies.

STFuse: Infrared and Visible Image Fusion via Semisupervised Transfer Learning.

Infrared and visible image fusion (IVIF) aims to obtain an image that contains complementary information about the source images. However, it is challenging to define complementary information between source images in the lack of ground truth and without borrowing prior knowledge. Therefore, we propose a semisupervised transfer learning-based method for IVIF, termed STFuse, which aims to transfer knowledge from an informative source domain to a target domain, thus breaking the above limitations.

Simulation training in urology.

Purpose Of Review: This review outlines recent innovations in simulation technology as it applies to urology. It is essential for the next generation of urologists to attain a solid foundation of technical and nontechnical skills, and simulation technology provides a variety of safe, controlled environments to acquire this baseline knowledge.

Recent Findings: With a focus on urology, this review first outlines the evidence to support surgical simulation, then discusses the strides being made in the development of 3D-printed models for surgical skill training and preoperative planning, virtual reality models for different urologic procedures, surgical skill assessment for simulation, and integration of simulation into urology residency curricula.

Artificial Intelligence-Based Video Feedback to Improve Novice Performance on Robotic Suturing Skills: A Pilot Study.

Automated skills assessment can provide surgical trainees with objective, personalized feedback during training. Here, we measure the efficacy of artificial intelligence (AI)-based feedback on a robotic suturing task. Forty-two participants with no robotic surgical experience were randomized to a control or feedback group and video-recorded while completing two rounds (R1 and R2) of suturing tasks on a da Vinci surgical robot.

Development of a Classification System for Live Surgical Feedback.

Importance: Live feedback in the operating room is essential in surgical training. Despite the role this feedback plays in developing surgical skills, an accepted methodology to characterize the salient features of feedback has not been defined.

Objective: To quantify the intraoperative feedback provided to trainees during live surgical cases and propose a standardized deconstruction for feedback.

A Multi-institution Study on the Association of Virtual Reality Skills with Continence Recovery after Robot-assisted Radical Prostatectomy.

Background: Virtual reality (VR) simulators are increasingly being used for surgical skills training. It is unclear what skills are best improved via VR, translate to live surgical skills, and influence patient outcomes.

Objective: To assess surgeons in VR and live surgery using a suturing assessment tool and evaluate the association between technical skills and a clinical outcome.

A vision transformer for decoding surgeon activity from surgical videos.

The intraoperative activity of a surgeon has substantial impact on postoperative outcomes. However, for most surgical procedures, the details of intraoperative surgical actions, which can vary widely, are not well understood. Here we report a machine learning system leveraging a vision transformer and supervised contrastive learning for the decoding of elements of intraoperative surgical activity from videos commonly collected during robotic surgeries.

Exploring the Use of Artificial Intelligence in the Management of Prostate Cancer.

Purpose Of Review: This review aims to explore the current state of research on the use of artificial intelligence (AI) in the management of prostate cancer. We examine the various applications of AI in prostate cancer, including image analysis, prediction of treatment outcomes, and patient stratification. Additionally, the review will evaluate the current limitations and challenges faced in the implementation of AI in prostate cancer management.

Surgical gestures as a method to quantify surgical performance and predict patient outcomes.

How well a surgery is performed impacts a patient's outcomes; however, objective quantification of performance remains an unsolved challenge. Deconstructing a procedure into discrete instrument-tissue "gestures" is a emerging way to understand surgery. To establish this paradigm in a procedure where performance is the most important factor for patient outcomes, we identify 34,323 individual gestures performed in 80 nerve-sparing robot-assisted radical prostatectomies from two international medical centers.

Assessing the efficacy of dissection gestures in robotic surgery.

Our group previously defined a dissection gesture classification system that deconstructs robotic tissue dissection into its most elemental yet meaningful movements. The purpose of this study was to expand upon this framework by adding an assessment of gesture efficacy (ineffective, effective, or erroneous) and analyze dissection patterns between groups of surgeons of varying experience. We defined three possible gesture efficacies as ineffective (no meaningful effect on the tissue), effective (intended effect on the tissue), and erroneous (unintended disruption of the tissue).

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

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.

Prognostic Value of Tumor Size in Patients with Upper Tract Urothelial Carcinoma: A Systematic Review and Meta-analysis.

Context: The role of tumor size in predicting prognosis in upper tract urothelial carcinoma (UTUC) patients remains poorly defined.

Objective: To assess the prognostic value of tumor size in patients with UTUC through a systematic review and meta-analysis.

Evidence Acquisition: A comprehensive literature search of the PubMed and Embase databases were performed to identify all relevant articles published up to December 2021 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement.

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

Purpose: Previously, we identified 8 objective suturing performance metrics highly predictive of urinary continence recovery after robotic-assisted radical prostatectomy. Here, we aimed to test the feasibility of providing tailored feedback based upon these clinically relevant metrics and explore the impact on the acquisition of robotic suturing skills.

Materials And Methods: Training surgeons were recruited and randomized to a feedback group or a control group.

The Relationship Between Technical Skills, Cognitive Workload, and Errors During Robotic Surgical Exercises.

We attempt to understand the relationship between surgeon technical skills, cognitive workload, and errors during a simulated robotic dissection task. Participant surgeons performed a robotic surgery dissection exercise. Participants were grouped based on surgical experience.