Abstract 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. Gestures are classified into nine distinct dissection gestures (e.g., hot cut) and four supporting gestures (e.g., retraction). Our primary outcome is to identify factors impacting a patient’s 1-year erectile function (EF) recovery after radical prostatectomy. We find that less use of hot cut and more use of peel/push are statistically associated with better chance of 1-year EF recovery. Our results also show interactions between surgeon experience and gesture types—similar gesture selection resulted in different EF recovery rates dependent on surgeon experience. To further validate this framework, two teams independently constructe distinct machine learning models using gesture sequences vs. traditional clinical features to predict 1-year EF. In both models, gesture sequences are able to better predict 1-year EF (Team 1: AUC 0.77, 95% CI 0.73–0.81; Team 2: AUC 0.68, 95% CI 0.66–0.70) than traditional clinical features (Team 1: AUC 0.69, 95% CI 0.65–0.73; Team 2: AUC 0.65, 95% CI 0.62–0.68). Our results suggest that gestures provide a granular method to objectively indicate surgical performance and outcomes. Application of this methodology to other surgeries may lead to discoveries on methods to improve surgery. 

/pdf/surgical-gestures-as-a-method-to-quantify-surgical-1q21ls5w.pdf

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

An Assessment Tool to Provide Targeted Feedback to Robotic Surgical Trainees: Development and Validation of the End-to-End Assessment of Suturing Expertise (EASE)

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.

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

Assessing the efficacy of dissection gestures in robotic surgery

A universal resident robotic surgery training pathway that maximizes proficiency and safety has not been defined by a consensus of surgical educators or by surgical societies. The objective of the Robotic Surgery Education Working Group was to develop a universal curriculum pathway and leverage digital tools to support resident education. The two lead authors (JP and YN) contacted potential members of the Working Group. Members were selected based on their authorship of peer-review publications, their experience as minimally invasive and robotic surgeons, their reputations, and their ability to commit the time involved to work collaboratively and efficiently to reach consensus regarding best practices in robotic surgery education. The Group's approach was to reach 100% consensus to provide a transferable curriculum that could be applied to the vast majority of resident programs. Virtual and in-person meetings in the United States. Eight surgeons (2 females and 6 males) from five academic medical institutions (700–1541 beds) and three community teaching hospitals (231–607 beds) in geographically diverse locations comprised the Working Group. They represented highly specialized general surgeons and educators in their mid-to-late careers. All members were experienced minimally invasive surgeons and had national reputations as robotic surgery educators. The surgeons initially developed and agreed upon questions for each member to consider and respond to individually via email. Responses were collated and consolidated to present on an anonymized basis to the Group during an in-person day-long meeting. The surgeons self-facilitated and honed the agreed upon responses of the Group into a 5-level Robotic Surgery Curriculum Pathway, which each member agreed was relevant and expressed their convictions and experience. The current needs for a universal robotic surgery training curriculum are validated objective and subjective measures of proficiency, access to simulation, and a digital platform that follows a resident from their first day of residency through training and their entire career. Refinement of current digital solutions and continued innovation guided by surgical educators is essential to build and maintain a scalable, multi-institutional supported curriculum. 

Structured Resident Training in Robotic Surgery: Recommendations of the Robotic Surgery Education Working Group.

Development and Validation of an Objective Scoring Tool to Evaluate Surgical Dissection: Dissection Assessment for Robotic Technique (DART)

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Development and Validation of an Objective Scoring Tool to Evaluate Surgical Dissection: Dissection Assessment for Robotic Technique (DART)