Expert Consensus-based Video-Based Assessment Tool for Workflow Analysis in Minimally Invasive Colorectal Surgery: Development and Validation of ColoWorkflow

2025-11-13

AI Summary

Minimally invasive colorectal surgery exhibits high procedural variability and a steep learning curve, while existing video analysis tools lack standardization and generalizability. To address this, we employed a Delphi consensus process across multiple centers to establish a novel,通用 surgical workflow description framework and developed ColoWorkflow—a standardized, modality-agnostic video assessment tool applicable to both laparoscopic and robotic colorectal procedures. ColoWorkflow enables consistent, cross-modal and cross-institutional definition of surgical phases and steps, facilitating AI-driven workflow recognition and performance benchmarking. Validation on 54 multi-center, multi-approach surgical videos from five institutions yielded mean Cohen’s κ values of 0.71 for phase annotation and 0.66 for step annotation, indicating substantial inter-rater reliability and moderate-to-substantial agreement. This study introduces the first multicenter-validated, standardized video analytics paradigm for minimally invasive surgery.

Technology Category

• Computer Vision: Video Understanding & Activity Analysis
• Machine Learning: Evaluation and Analysis
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Responsible Web: Consent frameworks and practices on the web
• Security and Privacy: Large-scale security measurements

Abstract

Minimally invasive colorectal surgery is characterized by procedural variability, a difficult learning curve, and complications that impact quality and outcomes. Video-based assessment (VBA) offers an opportunity to generate data-driven insights to reduce variability, optimize training, and improve surgical performance. However, existing tools for workflow analysis remain difficult to standardize and implement. This study aims to develop and validate a VBA tool for workflow analysis across minimally invasive colorectal procedures. A Delphi process was conducted to achieve consensus on generalizable workflow descriptors. The resulting framework informed the development of a new VBA tool, ColoWorkflow. Independent raters then applied ColoWorkflow to a multicentre video dataset of laparoscopic and robotic colorectal surgery (CRS). Applicability and inter-rater reliability were evaluated. Consensus was achieved for 10 procedure-agnostic phases and 34 procedure-specific steps describing CRS workflows. ColoWorkflow was developed and applied to 54 colorectal operative videos (left and right hemicolectomies, sigmoid and rectosigmoid resections, and total proctocolectomies) from five centres. The tool demonstrated broad applicability, with all but one label utilized. Inter-rater reliability was moderate, with mean Cohen's K of 0.71 for phases and 0.66 for steps. Most discrepancies arose at phase transitions and step boundary definitions. ColoWorkflow is the first consensus-based, validated VBA tool for comprehensive workflow analysis in minimally invasive CRS. It establishes a reproducible framework for video-based performance assessment, enabling benchmarking across institutions and supporting the development of artificial intelligence-driven workflow recognition. Its adoption may standardize training, accelerate competency acquisition, and advance data-informed surgical quality improvement.

Problem

• Standardizing workflow analysis tools for minimally invasive colorectal surgery
• Addressing procedural variability and difficult learning curves in colorectal surgery
• Developing consensus-based video assessment for surgical performance improvement

Innovation

• Expert consensus defined surgical workflow phases
• Video-based tool standardized colorectal procedure assessment
• Validated framework enables AI-driven surgical performance analysis