Validation of Novel Image Processing Method for Objective Quantification of Intra-Articular Bleeding During...

Area of Science:

• Orthopedic Surgery
• Medical Imaging
• Computer Vision

Background:

• Optimal visual clarity is essential for precise shoulder arthroscopy.
• Intraoperative bleeding significantly impairs visibility and surgical effectiveness.
• Current subjective bleeding assessments lack standardization and consistency.

Purpose of the Study:

• To develop and validate a novel image processing system for objective quantification of intraoperative bleeding in shoulder arthroscopy.
• To assess the system's accuracy and reliability in comparison to expert surgeon evaluations.
• To provide a standardized tool for evaluating bleeding and supporting advanced surgical technologies.

Main Methods:

• A new image processing system utilizing color recognition algorithms and multiple color spaces was developed.
• The system calculates a bleeding score based on pixel ratios.
• 200 video clips from arthroscopic rotator cuff repairs were analyzed by the system and three senior surgeons; intraobserver reliability was assessed.

Main Results:

• The system achieved an average bleeding score of 5.08, closely matching the average surgeon score of 5.10.
• High agreement was observed between the system and surgeon scores (ICC = 0.967), with a mean absolute error of 0.56.
• The system demonstrated strong intraobserver reliability and precise detection of blood variations.

Conclusions:

• The developed image processing system offers a standardized and objective method for quantifying intraoperative bleeding in shoulder arthroscopy.
• This technology enhances visual clarity, enabling more precise surgical interventions.
• The system supports the integration of advanced tools, such as autonomous arthropumps, to improve arthroscopic procedures and patient outcomes.