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Performance Comparison of Large Language Models in TAP Block Ultrasound Interpretation

StatusRecruiting
PhaseNot specified
Started
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Record status
This record was last updated February 4, 2026 (before its estimated April 30, 2026 completion). Its status may not reflect the trial's current state.

Record History

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  1. Trial status: Not Yet Recruiting to Recruiting
    • Start date changed from estimate of Nov 30, 2025 to Jan 15, 2026
    • Site details revised
    • Study title shortened, about 4 words
    v2
  2. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
The goal of this study is to learn how accurately two artificial intelligence (AI) models, Gemini 2.5 Pro and ChatGPT-5.1, can interpret ultrasound videos of the Transversus Abdominis Plane (TAP) block, a regional anesthesia technique used for pain control after surgery. The main questions this study aims to answer are: How accurately can each AI model identify anatomical structures on TAP block ultrasound videos? Can the AI models correctly evaluate the spread of local anesthetic and determine whether the block is successful? How closely do the AI models' answers match the evaluations of expert anesthesiologists? No additional procedures will be performed on patients. TAP blocks will be done as part of routine clinical care, and the ultrasound videos will be recorded and de-identified. Participants will not need to do anything extra for the study. Experienced anesthesiologists will review the videos and provide expert answers. The AI models will be given the same videos and asked the same questions. A second expert, who does not know which answers came from humans or AI, will compare all responses. The results will help researchers understand whether advanced AI systems can safely support clinicians in interpreting ultrasound-guided regional anesthesia procedures and improve education and decision-making in anesthesia practice.
Trial Details
NCT Number NCT07261436
Lead Sponsor Kanuni Sultan Suleyman Training and Research Hospital
Conditions
(from sponsor)		 Artificial Intelegence
Enrollment 40 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov