The Evaluation of ChatGPT-4's Success in Identifying Anatomical Landmarks in Ultrasound Images of Regional Anesthesia Techniques
Trial ID: NCT06642389
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2024-10-17
Completion date: 2025-02-16
Sponsor: Kanuni Sultan Suleyman Training and Research Hospital
Conditions: Regional Anesthesia
Interventions: Sonoanatomical Structure Identification; Block Type Prediction; Block Success Assessment
Locations: Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital
Countries: Turkey (Türkiye)
Enrollment: 147
Age range: 18 Years - None
Sex: ALL

Summary:
Aim and Importance:

Regional anesthesia techniques have advanced significantly with the advent of ultrasound guidance. Peripheral nerve blocks and fascial plane blocks can now be performed safely and effectively under ultrasound visualization. Research has shown that ultrasound use significantly improves block success rates. However, accurate application requires in-depth knowledge of sonoanatomy, as failure to identify critical structures may result in incorrect anesthetic placement or failed blocks. While experienced anesthesiologists can easily identify these anatomical landmarks, those less familiar with sonoanatomy may find it challenging.

This study aims to evaluate the effectiveness of ChatGPT-4 in identifying sonoanatomical structures in ultrasound images. A secondary objective is to assess whether artificial intelligence can evaluate the accuracy of regional anesthesia applications.

Expected Benefits and Risks:

The primary benefit is to explore the potential of AI-based systems in improving the learning and application of sonoanatomy, which may help anesthesiologists perform more accurate and successful blocks. We believe that the findings could contribute to regional anesthesia training. The study poses no risks to participants.

Study Type, Scope, and Design:

This prospective, observational study will be conducted at Health Sciences University Istanbul Kanuni Sultan Süleyman Education and Research Hospital. Ultrasound images from patients aged 18 and older undergoing regional anesthesia under ultrasound guidance will be photographed, without collecting personal data. Detailed images of the ultrasound-guided block steps will be captured. The position and orientation of the ultrasound probe will be documented for the AI model.

A customized GPT-4 model will be developed to evaluate the sonoanatomical structures in the provided ultrasound images based on the probe's position and orientation. Additionally, the AI model will predict which block is being performed and assess the success of the block by analyzing the images. An experienced anesthesiologist will evaluate the accuracy of the AI's predictions.

Eligibility criteria:
Inclusion Criteria:

* Patients aged 18 years or older.
* Patients undergoing surgery.
* Patients receiving any regional anesthesia technique under ultrasound guidance.
* Patients who have signed an informed consent form.

Exclusion Criteria:

* Patients under the age of 18.
* Patients without a history of surgery.
* Patients who have not received any regional anesthesia technique under ultrasound guidance.
* Patients who have not signed the required informed consent documents will not be included in the study.

Outcomes:
accuracy of ChatGPT-4