Agreement Between Artificial Intelligence and Anesthesiologists in Ultrasound-Guided Axillary Brachial Plexus Block
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Ultrasound-Guided Axillary Brachial Plexus Block (Routine Clinical Practice).
- Who it may be relevant to
- Registry conditions: Ultrasound-Guided Nerve Block and Artificial Intelligence. Basic parameters: 18 years — 80 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Evaluation of Agreement Between Artificial Intelligence and Experienced Anesthesiologists in Target Point Identification for Ultrasound-Guided Axillary Brachial Plexus Block: A Prospective Observational Study
Overview
This prospective observational study aims to evaluate the agreement between artificial intelligence (AI)-assisted target point identification and experienced anesthesiologists during ultrasound-guided axillary brachial plexus block. Ultrasound guidance is widely used in regional anesthesia to improve block success and safety. However, accurate identification of anatomical structures and optimal injection points remains operator-dependent. Artificial intelligence-based systems have the potential to assist clinicians by identifying anatomical landmarks in real time. In this study, AI-generated target points will be compared with those determined by experienced anesthesiologists. The level of agreement between the two methods will be analyzed. Secondary outcomes will include block performance parameters and image quality. The findings of this study may contribute to understanding the clinical utility of AI in ultrasound-guided regional anesthesia.
Detailed description
Ultrasound-guided axillary brachial plexus block is a widely used regional anesthesia technique for upper extremity surgeries. The success of the procedure largely depends on accurate identification of neural structures and optimal injection points, which are operator-dependent.
Artificial intelligence (AI) has recently emerged as a promising tool for assisting ultrasound interpretation by automatically identifying anatomical structures. However, the level of agreement between AI-based target point identification and expert anesthesiologists has not been sufficiently investigated, particularly in axillary brachial plexus block.
In this prospective observational study, patients undergoing upper extremity surgery under axillary brachial plexus block will be included. No additional intervention will be performed on patients within the scope of the study. All evaluations will be based on real-time ultrasound imaging obtained as part of routine clinical practice.
During routine ultrasound examination prior to block performance, images will be observed in real time. Experienced anesthesiologists will determine anatomical structures and optimal target injection points during the procedure. Simultaneously, the AI-based system will analyze the same real-time ultrasound images and identify target points.
For each identified nerve (median, ulnar, radial, and musculocutaneous), both AI and anesthesiologists will determine target injection points. The spatial difference between AI-generated and expert-defined target points will be calculated in millimeters.
The primary objective is to evaluate the agreement between AI and anesthesiologists in target point identification using the intraclass correlation coefficient (ICC). Additionally, a difference of ≤5 mm between measurements will be considered clinically acceptable agreement.
Secondary outcomes will include:
Proportion of measurements within ≤5 mm agreement Agreement in nerve identification Procedure-related parameters
All expert evaluations will be performed independently and blinded to AI outputs.
This study aims to determine whether AI can reliably assist clinicians in identifying anatomical targets during ultrasound-guided regional anesthesia without introducing any additional risk to patients.
Interventions
- Procedure Ultrasound-Guided Axillary Brachial Plexus Block (Routine Clinical Practice)
Ultrasound-guided axillary brachial plexus block performed as part of routine clinical care. No additional intervention is introduced for the purposes of the study. Real-time ultrasound images obtained during the procedure will be analyzed by an artificial intelligence system and experienced anesthesiologists.
Primary outcome measures
- Agreement in Target Point Identification Between Artificial Intelligence and Anesthesiologists [Time frame: During block procedure (ultrasound imaging)]
Secondary outcome measures (3)
- Proportion of Measurements Within Clinically Acceptable Agreement [Time frame: During block procedure]
- Agreement in Nerve Identification [Time frame: During block procedure]
- Spatial Difference Between Target Points [Time frame: During block procedure]
Eligibility criteria
Inclusion criteria
- Age between 18 and 80 years
- American Society of Anesthesiologists (ASA) physical status I-III
- Patients scheduled for upper extremity surgery under ultrasound-guided axillary brachial plexus block as part of routine clinical practice
- Ability to obtain adequate real-time ultrasound imaging of the axillary region prior to block performance
- Provision of written informed consent
Exclusion criteria
- Inability to clearly visualize the axillary artery and at least one peripheral nerve (median, ulnar, radial, or musculocutaneous) on ultrasound imaging
- Presence of significant ultrasound artifacts impairing image interpretation
- History of previous surgery in the axillary region causing anatomical distortion
- Anatomical deformities or significant anatomical variations in the axillary region
- Inadequate ultrasound image quality due to severe obesity or other technical limitations
- Failure to obtain real-time ultrasound imaging prior to block performance
- Withdrawal of informed consent
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Case-only
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07532278 · 121