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OpenTrials
Completed

NCT Number: NCT07171502

AI-Assisted Ultrasound-Guided Nerve Block: Model Development and Performance Assessment

This study intends to have experts with over 10 years of experience in ultrasound-guided regional anesthesia acquire 1,000 target images. These images will be annotated by both an AI model and human experts, and the model's annotations will be evaluated by a panel of 10 specialists. The primary outcome is the accuracy of identifying the target anatomical structures in the annotated images. Secondary outcomes include the number of true positive, false positive, true negative, and false negative structures, the time required for annotation, and the potential application of the AI model in assisting the performance of ultrasound-guided regional blocks.

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Key information

Conditions

AI (Artificial Intelligence) Ultrasound-Guided Nerve Blocks

Age range

18 year–70 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Shanghai Sixth People's Hospital Affiliated with Shanghai Jiao Tong University School of Medicine

Shanghai, China

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Aged 18-70 years
  • BMI between 19-23 kg·m-²
  • ASA physical status classification I-II
  • Normal orientation and able to cooperate with physical examination.

Exclusion criteria

  • Patient refusal
  • Infection, trauma, skin defect, deformity, or other abnormalities at the intended nerve block site
  • Pregnancy

Treatment and study plan

AI Annotation

Device

Use the AI model to assist in annotating the target images.

manual annotation

Other

Use the manual to annotate the target images.

Primary outcomes

  1. The accuracy of identifying the target anatomical structures in the annotated images.

    Time frame: From enrollment to the end of treatment at 4 months

Secondary outcomes

  1. The number of true positive (TP) structures

    Time frame: From enrollment to the end of treatment at 4 months

  2. The number of false positive (FP) structures

    Time frame: From enrollment to the end of treatment at 4 months

  3. The number of true negative (TN) structures

    Time frame: From enrollment to the end of treatment at 4 months

  4. The number of false negative (FN) structures

    Time frame: From enrollment to the end of treatment at 4 months

  5. The annotation time (time from the start to the end of annotation)

    Time frame: From enrollment to the end of treatment at 4 months

  6. An evaluation of the AI model if applied to assist in performing ultrasound-guided regional blocks: a) its impact on block failure rate (increase, no effect, decrease); b) its impact on the incidence of adverse events (increase, no effect, decrease)

    Time frame: From enrollment to the end of treatment at 4 months

Sponsors and collaborators

Lead sponsor

Shanghai Jiao Tong University Affiliated Sixth People's Hospital

Other

Registry information

Acronym: AI

Important dates

Study start
2025
Primary completion
2025
Study completion
2025
First posted
Sep 12, 2025
Registry last updated
Jan 6, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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