Exploring the Efficacy of Assistive Artificial Intelligence for Ultrasound Guided Regional Anesthesia in Residency Training

NCT06667401 | Completed DMC FDA Device

• 1 other identifier: PRO00052792
• Study Type: observational
• Target: 20
• Locations: 1 country
• Sites: 1

Brief Summary

The purpose of this study is to investigate the efficacy of a novel artificial intelligence (AI) device designed to assist in Ultrasound guided regional anesthesia (ScanNav Anatomy Peripheral Nerve Block; ScanNav), in the teaching and training of anesthesiology residents in the subspecialty of regional anesthesia.

Conditions

Regional Anesthesia

Keywords

Regional anesthesia; Artificial Intelligence; Resident training

Outcome Measures

Primary Outcomes (1)

• Qualtric questionaire of participants

  Improved teaching and training of anesthesiology residents in the subspecialty of regional anesthesia will be accessed via a questionnaire filled out by participants after use of the device. The questionnaire will access, the type of regional blocks, feasibility of block and ease of teaching with the artificial intelligence Ultrasound.

  From enrollment to the end of device use at 2 weeks.

Study Arms (1)

The study will recruit the entire CA1 resident class (n=20)

The study will recruit the entire CA1-2 resident class (n=20-30) who have no prior experience with Ultrasound guided regional anesthesia (UGRA) at the Medical College of Wisconsin/Froedtert Hospital. Inclusion criteria include having no prior experience with UGRA. Exclusion criteria include having undergone the regional elective service prior to the inception of the study (CA-2/3 class). No intervention of interest is noted, the cohort will be accessed based on use of the artificial intelligent Ultrasound.

Device: The ScanNav, a novel artificial intelligence device designed to assist in Ultrasound guided regional anesthesia

Interventions

The ScanNav, a novel artificial intelligence device designed to assist in Ultrasound guided regional anesthesia DEVICE

The ScanNav, a novel artificial intelligence device designed to assist in Ultrasound guided regional anesthesia.We also aim to see of how it enhances teaching and training of residents by experienced regional anesthesia providers. We intend to use surveys/questionnaires of both resident and regional anesthesia provider as they utilize the device in real time.

The study will recruit the entire CA1 resident class (n=20)

Eligibility Criteria

• Sex: all
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The student population includes anesthesia residents in training, and experienced regional anesthesia providers.

Sponsors & Collaborators

• Medical College of Wisconsin: lead

Study Sites (1)

Medical College of Wisconsin

Milwaukee, Wisconsin, 53226, United States

Location

Related Publications (1)

• Bowness JS, El-Boghdadly K, Woodworth G, Noble JA, Higham H, Burckett-St Laurent D. Exploring the utility of assistive artificial intelligence for ultrasound scanning in regional anesthesia. Reg Anesth Pain Med. 2022 Jun;47(6):375-379. doi: 10.1136/rapm-2021-103368. Epub 2022 Jan 28.

  PMID: 35091395 BACKGROUND

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 2 Weeks
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: MD

Study Record Dates

• First Submitted: October 27, 2024
• First Posted: October 31, 2024
• Study Start: March 10, 2025
• Primary Completion: January 1, 2026
• Study Completion: January 1, 2026
• Last Updated: March 3, 2026

Record last verified: 2024-10

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, CSR
• Time Frame: When published with ICMJE journal and as requested.

Locations

US (1)