A Study to Evaluate the Performance and Potential Benefits of an Assistive Artificial Intelligence Device ScanNav Anatomy Peripheral Nerve Block - US V1.0 for Ultrasound-guided Regional Anesthesia

NCT04918693 | Completed FDA Device

• 1 other identifier: IU2021_AG_08
• Study Type: observational
• Target: 34
• Locations: 1 country
• Sites: 1

Brief Summary

This is a single-center, prospective study to be undertaken at University of Oregon, Portland, USA. The aim is to provide data on the clinical performance of ScanNav Anatomy PNB for identification of anatomical structures during UGRA scanning, in particular:

1. 1.Assess the benefits of the device to intended users when supervising a trainee who is performing UGRA scanning.
2. 2.Assess the benefits of the device when intended users perform UGRA scanning.
3. 3.Assess risk mitigation by the intended users when performing UGRA scanning.

Conditions

Ultrasound Imaging of Anatomical Structures

Outcome Measures

Primary Outcomes (1)

• Obtaining the correct ultrasound view

  Number of participants obtaining the correct ultrasound view \[majority view, at least 8/15 participants in agreement\]

  6 months

Secondary Outcomes (4)

• Identifying anatomical structures

  6 months

• Effect of supervision in anatomical structure identification

  6 months

• Measuring operator confidence

  6 months

• Number of errors in anatomy recognition by participants

  6 months

Study Arms (2)

Participant

All 15 participants must be anesthesiologists who are competent to perform UGRA independently. In order to be eligible for the study, participants must be a U.S. board-eligible/board-certified and licensed Medical Doctor.

Device: Ultrasound scanning

Trainee

All 15 trainees must be healthcare practitioners who are licensed to perform UGRA. In order to be eligible for the study, participants must be a U.S. board-eligible/board-certified health practitioner

Device: Ultrasound scanning

Interventions

Ultrasound scanning DEVICE

All participants will scan with and without device and trainee on 4 models. The order of the device assistance and models will be randomized between participants, but participant will always have exposure to device first before supervising the trainee.

Participant; Trainee

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Participants All participants must be anesthesiologists who are competent to perform UGRA independently. In order to be eligible for the study, participants must be a U.S. board-eligible/board-certified and licensed Medical Doctor. Trainees All trainees must be healthcare practitioners who are licensed to perform UGRA. In order to be eligible for the study, participants must be a U.S. board-eligible/board-certified health practitioner. Models 4 models will be selected carefully based on their BMI inclusion criteria.

You may qualify if:

• Completed advanced training (e.g., fellowship) in or hold a qualification related to UGRA
• Regularly delivers direct clinical care using UGRA, including for 'awake' surgery where indicated
• Member of a relevant professional society (e.g., ASA, ASRA, ESRA, RA-UK)
• Regularly teach UGRA in the course of their clinical work, including advanced techniques where indicated

You may not qualify if:

• Unwilling or unable to provide informed consent.
• Involved in development of the ScanNav Anatomy PNB device.
• U.S. board-eligible/board-certified health practitioner who holds a qualification licensing to perform UGRA
• NOT capable or confident of independent UGRA practice
• Unwilling or unable to provide informed consent.
• Involved in development of the ScanNav Anatomy PNB device.
• Male or female, at least 18 years of age;
• Able to comprehend and sign the Informed Consent prior to enrolment in the study.
• To fit either BMI category: BMI \<30 OR BMI \>=30
• Aged \<18 years of age or over 60 years or age
• Unwilling or unable to provide informed consent.
• BMI\> 39 kg/m2
• Known pathology of the area to be scanned.

Sponsors & Collaborators

• IntelligentUltrasound Limited: lead

Study Sites (1)

Oregon Health & Science University

Portland, Oregon, 97239, 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 DERIVED

MeSH Terms

Interventions

Ultrasonography

Intervention Hierarchy (Ancestors)

Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis

Study Officials

• Glenn Woodworth, MD

  Oregon Health and Science University

  PRINCIPAL INVESTIGATOR

• James Bowness, MD

  University of Oxford & Royal Gwent Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 25, 2021
• First Posted: June 9, 2021
• Study Start: May 16, 2021
• Primary Completion: May 22, 2021
• Study Completion: November 30, 2021
• Last Updated: April 1, 2022

Record last verified: 2021-06

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)