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

NCT ID: NCT04918693

Last Updated: 2022-04-01

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

34 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-05-16

Study Completion Date

2021-11-30

Brief Summary

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

Detailed Description

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Background:

The American Society of Regional Anesthesia and Pain Medicine (ASRA) has published evidence-based assessment of ultrasound-guided regional anesthesia (Neal et al., 2010) concluding that ultrasound guidance is superior or equal to other non-ultrasound nerve localization techniques. A subsequent publication from ASRA (Neal et al., 2016), has strengthened their position of ultrasound guidance being superior than other methods, including for the reduction of local anesthetic systemic toxicity. However, ultrasound-guided regional anesthesia (UGRA) is a difficult technique to master. A key activity of UGRA is ultrasound image interpretation (Sites et al., 2009) which ScanNav Anatomy PNB is designed to support.

Methodology:

15 participants (anesthesiologists capable of independently performing UGRA) will be recruited to evaluate the performance and benefit of ScanNav Anatomy PNB device in person, by scanning 2 healthy models (n=1 BMI\<30, n=1 BMI\>=30 kg/m2).

The device performance and benefits will be ascertained once the scanning session for each block is complete by use of a structured questionnaire.

* Participants will be asked to scan a model with and without the use of ScanNav Anatomy PNB. The order of with/without the device will be randomized between participants.
* Participants will also be asked to supervise a trainee (another healthcare professional qualified to perform the UGRA procedure under supervision) while they are scanning models with and without ScanNav Anatomy PNB aid. The participant will always use the device first before supervising the trainee.
* The above will be performed on 2 models from different BMI categories (n=1 BMI\<30, n=1 BMI\>=30 kg/m2; total scans n=16).
* The order of models will be randomized between participants.
* All 9 supported regions will be evaluated; each region will be scanned/evaluated at least 3 times.

Data collection

\- Participants and trainees will be asked to complete a structured questionnaire to assess the device performance and clinical benefits at the end of scanning for the block.

Data analysis:

* Data will be aggregated and evaluated on safety critical structure type basis.
* Quantitative data obtained from the participants will be presented as frequencies and expressed as percent of total or as mean ± s.d. where appropriate.

The collected data and overall performance and benefits of ScanNav Anatomy PNB will be evaluated and summarized by presence and absence of ScanNav Anatomy PNB assistance, trainee and stratified by low/high BMI model.

Independent expert evaluation

* The scans be recorded during the study sessions. These scans will be post processed to short clips (10 seconds prior to obtaining optimum view) and sent for evaluation to an independent expert panel.
* The expert panel will be asked to evaluate the scans and the ScanNav Anatomy PNB highlighting performance independently from the participant. The majority opinion (at least 2/3) will be obtained to establish the agreement (e.g., yes/yes/no = yes)
* The answers obtained during the scan session from participants will be compared to expert panel view. Independent comparisons between performance assessment will be made, providing that the expert panel view is the 'ground truth'.
* Data will be evaluated and presented by safety structure on each model and overall (i.e., total for each class of safety critical structure; nerve, artery etc.).

Conditions

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Ultrasound Imaging of Anatomical Structures

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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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.

Ultrasound scanning

Intervention Type 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.

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

Ultrasound scanning

Intervention Type 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.

Interventions

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Ultrasound scanning

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.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

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


1. U.S. board-eligible/board-certified health practitioner who holds a qualification licensing to perform UGRA
2. NOT capable or confident of independent UGRA practice


1. Male or female, at least 18 years of age;
2. Able to comprehend and sign the Informed Consent prior to enrolment in the study.
3. To fit either BMI category: BMI \<30 OR BMI \>=30

Exclusion Criteria

1. Unwilling or unable to provide informed consent.
2. Involved in development of the ScanNav Anatomy PNB device.


1. Unwilling or unable to provide informed consent.
2. Involved in development of the ScanNav Anatomy PNB device.


1. Aged \<18 years of age or over 60 years or age
2. Unwilling or unable to provide informed consent.
3. BMI\> 39 kg/m2
4. Known pathology of the area to be scanned.
Minimum Eligible Age

18 Years

Maximum Eligible Age

70 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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IntelligentUltrasound Limited

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Glenn Woodworth, MD

Role: PRINCIPAL_INVESTIGATOR

Oregon Health and Science University

James Bowness, MD

Role: PRINCIPAL_INVESTIGATOR

University of Oxford & Royal Gwent Hospital

Locations

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Oregon Health & Science University

Portland, Oregon, United States

Site Status

Countries

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United States

References

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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.

Reference Type DERIVED
PMID: 35091395 (View on PubMed)

Other Identifiers

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IU2021_AG_08

Identifier Type: -

Identifier Source: org_study_id

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