Identification of Interscalene Brachial Plexus on Ultrasonography Using a Deep Neural Network (IBRUNNET)

June 28, 2021 updated by: Xiao-Yu Yang, MD, Huashan Hospital

Identification of Interscalene Brachial Plexus Automatically on Ultrasonography Using a Deep Neural Network

The purpose of the study is to develop and validate an algorithm based on deep neural networks (DNNs) to identify interscalene brachial plexus on ultrasonography automatically.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

The investigators plan to develop a deep learning-based network to automatically identify interscalene brachial nerves on ultrasound images. The trained model will be validated on an independent dataset. The performance of the network will also be compared against practicing anesthesiologists.

Study Type

Interventional

Enrollment (Actual)

1126

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Shanghai
      • Shanghai, Shanghai, China, 200040
        • Huashan Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 80 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • ASA physical status class I or II
  • scheduled for elective surgery

Exclusion Criteria:

  • skin lesion or infection of neck
  • any known peripheral neuropathy
  • brachial nerve plexus injury
  • previous injury or operation on neck
  • pregnancy
  • allergic to ultrasound gel

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Image collecting Group
An computer algorithm will be developed and evaluated by these image data.
Procedure: ultrasound examination
the participants will be placed in the supine position, with head turned slightly away from the operating side and arms beside the body. The operator will identify right and left interscalene brachial plexuses by ultrasound equipment (Sonosite EDGE or GE LOGIQ e). Clear images and videos of brachial plexus will be captured and saved.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
The distance of the lateral midpoints of the nerve sheath contours
Time Frame: immediately after the procedure
between model predictions and the ground truth; between nonexpert anesthesiologist predictions and the ground truth
immediately after the procedure

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy, Sensitivity and specificity
Time Frame: immediately after the procedure
Accuracy, Sensitivity and specificity of the network and nonexpert anesthesiologists
immediately after the procedure
The percentage of the intersection over union
Time Frame: immediately after the procedure
between model predictions and the ground truth; between nonexpert anesthesiologist predictions and the ground truth
immediately after the procedure

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Huashan Hospital

Investigators

  • Principal Investigator: Xiaoyu Yang, MD, Huashan Hospital

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 1, 2019

Primary Completion (Actual)

September 30, 2020

Study Completion (Actual)

October 31, 2020

Study Registration Dates

First Submitted

November 19, 2019

First Submitted That Met QC Criteria

November 29, 2019

First Posted (Actual)

December 3, 2019

Study Record Updates

Last Update Posted (Actual)

June 30, 2021

Last Update Submitted That Met QC Criteria

June 28, 2021

Last Verified

June 1, 2021

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • KY2019-502

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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