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

Fudan University

Status: Completed

Conditions: Ultrasound Therapy; Complications

Treatments: Procedure: ultrasound examination

Study type: Interventional

Funder types: Other

Identifiers

NCT04183972

KY2019-502

Details and patient eligibility

About

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.

Full 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.

Enrollment: 1,126 patients

Sex: All

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

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

Trial design

Primary purpose: Diagnostic

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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1,126 participants in 1 patient group

Image collecting Group

Experimental group

Description:

An computer algorithm will be developed and evaluated by these image data.

Treatment:

Procedure: ultrasound examination