Ultrasound Therapy; Complications Clinical Trial
— IBRUNNETOfficial title:
Identification of Interscalene Brachial Plexus Automatically on Ultrasonography Using a Deep Neural Network
| Verified date | June 2021 |
| Source | Huashan Hospital |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | |
| Study type | Interventional |
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.
| Status | Completed |
| Enrollment | 1126 |
| Est. completion date | October 31, 2020 |
| Est. primary completion date | September 30, 2020 |
| Accepts healthy volunteers | No |
| Gender | All |
| Age group | 18 Years to 80 Years |
| Eligibility | 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 |
| Country | Name | City | State |
|---|---|---|---|
| China | Huashan Hospital | Shanghai | Shanghai |
| Lead Sponsor | Collaborator |
|---|---|
| Huashan Hospital |
China,
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | The distance of the lateral midpoints of the nerve sheath contours | between model predictions and the ground truth; between nonexpert anesthesiologist predictions and the ground truth | immediately after the procedure | |
| Secondary | Accuracy, Sensitivity and specificity | Accuracy, Sensitivity and specificity of the network and nonexpert anesthesiologists | immediately after the procedure | |
| Secondary | The percentage of the intersection over union | between model predictions and the ground truth; between nonexpert anesthesiologist predictions and the ground truth | immediately after the procedure |
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