Ultrasound Therapy; ComplicationsIBRUNNETNCT04183972
Identification of Interscalene Brachial Plexus on Ultrasonography Using a Deep Neural Network
A study testing ultrasound examination in people with Ultrasound Therapy; Complications, run by Huashan Hospital at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Ultrasound Therapy; Complications
- What is being tested?
- ultrasound examination
- Type of treatment
- Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,126 participants
- Where
- 1 siteChina
- Study dates
- 1 Dec 2019to 31 Oct 2020
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- ASA physical status class I or II
- scheduled for elective surgery
Who cannot join
- 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 locations and contacts
1 site in 1 country.
About this study
Official title: 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.
Read the 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.
- Conditions
- Ultrasound Therapy; Complications
- Being tested
- ultrasound examination
- Keywords
- peripheral nerve block, ultrasound image, deep neural network, brachial plexus
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ultrasound examinationProcedure or surgery
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.
| Study group | Role | What they receive |
|---|---|---|
| Image collecting Group | Experimental | An computer algorithm will be developed and evaluated by these image data. Receives: Procedure: ultrasound examination |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: immediately after the procedure
Secondary outcomes (2)
Accuracy, Sensitivity and specificity
Accuracy, Sensitivity and specificity of the network and nonexpert anesthesiologists
Measured: immediately after the procedure
The percentage of the intersection over union
between model predictions and the ground truth; between nonexpert anesthesiologist predictions and the ground truth
Measured: immediately after the procedure
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Dec 2019
- Study start1 Dec 2019
- Primary completion30 Sep 2020
- Study completion31 Oct 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Ultrasound Therapy; ComplicationsStudies of the same condition, open and under way.
- More trials run by Huashan HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- Patients who have been scheduled to surgery will be recruited for collecting ultrasound images.
- Masking
- None (open label)
- Enrolment
- 1,126 participants (actual)
Sponsor and investigators
- Lead sponsor
- Huashan Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xiao-Yu Yang, MD, Huashan Hospital
- Investigators
- Xiaoyu Yang, MD, Principal investigator, Huashan Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04183972
- Sponsor's protocol ID
- KY2019-502
- Acronym
- IBRUNNET
- Status last verified
- Jun 2021
- First submitted
- 19 Nov 2019
- Last updated
- 30 Jun 2021
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Yang XY, Wang LT, Li GD, Yu ZK, Li DL, Guan QL, Zhang QR, Guo T, Wang HL, Wang YW. Artificial intelligence using deep neural network learning for automatic location of the interscalene brachial plexus in ultrasound images. Eur J Anaesthesiol. 2022 Sep 1;39(9):758-765. doi: 10.1097/EJA.0000000000001720. Epub 2022 Jul 20.
PubMed 35919026
Study at a glance
From the registry record, last updated by the sponsor on 30 Jun 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Identification of Interscalene Brachial Plexus Automatically on Ultrasonography Using a Deep Neural Network
- ClinicalTrials.gov ID
- NCT04183972
- Acronym / sponsor ID
- IBRUNNET / KY2019-502
- Conditions
- Ultrasound Therapy; Complications
- Keywords
- peripheral nerve block, ultrasound image, deep neural network, brachial plexus
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 1,126 participants (actual)
- Lead sponsor
- Huashan HospitalUniversity, hospital or other
- Study start
- 1 Dec 2019 (actual)
- Primary completion
- 30 Sep 2020 (actual)
- Study completion
- 31 Oct 2020 (actual)
- First posted
- 3 Dec 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- Patients who have been scheduled to surgery will be recruited for collecting ultrasound images.
| Arm | Type | Receives |
|---|---|---|
| Image collecting Group | Experimental | Procedure: ultrasound examinationAn computer algorithm will be developed and evaluated by these image data. |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- ASA physical status class I or II
- scheduled for elective surgery
Key exclusion criteria (6 listed)
- skin lesion or infection of neck
- any known peripheral neuropathy
- brachial nerve plexus injury
- previous injury or operation on neck
- pregnancy
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| ultrasound examinationthe 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. | Procedure or surgery | Image collecting Group |
Primary outcome
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
2 secondary outcomes
Accuracy, Sensitivity and specificity
Time frame: immediately after the procedure
The percentage of the intersection over union
Time frame: immediately after the procedure
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Jun 2021.
- Derived from this study: PubMed 35919026Yang XY, Wang LT, Li GD, Yu ZK, Li DL, Guan QL, Zhang QR, Guo T, Wang HL, Wang YW. Artificial intelligence using deep neural network learning for automatic location of the interscalene brachial plexus in ultrasound images. Eur J Anaesthesiol. 2022 Sep 1;39(9):758-765. doi: 10.1097/EJA.0000000000001720. Epub 2022 Jul 20.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Xiaoyu Yang, MD principal investigator
Huashan Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing ultrasound examination in people with Ultrasound Therapy; Complications, run by Huashan Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 30 Jun 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The distance of the lateral midpoints of the nerve sheath contours (time frame: immediately after the procedure). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04183972, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 30 Jun 2021.