Benign and Malignant Lymph NodesNCT06351319
Ultrasound Imaging Based on Ultrasound Bronchoscopy in Respiratory Diseases: a Retrospective, Single-center, Confirmatory Study
An observational study of Benign and Malignant Lymph Nodes, run by Quncheng Zhang at 1 site in China.
Trial summary
ABSTRACT Background and objective: To establish a ultrasound radiomics machine learning model based on endobronchial ultrasound (EBUS)to assistdoctors in distinguishing between benign and malignant diagnoses ofmediastinal and hilar lymph nodes. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Benign and Malignant Lymph Nodes
- What is being tested?
- SVM model
- How many people
- 197 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2018to 1 Apr 2024
- Phase
- Observational
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Henan Provincial People's Hospital
Who may be able to join
- (1)chest CT showing enlarged mediastinal or hilar lymph nodes or positive findings of mediastinal and hilar lymph nodes on PET/CT (SUV≥2.5); (2)patients who underwent EBUS-TBNA examination; (3)no contraindications for surgery.
Who cannot join
- (1)prior treatment of target lymph nodes before EBUS-TBNA; (2)unclear diagnostic results; (3)loss to follow-up.
Trial locations and contacts
1 site in 1 country.
China1 site
Department of Respiratory and Critical Care Medicine
Zhengzhou, Henan, 450000
About this study
ABSTRACT Background and objective: To establish a ultrasound radiomics machine learning model based on endobronchial ultrasound (EBUS)to assistdoctors in distinguishing between benign and malignant diagnoses ofmediastinal and hilar lymph nodes.
Methods: The clinical and ultrasonic image data of 197 patients wereretrospectively analyzed. The radiomics features were extracted by EBUS.based radiomics and dimensionality reduction was performed on thesefeatures by the least absolute shrinkage and selection operator (LASSO)EBUS-based radiomics model was established by support vector machine(SVM).205 lesions were randomly divided into a training group (n=143)and a validation group (n=62). The diagnostic efficiency was evaluated byreceiver operating characteristic (ROC).Results: A total of 13 stable features with non-zero coefficients wereselected. The support vector machine (SV) model exhibited promisingperformance in both the training and verification groups. In the traininggroup, the SVM model achieved an area under the curve (AUC) of 0.892(95% CI: 0.885-0.899), with an accuracy of 85.3%, sensitivity of 93.2%and specificity of 79.8%.In the verification group, the SVM modeldemonstrated an AUC of 0.906 (95% C: 0.890-0.923),along with anaccuracy of 74.2%,sensitivity of 70.3%, and specificity of 74.1% Conclusion:EBUS-based radiomics model can be used to differentiatemediastinal and hilar benign and malignant lymph nodes. The SVM modeldemonstrates superiority and holds potential as a diagnostic tool in clinical practice
- Conditions
- Benign and Malignant Lymph Nodes
- Being tested
- SVM model
- Keywords
- mediastinal and hilar lymph nodes, benign and malignant, endobronchial ultrasound-based radiomics, distinguishing, support vector machine
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
SVM modelDiagnostic test
Bronchoscopic ultrasound images were analyzed according to SVM mode
| Study group | Role | What they receive |
|---|---|---|
| training group | Not described Receives: Diagnostic Test: SVM model | |
| validation group | Not described Receives: Diagnostic Test: SVM model |
What is being measured
The primary outcome is the main question the study is designed to answer.
AUC
Judge the validity and accuracy of the model
Measured: One month
accuracy
Judge the validity and accuracy of the model
Measured: One month
sensitivity
Judge the validity and accuracy of the model
Measured: One month
specificity
Judge the validity and accuracy of the model
Measured: One month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Apr 2024
- Study start1 Jan 2018
- Primary completion1 Dec 2023
- Study completion1 Apr 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Benign and Malignant Lymph NodesStudies of the same condition, open and under way.
- 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
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 197 participants (actual)
Sponsor and investigators
- Lead sponsor
- Quncheng Zhang
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Quncheng Zhang, Henan Provincial People's Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06351319
- Sponsor's protocol ID
- HenanPPH-zhangquncheng
- Status last verified
- May 2024
- First submitted
- 2 Apr 2024
- Last updated
- 24 May 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 May 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Ultrasound Imaging Based on Ultrasound Bronchoscopy in Respiratory Diseases: a Retrospective, Single-center, Confirmatory Study
- ClinicalTrials.gov ID
- NCT06351319
- Acronym / sponsor ID
- HenanPPH-zhangquncheng
- Conditions
- Benign and Malignant Lymph Nodes
- Keywords
- mediastinal and hilar lymph nodes, benign and malignant, endobronchial ultrasound-based radiomics, distinguishing, support vector machine
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 197 participants (actual)
- Lead sponsor
- Quncheng ZhangUniversity, hospital or other
- Study start
- 1 Jan 2018 (actual)
- Primary completion
- 1 Dec 2023 (actual)
- Study completion
- 1 Apr 2024 (actual)
- First posted
- 8 Apr 2024 (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.
ABSTRACT Background and objective: To establish a ultrasound radiomics machine learning model based on endobronchial ultrasound (EBUS)to assistdoctors in distinguishing between benign and malignant diagnoses ofmediastinal and hilar lymph nodes.
Methods: The clinical and ultrasonic image data of 197 patients wereretrospectively analyzed. The radiomics features were extracted by EBUS.based radiomics and dimensionality reduction was performed on thesefeatures by the least absolute shrinkage and selection operator (LASSO)EBUS-based radiomics model was established by support vector machine(SVM).205 lesions were randomly divided into a training group (n=143)and a validation group (n=62). The diagnostic efficiency was evaluated byreceiver operating characteristic (ROC).Results: A total of 13 stable features with non-zero coefficients wereselected. The support vector machine (SV) model exhibited promisingperformance in both the training and verification groups. In the traininggroup, the SVM model achieved an area under the curve (AUC) of 0.892(95% CI: 0.885-0.899), with an accuracy of 85.3%, sensitivity of 93.2%and specificity of 79.8%.In the verification group, the SVM modeldemonstrated an AUC of 0.906 (95% C: 0.890-0.923),along with anaccuracy of 74.2%,sensitivity of 70.3%, and specificity of 74.1% Conclusion:EBUS-based radiomics model can be used to differentiatemediastinal and hilar benign and malignant lymph nodes. The SVM modeldemonstrates superiority and holds potential as a diagnostic tool in clinical practice
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| training group | – | Diagnostic Test: SVM model |
| validation group | – | Diagnostic Test: SVM model |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Henan Provincial People's Hospital
Key inclusion criteria (1 listed)
- (1)chest CT showing enlarged mediastinal or hilar lymph nodes or positive findings of mediastinal and hilar lymph nodes on PET/CT (SUV≥2.5); (2)patients who underwent EBUS-TBNA examination; (3)no contraindications for surgery.
Key exclusion criteria (1 listed)
- (1)prior treatment of target lymph nodes before EBUS-TBNA; (2)unclear diagnostic results; (3)loss to follow-up.
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 |
|---|---|---|
| SVM modelBronchoscopic ultrasound images were analyzed according to SVM mode | Diagnostic test | training group, validation group |
Primary outcome
AUC
Time frame: One month
Judge the validity and accuracy of the model
accuracy
Time frame: One month
Judge the validity and accuracy of the model
sensitivity
Time frame: One month
Judge the validity and accuracy of the model
specificity
Time frame: One month
Judge the validity and accuracy of the model
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 24 May 2024.
- 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.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Benign and Malignant Lymph Nodes, run by Quncheng Zhang 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 1 inclusion and 1 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 24 May 2024. 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?
AUC (time frame: One month). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 24 May 2024.