Diagnoses DiseaseR-EBUSNCT04497233
Prediction Model of Peripheral Pulmonary Lesions Based on R-EBUS Image
An observational study of Diagnoses Disease, run by Shanghai Chest Hospital at 1 site in China.
Trial summary
Peripheral pulmonary lesions(PPLs) have a wide spectrum of diseases, and the diagnosis will affect the treatment strategy and prognosis. Radial endobronchial ultrasound (R-EBUS) can be used for non-invasive diagnosis of PPLs, and the supplement pathological diagnosis results of EBUS-TBLB, which has important clinical… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Diagnoses Disease
- How many people
- 1,300 participants
- Where
- 1 siteChina
- Study dates
- 1 Jul 2018to 31 Mar 2021
- 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 18 years and older
- All sexes
- Adult, Older adult
Study population: The population of this study are those who meet the inclusion and exclusion criteria.
Who may be able to join
- Patients with PPLs in Chest CT or PET / CT;
- Chest CT or PET / CT shows PPLs with diameter greater than 8 mm;
- Patients agree to perform EBUS-TBLB and sign the informed consent.
Who cannot join
- Thin-layer Chest CT or PET / CT indicates lack of bronchial access to PPLs;
- Patients refuse to participate in this clinical trial;
- Patients with severe cardiopulmonary dysfunction or other indications that not allowed for bronchoscopy;
- Visible lesions in the lumen during conventional bronchoscopy;
- Patients have other related contraindications of bronchoscopy;
- Patients have other reasons unfit for this study.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Shanghai Chest Hospital
Shanghai
Jiayuan Sun, PhD, 18017321598, jysun1976@163.com
About this study
Official title: Prediction Model of Benign and Malignant Peripheral Pulmonary Lesions Based on Image of Radial Endobronchial Ultrasound
Peripheral pulmonary lesions(PPLs) have a wide spectrum of diseases, and the diagnosis will affect the treatment strategy and prognosis. Radial endobronchial ultrasound (R-EBUS) can be used for non-invasive diagnosis of PPLs, and the supplement pathological diagnosis results of EBUS-TBLB, which has important clinical application value. This project intends to select representative images from R-EBUS dynamic videos for qualitative and quantitative analysis, to establish and verify the diagnostic evaluation system of R-EBUS forPPLs. Then build 1,000 R-EBUS image databases of PPLs, train deep learning networks for automatic extraction and diagnosis of target areas, and automatically extract representative images from videos to establish a benign and malignant prediction model of PPLs. We will provide reliable theoretical basis for the diagnosis of PPLs, and optimize the diagnosis and treatment method.The network would be prospectively verified through 300 R-EBUS images from multi centers.
Read the detailed description
PPLs are lesions at tertiary bronchus and above. The lesion cannot be seen by conventional bronchoscopy and the diagnosis will affect the treatment strategy and prognosis. R-EBUS can be used for non-invasive diagnosis of PPLs, and the supplement pathological diagnosis results of EBUS-TBLB. During the procedure, target PPLs are examined by ultrasound host (EU-ME2, Olympus, Tokyo, Japan) equipped with Doppler function and ultrasound probe . The bronchoscope reaches the distal as far as possible according to the predetermined position on chest CT or positron emission tomography-computed tomography (PET-CT) . The R-EBUS probe is inserted into the working channel of the bronchoscope, and gradually approaches the target PPL to obtain R-EBUS image. According to the characteristics such as within or adjacent to image, the probe scan the lesion from the near end to the far end and record the video. The recording time is required longer than 10 seconds. After selecting a typical R-EBUS image, freeze the image and take a screenshot. The long and short diameter of the lesion will be measured. This project includes three parts: preliminary construction and evaluation of R-EBUS image system for benign and malignant PPLs, construction of R-EBUS artificial intelligence prediction model and multi-center prospective validation of the prediction model. A total of 1000 patients will be enrolled to construct diagnostic model and 300 are enrolled to verify the diagnostic effiency.
- Conditions
- Diagnoses Disease
- Keywords
- R-EBUS image, Deep learning, Peripheral pulmonary lesions, Prediction model, Diagnosis
- Medical subject headings
- Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Prospectively validation group | Two diagnosis methods will be used in the prospective validation section, one is traditional qualitative and quantitative method, the other is artificial intelligence prediction model based on videos to compare the diagnostic efficacy. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic efficacy of R-EBUS prediction model.
Diagnostic efficacy includes sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy
Measured: 18 months
Secondary outcomes (1)
Diagnostic efficacy of traditional qualitative and quantitative methods
Diagnostic efficacy includes sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy
Measured: 18 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Aug 2020
- Study start1 Jul 2018
- Primary completion30 Sep 2020 (estimated)
- Study completion31 Mar 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diagnoses DiseaseStudies of the same condition, open and under way.
- More trials run by Shanghai Chest 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
- Observational
- Observational model
- Case only
- Time perspective
- Other
- Enrolment
- 1,300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shanghai Chest Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Jiayuan Sun, Shanghai Chest Hospital
- Investigators
- Jiayuan Sun, PhD, Study director, Shanghai Chest Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04497233
- Sponsor's protocol ID
- SHCHE202001
- Acronym
- R-EBUS
- Status last verified
- Jul 2020
- First submitted
- 19 Jul 2020
- Last updated
- 4 Aug 2020
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 4 Aug 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prediction Model of Benign and Malignant Peripheral Pulmonary Lesions Based on Image of Radial Endobronchial Ultrasound
- ClinicalTrials.gov ID
- NCT04497233
- Acronym / sponsor ID
- R-EBUS / SHCHE202001
- Conditions
- Diagnoses Disease
- Keywords
- R-EBUS image, Deep learning, Peripheral pulmonary lesions, Prediction model, Diagnosis
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,300 participants (estimated)
- Lead sponsor
- Shanghai Chest HospitalUniversity, hospital or other
- Study start
- 1 Jul 2018 (actual)
- Primary completion
- 30 Sep 2020 (estimated)
- Study completion
- 31 Mar 2021 (estimated)
- First posted
- 4 Aug 2020 (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.
Peripheral pulmonary lesions(PPLs) have a wide spectrum of diseases, and the diagnosis will affect the treatment strategy and prognosis. Radial endobronchial ultrasound (R-EBUS) can be used for non-invasive diagnosis of PPLs, and the supplement pathological diagnosis results of EBUS-TBLB, which has important clinical application value. This project intends to select representative images from R-EBUS dynamic videos for qualitative and quantitative analysis, to establish and verify the diagnostic evaluation system of R-EBUS forPPLs. Then build 1,000 R-EBUS image databases of PPLs, train deep learning networks for automatic extraction and diagnosis of target areas, and automatically extract representative images from videos to establish a benign and malignant prediction model of PPLs. We will provide reliable theoretical basis for the diagnosis of PPLs, and optimize the diagnosis and treatment method.The network would be prospectively verified through 300 R-EBUS images from multi centers.
Detailed description
PPLs are lesions at tertiary bronchus and above. The lesion cannot be seen by conventional bronchoscopy and the diagnosis will affect the treatment strategy and prognosis. R-EBUS can be used for non-invasive diagnosis of PPLs, and the supplement pathological diagnosis results of EBUS-TBLB. During the procedure, target PPLs are examined by ultrasound host (EU-ME2, Olympus, Tokyo, Japan) equipped with Doppler function and ultrasound probe . The bronchoscope reaches the distal as far as possible according to the predetermined position on chest CT or positron emission tomography-computed tomography (PET-CT) . The R-EBUS probe is inserted into the working channel of the bronchoscope, and gradually approaches the target PPL to obtain R-EBUS image. According to the characteristics such as within or adjacent to image, the probe scan the lesion from the near end to the far end and record the video. The recording time is required longer than 10 seconds. After selecting a typical R-EBUS image, freeze the image and take a screenshot. The long and short diameter of the lesion will be measured. This project includes three parts: preliminary construction and evaluation of R-EBUS image system for benign and malignant PPLs, construction of R-EBUS artificial intelligence prediction model and multi-center prospective validation of the prediction model. A total of 1000 patients will be enrolled to construct diagnostic model and 300 are enrolled to verify the diagnostic effiency.
Study design
- Observational model
- Case only
- Time perspective
- Other
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Prospectively validation group | – | –Two diagnosis methods will be used in the prospective validation section, one is traditional qualitative and quantitative method, the other is artificial intelligence prediction model based on videos to compare the diagnostic efficacy. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- The population of this study are those who meet the inclusion and exclusion criteria.
Key inclusion criteria (3 listed)
- Patients with PPLs in Chest CT or PET / CT;
- Chest CT or PET / CT shows PPLs with diameter greater than 8 mm;
- Patients agree to perform EBUS-TBLB and sign the informed consent.
Key exclusion criteria (6 listed)
- Thin-layer Chest CT or PET / CT indicates lack of bronchial access to PPLs;
- Patients refuse to participate in this clinical trial;
- Patients with severe cardiopulmonary dysfunction or other indications that not allowed for bronchoscopy;
- Visible lesions in the lumen during conventional bronchoscopy;
- Patients have other related contraindications of bronchoscopy;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Diagnostic efficacy of R-EBUS prediction model.
Time frame: 18 months
Diagnostic efficacy includes sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy
1 secondary outcome
Diagnostic efficacy of traditional qualitative and quantitative methods
Time frame: 18 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Aug 2020.
- Individual participant dataSharing planned: Undecided
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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.
Jiayuan Sun, PhD study director
Shanghai Chest Hospital
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 Diagnoses Disease, run by Shanghai Chest 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 3 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: status not confirmed, as of the sponsor's last update on 4 Aug 2020. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Jiayuan Sun, PhD (18017321598, jysun1976@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic efficacy of R-EBUS prediction model. (time frame: 18 months). 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 4 Aug 2020.