- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03872362
Radiomics Multifactorial Biomarker for Pulmonary Nodules (RMBPN)
Radiomics and Clinical Variables Can Differentiate Malignant Nodules and Detect Invasive Adenocarcinoma in Pulmonary Nodules: a Multi-center Study
Study Overview
Status
Intervention / Treatment
Detailed Description
With the development of computed tomography (CT) equipment and the increasing use of lung cancer screening programs with low-dose CT, a growing number of early-stage lung cancers were detected so that a large number of patients have undergone surgery.
Although a number of radiological studies have been used morphological signs so-called semantic features to make a differential diagnosis, it is still hard to apply by clinician because pulmonary nodules especially ground-glass nodules and small size nodules have atypical radiology signs and have strong subjectivity from different observers. Recently, CT-based radiomics, extracting the quantitative high-throughput features from medical images and facilitating clinical decision-making system, showed a good performance to predict diagnosis and prognosis of diverse cancer.
Therefore, the proposed project aims to develop and validate radiomics models based on CT images to identify malignant nodules and then to discriminate the different types of lung adenocarcinoma in patients with pulmonary nodules.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
-
-
Liaoning
-
Dalian, Liaoning, China, 116000
- Affiliated Zhongshan Hospital of Dalian University
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- intraoperative frozen section diagnosis and final pathology diagnosis are available
- preoperative standard non-enhanced CT is available
- Pathologically confirmed
Exclusion Criteria:
- with a previous history of radiation therapy, chemotherapy or biopsy
- the time interval between the CT examination and surgery was more than two weeks
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Retrospective
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Training dataset
No interventions
|
The high-throughput extraction of large amounts of quantitative image features from medical images
|
External validation1
No interventions
|
The high-throughput extraction of large amounts of quantitative image features from medical images
|
External validation2
No interventions
|
The high-throughput extraction of large amounts of quantitative image features from medical images
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Malignant nodules classifier
Time Frame: 30 days
|
Model based on Radiomic that can differentiate malignant nodules from benign nodules.
|
30 days
|
Invasive adenocarcinoma classifier
Time Frame: 30 days
|
Model based on Radiomic that can differentiate invasive adenocarcinoma from non-invasive adenocarcinoma.
|
30 days
|
Collaborators and Investigators
Publications and helpful links
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- UM2019DLABGY1
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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