- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04241614
Classification of Benign and Malignant Lung Nodules Based on CT Raw Data
Comparison and Analysis of Predictive Performance of CT and Raw Data in Benign and Malignant Classification of Pulmonary Nodules
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
The routinely used diagnostic scheme of cancers follows the process of signal-to-image-to-diagnosis. It is essential to reconstruct the visible images from the signal of medical device so that the human doctor can perform diagnosis. However, the huge amount of information inside the signal is not optimally mined, which causes the current unsatisfactory performance of image based diagnosis.
In this clinical trial, we will develop an AI based diagnostic scheme for lung nodules directly from the signal (raw data) to diagnosis, skipping the reconstruction step. In this trial, we will focus on the discrimination of malignant from benign lung nodules. We will collect a dataset of patients who are screened out lung nodules. All patients undergo preoperative CT scan (raw data and CT images available) and have pathologically confirmed result of the nodules. We will build a model using only raw data for diagnosis of the lung nodules. Moreover, another model from CT image will be built for comparison.
Furthermore, we will perform follow-up on these patients and build a model based on CT raw data for prognosis analysis of lung cancer.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
-
-
Jilin
-
Changchun, Jilin, China, 130021
- The First Hospital of Ji Lin University
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Patients who are screened out lung nodule.
- The CT data and corresponding CT raw data are available before the surgery.
- Final pathology diagnosis of the malignancy of the nodule is available.
Exclusion Criteria:
- Previous history of lung malignancies.
- Artifacts on CT images seriously deteriorating the observation of the lesion.
- The time interval between CT scan and pathology diagnosis is more than 4 weeks.
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
The First Hospital of Ji Lin University
CT data and corresponding CT raw data of patients with lung nodule will be collected.
|
No interventions
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Area under the receiver operating characteristic curve (ROC)
Time Frame: 8 months
|
Area under curve (AUC) of raw data in discriminating malignant nodules from benign nodules.
|
8 months
|
Disease free survival
Time Frame: 5 years
|
The association between raw data and disease free survival (DFS), which defined as the time from the beginning of diagnosis of lung cancer to the confirmed time of recurrence or metastatic disease, or death occurred.
|
5 years
|
Overal survival
Time Frame: 5 years
|
The association between raw data and overall survival (OS), which defined as the time from the beginning of diagnosis of lung cancer to the death with any causes.
|
5 years
|
Collaborators and Investigators
Sponsor
Investigators
- Study Director: Yali Zang, Ph.D., Institute of Automation, Chinese Academy of Sciences
Publications and helpful links
General Publications
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
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- CASMI001
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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