Classification of Benign and Malignant Lung Nodules Based on CT Raw Data
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|ClinicalTrials.gov Identifier: NCT04241614|
Recruitment Status : Recruiting
First Posted : January 27, 2020
Last Update Posted : January 28, 2020
|Condition or disease||Intervention/treatment|
|Lung Cancer Image, Body||Other: No interventions|
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 :||Observational|
|Estimated Enrollment :||400 participants|
|Official Title:||Comparison and Analysis of Predictive Performance of CT and Raw Data in Benign and Malignant Classification of Pulmonary Nodules|
|Actual Study Start Date :||April 15, 2019|
|Estimated Primary Completion Date :||February 15, 2020|
|Estimated Study Completion Date :||April 15, 2024|
The First Hospital of Ji Lin University
CT data and corresponding CT raw data of patients with lung nodule will be collected.
Other: No interventions
- 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.
- 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.
- 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.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04241614
|Contact: Di Dong, Ph.D.||+86 email@example.com|
|The First Hospital of Ji Lin University||Recruiting|
|Changchun, Jilin, China, 130021|
|Contact: Di Dong, Ph.D. +86 13811833760 firstname.lastname@example.org|
|Study Director:||Yali Zang, Ph.D.||Institute of Automation, Chinese Academy of Sciences|