Ignite Creation Date:
2024-10-26 @ 3:35 PM
Last Modification Date:
2024-10-26 @ 3:35 PM
Study NCT ID:
NCT06518655
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-07-19
Brief Title:
Differentiation of Benign and Malignant Pulmonary Nodules by Volatile Organic Compounds in Human Exhaled Breath
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Exploratory Study on the Identification of Benign and Malignant Pulmonary Nodules Using Volatile Organic Compounds in Human Exhaled Breath
Status:
RECRUITING
Status Verified Date:
2024-10
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The goal of this observational study is to develop an advanced expiratory algorithm model utilizing exhaled breath volatile organic compound VOC markers This model aims to accurately differentiate benign from malignant nodules in individuals harboring pulmonary nodules The primary objectives it strives to accomplish are
1 To assess the diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence AI model in distinguishing benign and malignant pulmonary nodules
2 To evaluate the diagnostic effectiveness of an AI model that employs exhaled breath VOC biomakers to identify specific types of malignant nodules including lung adenocarcinoma lung squamous cell carcinoma and small cell lung cancer
3 To explore and identify key characteristic VOCs combinations that are associated with EGFR site mutations in malignant nodules further modeling and evaluating the classification performance
By utilizing this comprehensive approach the study hopes to contribute significantly to early detection and accurate classification of pulmonary nodules ultimately leading to improved patient care and treatment outcomes
1 To assess the diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence AI model in distinguishing benign and malignant pulmonary nodules
2 To evaluate the diagnostic effectiveness of an AI model that employs exhaled breath VOC biomakers to identify specific types of malignant nodules including lung adenocarcinoma lung squamous cell carcinoma and small cell lung cancer
3 To explore and identify key characteristic VOCs combinations that are associated with EGFR site mutations in malignant nodules further modeling and evaluating the classification performance
By utilizing this comprehensive approach the study hopes to contribute significantly to early detection and accurate classification of pulmonary nodules ultimately leading to improved patient care and treatment outcomes
Detailed Description:
This is a prospective cross-sectional and observational cohort study aiming at recruiting 3000 participants with pulmonary nodules ranging from 5 to 30 mm in diameter Prior to invasive surgery exhaled breath samples will be collected from these participants and analyzed using Gas chromatography-mass spectrometryGC-MS and micro Gas Chromatography-photoionisation detector μGC-PID system Following the acquisition of μGC-PID results a comprehensive evaluation of the diagnostic performance of VOC biomakers distinguishing between benign and malignant pulmonary nodules will be conducted leveraging histopathological findings CT examination data and clinical data
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None