Exploration and Study on the Identification of Various Pulmonary Diseases Using Volatile Organic Compounds Biomarkers in Human Exhaled Breath

Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Observational
SUMMARY

The goal of this observational study is to develop an advanced expiratory algorithm model utilizing exhaled breath volatile organic compound (VOC) marker molecules. This model aims to accurately diagnose mutiple pulmonary diseases. 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 diagnose several common pulmonary diseases. 2. To assess the diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in diagnose more pulmonary diseases.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Maximum Age: 100
Healthy Volunteers: t
View:

• Males or females, age must be 18 years old or above.

• Patients must meet the CT imaging diagnostic criteria for different lung diseases, and patients must be able to provide electronic versions of CT image data.

• Patients must have a clear clinical diagnosis.

• All participants must sign a written informed consent form.

Locations
Other Locations
China
The First Affiliated Hospital of Guangzhou Medical University
RECRUITING
Guangzhou
Contact Information
Primary
Hengrui Liang, MD
hengrui_liang@163.com
+86 15625064712
Time Frame
Start Date: 2024-06-30
Estimated Completion Date: 2027-06-30
Participants
Target number of participants: 10000
Treatments
pulmonary disease
Individuals with abnormalities in lung CT imaging and clinically diagnosed with lung cancer, lung infection, chronic obstructive pulmonary disease (COPD), bronchitis, pulmonary fibrosis, pulmonary embolism, pulmonary arterial hypertension, tuberculosis, lung abscess, emphysema, radioactive lung injury, cystic fibrosis of the lung, Bronchial Asthma, Bronchiectasis, interstitial lung disease (ILD), preserved ratio impaired spirometry (PRISm) etc .
normal individual
Individuals with no abnormalities detected in lung CT imaging.
Sponsors
Collaborators: Shanghai Chest Hospital, Peking Union Medical College Hospital, The First Affiliated Hospital of Guangzhou Medical University, Huangpu District Xinlong Town Central Hospital, Fifth Affiliated Hospital of Guangzhou Medical University, Huangpu District Hongshan Street Community Health Service Center, Huangpu District Jiufo Street Community Health Service Center, First People's Hospital of Foshan, Guangzhou Development Zone Hospital, Huangpu District Lianhe Street Second Community Health Service Center, Sichuan Cancer Hospital and Research Institute, Huangpu District Yonghe Street Community Health Service Center, Huangpu District Chinese Medicine Hospital, Liwan District Central Hospital
Leads: ChromX Health

This content was sourced from clinicaltrials.gov