NCT06458673

A Prospective, Non-interventional Cohort Study of Subsolid Pulmonary Nodules

Prediction of Growth Trend of Pulmonary Nodules Based on Multi-temporal and Multimodal Medical Data and Its Impact on Pulmonary Nodule Management Strategies

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 1,184 (estimated)
• Sponsor: Guangdong Provincial People's Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

Some studies have shown that the model for judging and predicting the growth of sub-solid pulmonary nodules through big data and deep learning can detect nodule growth earlier. Since most of the training data come from large foreign samples, most of the validated data are CT data from a single center or a few centers, and their generalization ability needs to be further verified. In order to better study subsolid pulmonary nodules in the lungs in China, we plan to conduct a prospective, multicenter, non-interventional observational cohort study.

Detailed description

Through the follow-up of pulmonary nodules, artificial intelligence based on CT was used to study the natural evolution process of subsolid pulmonary nodules, as well as the development law and prognosis of pulmonary subsolid nodules under treatment or no treatment according to clinical guidelines.

Conditions

• Solitary Lung Nodule
• Multiple Pulmonary Nodules

Timeline

• Start date: 2024-12-01
• Primary completion: 2030-11-30
• Completion: 2030-11-30
• First posted: 2024-06-13
• Last updated: 2024-12-02

Locations

1 site across 1 country: China