A Multicenter Cohort Study of AI-Based Methods for Pulmonary Nodule Diagnosis and Follow-up

A Prospective, Multicentre Cohort Study of Artificial Intelligence-based Methods for Pulmonary Nodule Segmentation, Benign-Malignant Risk Stratification, and Follow-up

This is an observational, multicentre study. The primary objective of this study was to evaluate the diagnostic performance and clinical applicability of artificial intelligence models for pulmonary nodule segmentation, benign-malignant risk stratification, and follow-up management. We will collect CT images and medical data from participants at several hospitals. Participants will not receive any drugs or medical interventions.

Inclusion Criteria:

(1) Age ≥18 years; (2) At least one non-calcified pulmonary nodule (diameter ≥3 mm and ≤30 mm) detected on chest CT; (3) Agreement to participate in the study and provision of written informed consent.

-

Exclusion Criteria:

1. Poor CT image quality with severe artifacts that preclude AI-based analysis;
2. Expected survival <12 months or inability to complete follow-up;
3. History of prior ipsilateral lung malignancy or local treatment. -