The purpose of this study is to compare the predictive performance of a CT-based deep learning model for pure-solid nodules classification and compared with the tumor maximum standardized uptake value on PET in a multicenter prospective cohort.

Inclusion Criteria:

• Participants scheduled for surgery for radiological finding of pulmonary pure-solid lesions from the preoperative thin-section CT scans;
• The maximum short-axis diameter of lymph nodes less than 3 cm on CT scan;
• Age ranging from 18-75 years;
• definied pathological examination report available;
• Obtained written informed consent.

Exclusion Criteria:

• Multiple lung lesions;
• Poor quality of CT images;
• Participants with incomplete clinical information;
• Participants who have received neoadjuvant therapy before initial CT evaluation.

Patients with pulmonary radiological pure-solid nodules with size less than 3cm