Influencing factors and prediction of growth heterogeneity in solid nodule non-small cell lung cancer based on artificial intelligence: a prospective study.

ABSTRACT:

Background

The identification of rapidly growing solid nodules (SNs) through various preliminary examinations and their prompt removal can significantly improve the prognosis of patients with solid nodular lung cancer. However, previous studies have mostly focused on determining the nature of the solid nodules, with limited research on their growth heterogeneity. This study aimed to identify multi-dimensional factors influencing rapid nodule growth based on clinical, imaging, pathological, and genetic characteristics and provide a predictive model for solid nodule lung cancer growth.

Methods

We prospectively analyzed 250 pathologically confirmed non-small cell lung cancer (NSCLC) nodules. Patients underwent preoperative thin-layer computer tomography (CT) scans with a median

SUBMITTER: Chen J 

PROVIDER: S-EPMC12605479 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature