Total nodule number as an independent prognostic factor in resected stage III non-small cell lung cancer: a deep learning-powered study.

ABSTRACT:

Background

Almost every patient with lung cancer has multiple pulmonary nodules; however, the significance of nodule multiplicity in locally advanced non-small cell lung cancer (NSCLC) remains unclear.

Methods

We identified patients who had undergone surgical resection for stage I-III NSCLC at the Peking University People's Hospital from 2005 to 2018 for whom preoperative chest computed tomography (CT) scans were available. Deep learning-based artificial intelligence (AI) algorithms using convolutional neural networks (CNN) were applied to detect and classify pulmonary nodules (PNs). Maximally selected log-rank statistics were used to determine the optimal cutoff value of the total nodule number (TNN) for predicting survival.

Results

A total of 33,410 PNs were detecte

SUBMITTER: Chen X 

PROVIDER: S-EPMC8848356 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature