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ABSTRACT: Objectives
To investigate the value of imaging in predicting the growth rate of early lung adenocarcinoma.Methods
From January 2012 to June 2018, 402 patients with pathology-confirmed lung adenocarcinoma who had two or more thin-layer CT follow-up images were retrospectively analyzed, involving 407 nodules. Two complete preoperative CT images and complete clinical data were evaluated. Training and validation sets were randomly assigned according to an 8:2 ratio. All cases were divided into fast-growing and slow-growing groups. Researchers extracted 1218 radiomics features from each volumetric region of interest (VOI). Then, radiomics features were selected by repeatability analysis and Analysis of Variance (ANOVA); Based on the Univariate and multivariate analyses, the sign
SUBMITTER: Tan M
PROVIDER: S-EPMC8082461 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature