Predicting Ki-67 labeling index level in early-stage lung adenocarcinomas manifesting as ground-glass opacity nodules using intra-nodular and peri-nodular radiomic features.

ABSTRACT:

Objectives

To explore the diagnostic value of radiomics in differentiating between lung adenocarcinomas appearing as ground-glass opacity nodules (GGO) with high- and low Ki-67 expression levels.

Materials and methods

From January 2018 to January 2021, patients with pulmonary GGO who received lung resection were evaluated for potential enrollment. The included GGOs were then randomly divided into a training cohort and a validation cohort with a ratio of 7:3. Logistic regression (LR), decision tree (DT), support vector machines (SVM), and adaboost (AB) were applied for radiomic model construction. Area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the established models.

Results

Seven hundred

SUBMITTER: Zhu M 

PROVIDER: S-EPMC9636499 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature