2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer.

ABSTRACT:

Objective

To compare 2D and 3D radiomics features prognostic performance differences in CT images of non-small cell lung cancer (NSCLC).

Method

We enrolled 588 NSCLC patients from three independent cohorts. Two sets of 463 patients from two different institutes were used as the training cohort. The remaining cohort with 125 patients was set as the validation cohort. A total of 1014 radiomics features (507 2D features and 507 3D features correspondingly) were assessed. Based on the dichotomized survival data, 2D and 3D radiomics indicators were calculated for each patient by trained classifiers. We used the area under the receiver operating characteristic curve (AUC) to assess the prediction performance of trained classifiers (the support vector machine and logistic regressio

SUBMITTER: Shen C 

PROVIDER: S-EPMC5605492 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature