Applications of radiomics-based analysis pipeline for predicting epidermal growth factor receptor mutation status.

ABSTRACT:

Background

This study aimed to develop a pipeline for selecting the best feature engineering-based radiomic path to predict epidermal growth factor receptor (EGFR) mutant lung adenocarcinoma in ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT).

Methods

The study enrolled 115 lung adenocarcinoma patients with EGFR mutation status from June 2016 and September 2017. We extracted radiomics features by delineating regions-of-interest around the entire tumor in ¹⁸F-FDG PET/CT images. The feature engineering-based radiomic paths were built by combining various methods of data scaling, feature selection, and many methods for predictive model-building. Next, a pipeline was developed to select the best path.

Results

In

SUBMITTER: Liu Z 

PROVIDER: S-EPMC9945395 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature