1331 Objectives: The growth pattern of invasive lung adenocarcinoma (IAC) manifesting as
ground-glass opacity nodules (GGNs), is divided into lepidic, acinar, papillary …

Background To establish and validate 18 F-fluorodeoxyglucose (18 F-FDG) PET/CT-based
radiomics model and use it to predict the intermediate-high risk growth patterns in early …

Objective To analyze the FDG-PET and high-resolution computed tomography (HRCT)
features of early lung adenocarcinoma manifesting as solitary ground-glass opacity nodules …

AIM To explore the value of 2-[18 F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission
tomography (PET)/computed tomography (CT)-based radiomics model for predicting the …

Purpose To develop and validate a clinico-biological features and 18 F-fluorodeoxyglucose
(FDG) positron emission tomography/computed tomography (PET/CT) radiomic-based …

Materials and Methods: We retrospectively identified 39 cases with stage III NSCLC who
received chemoradiotherapy and underwent planning CT and staging 18 F-FDG PET scans …

OBJECTIVE. The purpose of this study was to explore the value of FDG PET combined with
high-resolution CT (HRCT) in predicting the pathologic subtypes and growth patterns of …

Purpose To evaluate the ability of CT and PET radiomics features to classify lung lesions as
primary or metastatic, and secondly to differentiate histological subtypes of primary lung …

Purpose We sought to distinguish lung adenocarcinoma (ADC) from squamous cell
carcinoma using a machine-learning algorithm with PET-based radiomic features. Methods …

Purpose The study is to explore potential features and develop classification models for
distinguishing benign and malignant lung lesions based on CT-radiomics features and PET …