Radiomic-Based Quantitative CT Analysis of Pure Ground-Glass Nodules to Predict the Invasiveness of Lung Adenocarcinoma

Radiomic-Based Quantitative CT Analysis of Pure Ground-Glass Nodules to Predict the Invasiveness of Lung Adenocarcinoma

Objectives: To investigate the performance of radiomic-based quantitative analysis on CT images in predicting invasiveness of lung adenocarcinoma manifesting as pure ground-glass nodules (pGGNs).Methods: A total of 275 lung adenocarcinoma cases, with 322 pGGNs resected surgically and confirmed patho...

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Bibliographic Details
Main Authors: Fangyi Xu, Wenchao Zhu, Yao Shen, Jian Wang, Rui Xu, Chooah Qutesh, Lijiang Song, Yi Gan, Cailing Pu, Hongjie Hu
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-08-01
Series:Frontiers in Oncology
Subjects:
radiomics
lung cancer
adenocarcinoma
computed tomography
machine learning
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2020.00872/full

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https://www.frontiersin.org/article/10.3389/fonc.2020.00872/full

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