Use of a Radiomics Model to Predict Tumor Invasiveness of Pulmonary Adenocarcinomas Appearing as Pulmonary Ground-Glass Nodules

Background. It is important to distinguish the classification of lung adenocarcinoma. A radiomics model was developed to predict tumor invasiveness using quantitative and qualitative features of pulmonary ground-glass nodules (GGNs) on chest CT. Materials and Methods. A total of 599 GGNs [including...

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Veröffentlicht in:	BioMed research international 2018-01, Vol.2018 (2018), p.1-9
Hauptverfasser:	Pang, Peipei, Yan, Jianhua, Chen, Feng, Peng, Wei, Yao, Linpeng, Zhang, Siying, Lian, Yuqing, Cui, Feng, Huang, Qiang, Yang, Yong, Xue, Xing, Li, Xin
Format:	Artikel
Sprache:	eng
Schlagworte:	Adenocarcinoma Adenocarcinoma - diagnostic imaging Adenocarcinoma - pathology Diagnosis, Differential Family medical history Health maintenance organizations Humans Invasiveness Lesions Lung cancer Lung Neoplasms - diagnostic imaging Lung Neoplasms - pathology Lung nodules Mathematical models Medical imaging Medical prognosis Metastasis Multivariate analysis Mutation Neoplasm Invasiveness NMR Nodules Nomograms Nuclear magnetic resonance Oncology Patients Predictions Radiomics Regression analysis Retrospective Studies Studies Surgery Tomography, X-Ray Computed Tumors
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