CT Slice Thickness and Convolution Kernel Affect Performance of a Radiomic Model for Predicting EGFR Status in Non-Small Cell Lung Cancer: A Preliminary Study

We evaluated whether the optimal selection of CT reconstruction settings enables the construction of a radiomics model to predict epidermal growth factor receptor (EGFR) mutation status in primary lung adenocarcinoma (LAC) using standard of care CT images. Fifty-one patients (EGFR:wildtype = 23:28)...

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Detalles Bibliográficos
Autores principales: Li, Yajun, Lu, Lin, Xiao, Manjun, Dercle, Laurent, Huang, Yue, Zhang, Zishu, Schwartz, Lawrence H., Li, Daiqiang, Zhao, Binsheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6297245/
https://www.ncbi.nlm.nih.gov/pubmed/30559455
http://dx.doi.org/10.1038/s41598-018-36421-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6297245/
https://www.ncbi.nlm.nih.gov/pubmed/30559455
http://dx.doi.org/10.1038/s41598-018-36421-0

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