Evaluating Solid Lung Adenocarcinoma Anaplastic Lymphoma Kinase Gene Rearrangement Using Noninvasive Radiomics Biomarkers.
De-Ning MaXin-Yi GaoYi-Bo DanAn-Ni ZhangWei-Jun WangGuang YangHong-Zhou ZhuPublished in: OncoTargets and therapy (2020)
Solid lung adenocarcinoma ALK+ radiogenomics classifier of standard post-contrast CT radiomics biomarkers produced superior performance compared with that of pre-contrast one, suggesting that post-contrast CT radiomics should be recommended in the context of solid lung adenocarcinoma radiogenomics AI. Standard post-contrast CT machine learning radiogenomics classifier could help precisely identify solid adenocarcinoma ALK rearrangement status, which may act as a pragmatic and cost-efficient substitute for traditional invasive ALK status test.
Keyphrases
- contrast enhanced
- magnetic resonance imaging
- magnetic resonance
- computed tomography
- machine learning
- dual energy
- advanced non small cell lung cancer
- artificial intelligence
- image quality
- positron emission tomography
- clinical trial
- gene expression
- genome wide
- copy number
- radiation therapy
- dna methylation
- study protocol
- double blind