Predicting the ISUP grade of clear cell renal cell carcinoma with multiparametric MR and multiphase CT radiomics.
Enming CuiZhuoyong LiChangyi MaQing LiYi LeiYong LanJuan YuZhipeng ZhouRonggang LiWansheng LongFan LinPublished in: European radiology (2020)
• Both the MR- and CT-based machine learning models are reliable predictors for differentiating high- from low-grade ccRCCs. • ML models based on multiparameter MR sequences and multiphase CT images potentially outperform those based on single-sequence or single-phase images in ccRCC grading.
Keyphrases
- contrast enhanced
- low grade
- magnetic resonance imaging
- computed tomography
- magnetic resonance
- machine learning
- dual energy
- deep learning
- image quality
- high grade
- convolutional neural network
- optical coherence tomography
- artificial intelligence
- positron emission tomography
- squamous cell carcinoma
- flow cytometry
- lymph node metastasis