A machine-learning-based combination of criteria to detect bladder cancer lymph node metastasis on [ 18 F]FDG PET/CT: a pathology-controlled study.

Antoine GirardLaurent DercleHelena Vila-ReyesLawrence H SchwartzAstrid GirmaMarc BertauxCamelia RadulescuThierry LebretOlivier DelcroixMathieu Rouanne

Published in: European radiology (2022)

F]FDG PET/CT in patients with muscle-invasive bladder cancer. • The top 3 features to predict LN involvement were the SUVmax of the most intense LN, the product of diameters of the largest LN, and the product of diameters of the primary bladder tumor.

Keyphrases

lymph node metastasis
muscle invasive bladder cancer
machine learning
squamous cell carcinoma
papillary thyroid
spinal cord injury
artificial intelligence
deep learning