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Preoperative prediction of tumour deposits in rectal cancer by an artificial neural network-based US radiomics model.

Li-Da ChenWei LiMeng-Fei XianXin ZhengYuan LinBao-Xian LiuMan-Xia LinXin LiYan-Ling ZhengXiao-Yan XieMing-De LuMing KuangJian-Bo XuWei Wang
Published in: European radiology (2019)
• We prospectively developed an artificial neural network model for predicting tumour deposits based on US radiomics that had an accuracy of 75.0%. • The area under the curve of the US radiomics model was improved than that of the MRI radiomics model (0.916 vs. 0.872), but the difference was not significant (p = 0.384). • The US radiomics-based model may potentially predict TDs accurately before therapy, but this model needs further validation with larger samples.
Keyphrases
  • neural network
  • contrast enhanced
  • lymph node metastasis
  • rectal cancer
  • magnetic resonance imaging
  • stem cells
  • squamous cell carcinoma
  • computed tomography
  • patients undergoing
  • locally advanced