Can machine learning radiomics provide pre-operative differentiation of combined hepatocellular cholangiocarcinoma from hepatocellular carcinoma and cholangiocarcinoma to inform optimal treatment planning?

Objective To differentiate combined hepatocellular cholangiocarcinoma (cHCC-CC) from cholangiocarcinoma (CC) and hepatocellular carcinoma (HCC) using machine learning on MRI and CT radiomics features. Methods This retrospective study included 85 patients aged 32 to 86 years with 86 histopathology-pr...

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Veröffentlicht in:	European radiology 2021-01, Vol.31 (1), p.244-255
Hauptverfasser:	Liu, Xiaoyang, Khalvati, Farzad, Namdar, Khashayar, Fischer, Sandra, Lewis, Sara, Taouli, Bachir, Haider, Masoom A., Jhaveri, Kartik S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adult Aged Aged, 80 and over Bile Duct Neoplasms - diagnostic imaging Bile Ducts, Intrahepatic Cancer Carcinoma, Hepatocellular - diagnostic imaging Cholangiocarcinoma Cholangiocarcinoma - diagnostic imaging Decisions Diagnostic Radiology Differentiation Feature extraction Hepatobiliary-Pancreas Hepatocellular carcinoma Histopathology Humans Imaging Internal Medicine Interventional Radiology Learning algorithms Liver Liver cancer Liver Neoplasms - diagnostic imaging Machine Learning Magnetic resonance imaging Medicine Medicine & Public Health Middle Aged Neuroradiology Performance prediction Principal components analysis Radiology Radiomics Retrospective Studies Segmentation Support vector machines Transplantation Tumors Ultrasound
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