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Abstract #2486

Radiomics Analysis on Gd-EOB-DTPA-Enhanced MRI for Prediction of Liver Function and Hepatic Cirrhosis

Xie Yuanliang1, Wang Xiang1, Li Hui1, Liu Xiaoyu1, and Sun Jianqing2
1Radiology, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 2Clinical Science,Philips Healthcare, Shanghai, China

This retrospective study explored the value of a radiomics-based model on Gd-EOB-DTPA-Enhanced MRI for predicting liver function and cirrhosis in clinic. Multi-class radiomics feature extraction was performed on 2D-view whole liver at portal level on HBP MRI obtained 20 min after Gd-EOB-DTPA-enhanced MRI. A prediction model including 15 radiomics features using a machine learning logistic regression classifier showed the mean AUCs on train dataset and test dataset were 0.91 and 0.87 for diagnosing Child-Pugh A respectively; 0.93 and 0.93 for diagnosing liver cirrhosis, respectively. Radiomics analysis of gadoxetic acid-enhanced HBP images allows for accurate diagnosis of clinically significant liver function reservation and liver cirrhosis and may be a promising noninvasive method for assessment of liver cirrhosis.

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