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
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.
Demonstration of radiomics
analysis on Gadoxetic acid-enhanced hepatobiliary phase (HBP) axial MR image at
hepatic portal level in a 54-year-old man with hepatitis B–related liver cirrhosis.
Train and test ROCs for liver function.