Predicting hepatic perfusion and clearance in hepatocellular carcinoma patients using Gd-EOB-DTPA-enhanced MRI
Jinghui Feng, Xukun Zhang, Jinpeng Tan, Minghao Han, Dongxue Qi, Xiaoying Wang, Lihua Zhang
Robotics Research (United States) Changchun University Fudan University Zhongshan Hospital
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摘要与影响
To assess the associations of Gd-EOB-DTPA-enhanced MRI features with hepatic perfusion and clearance in hepatocellular carcinoma (HCC) patients. A total of 79 patients diagnosed with HCC, waiting for transcatheter arterial chemoembolization (TACE), were retrospectively enrolled in this study. They all received Gd-EOB-DTPA-enhanced MRI, ICG-R15, and other necessary tests. Liver images were obtained at 20 min after Gd-EOB-DTPA enhancement and radiomic features were extracted from these images using gray-level matrix. Relative liver enhancement (RLE), liver-to-spleen ratio (LSR), liver-to-muscle ratio (LMR) and reduction rate of T1 relaxation time of the liver (rrT1) were quantified and were estimated in left lobe and right lobe separately. Correlation analysis suggested that there were significant correlations between ICG-related traits and MRI features except the LSR of left lobe. Intriguingly, the LMR of left lobe displayed the largest correlation coefficient with ICG-K (R = 0.49, 95 % CI [0.30, 0.64]) while the rrT1rt displayed the largest coefficient with other ICG-related traits. The univariable and multivariable analyses implicated that rrT1rt should be the independent predictor of liver function compared with other parameters. Gd-EOB-DTPA enhancement MRI can well reflect the liver function and the rrT1rt parameter displays the independent correlation and the best predictive performance.
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学术脉络
学科主题
生物医学Hepatocellular Carcinoma Treatment and Prognosis
MRI in cancer diagnosis · Radiomics and Machine Learning in Medical Imaging
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