MRI examinations with liver-specific contrast agents such as Gd-EOB-DTPA (gadoxetic acid) allow not only the characterization of liver lesions but also the determination of regional liver function. One promising method for assessing liver function is the use of imaging modalities such as MRI. Therefore, its score is often used as a point of reference for the development of new methods to determine liver function. The MELD was originally developed as a model to predict survival after transjugular intrahepatic portosystemic shunt (TIPS) and has been expanded for use in the prediction of 3-month mortality in patients with end-stage chronic liver disease awaiting liver transplantation. In clinical practice, blood values are used as a static test to assess liver function and are therefore an integral part of scoring systems such as the model for end-stage liver disease (MELD). In addition, the evaluation of liver function prior to liver resection is particularly important for avoiding posthepatectomy liver failure (PHLF). Therefore, a regular assessment of liver function is required for patients with CLD. The determination of liver function (LF) is becoming increasingly important given the rise in chronic liver disease (CLD) and the accompanying increase in the number of patients with liver cirrhosis and hepatocellular carcinoma (HCC). This study demonstrated that the fully automated determination of total liver function, regionally resolved, using MR liver imaging is feasible, providing the opportunity to use the MELIF score as a diagnostic marker in future prospective studies. However, MELIF showed a stronger correlation than the rrT1 liver score. Both scores correlated strongly with the MELD score, which is used as a reference for global liver function. A novel artificial-intelligence-based software prototype performed image segmentation and registration, calculated the reduction rate of the T1 relaxation time for the whole liver (rrT1 liver) and used it to calculate a personalized liver function score, then generated a unified score-the MELIF score-by combining the liver function score with a patient-specific factor that included weight, height and liver volume. T1 images from the native and hepatobiliary phases and the corresponding T1 maps from 195 patients were analyzed. The objective of this study was to demonstrate and evaluate the diagnostic performance of two fully automatically generated imaging-based liver function scores that take the whole liver into account. Gd-EOB-DTPA-enhanced MRI allows for both the acquisition of anatomical information and regional liver function quantification. In the management of patients with chronic liver disease, the assessment of liver function is essential for treatment planning.
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