Proof of principle: Estimation of liver function using color coded Doppler sonography of the portal vein

ACR Appropriateness Criteria® Abnormal Liver Function Tests

Liver function tests are commonly obtained in symptomatic and asymptomatic patients. Various overlapping lab patterns can be seen due to derangement of hepatocytes and bile ducts function. Imaging tests are pursued to identify underlying etiology and guide management based on the lab results. Liver function tests may reveal mild, moderate, or severe hepatocellular predominance and can be seen in alcoholic and nonalcoholic liver disease, acute hepatitis, and acute liver injury due to other causes. Cholestatic pattern with elevated alkaline phosphatase with or without elevated γ-glutamyl transpeptidase can be seen with various causes of obstructive biliopathy. Acute or subacute cholestasis with conjugated or unconjugated hyperbilirubinemia can be seen due to prehepatic, intrahepatic, or posthepatic causes. We discuss the initial and complementary imaging modalities to be used in clinical scenarios presenting with abnormal liver function tests. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Application of A U-Net for Map-like Segmentation and Classification of Discontinuous Fibrosis Distribution in Gd-EOB-DTPA-Enhanced Liver MRI

Highlights

Abstract

We aimed to evaluate whether U-shaped convolutional neuronal networks can be used to segment liver parenchyma and indicate the degree of liver fibrosis/cirrhosis at the voxel level using contrast-enhanced magnetic resonance imaging. This retrospective study included 112 examinations with histologically determined liver fibrosis/cirrhosis grade (Ishak score) as the ground truth. The T1-weighted volume-interpolated breath-hold examination sequences of native, arterial, late arterial, portal venous, and hepatobiliary phases were semi-automatically segmented and co-registered. The segmentations were assigned the corresponding Ishak score. In a nested cross-validation procedure, five models of a convolutional neural network with U-Net architecture (nnU-Net) were trained, with the dataset being divided into stratified training/validation (n = 89/90) and holdout test datasets (n = 23/22). The trained models precisely segmented the test data (mean dice similarity coefficient = 0.938) and assigned separate fibrosis scores to each voxel, allowing localization-dependent determination of the degree of fibrosis. The per voxel results were evaluated by the histologically determined fibrosis score. The micro-average area under the receiver operating characteristic curve of this seven-class classification problem (Ishak score 0 to 6) was 0.752 for the test data. The top-three-accuracy-score was 0.750. We conclude that determining fibrosis grade or cirrhosis based on multiphase Gd-EOB-DTPA-enhanced liver MRI seems feasible using a 2D U-Net. Prospective studies with localized biopsies are needed to evaluate the reliability of this model in a clinical setting.