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Hepatocellular carcinoma (HCC) is the sixth most common cancer and the second leading cause of cancer mortality worldwide. Incidence rates of liver cancer vary widely between geographic regions and are highest in Eastern Asia and sub-Saharan Africa. In the United States, the incidence of HCC has increased since the 1980s. HCC detection at an early stage through surveillance and curative therapy has considerably improved the 5-year survival. Therefore, medical societies advocate systematic screening and surveillance of target populations at particularly high risk for developing HCC to facilitate early-stage detection. Risk factors for HCC include cirrhosis, chronic infection with hepatitis B virus (HBV), hepatitis C virus (HCV), excess alcohol consumption, non-alcoholic fatty liver disease, family history of HCC, obesity, type 2 diabetes mellitus, and smoking. Medical societies utilize risk estimates to define target patient populations in which imaging surveillance is recommended (risk above threshold) or in which the benefits of surveillance are uncertain (risk unknown or below threshold). All medical societies currently recommend screening and surveillance in patients with cirrhosis and subsets of patients with chronic HBV; some societies also include patients with stage 3 fibrosis due to HCV as well as additional groups. Thus, target population definitions vary between regions, reflecting cultural, demographic, economic, healthcare priority, and biological differences. The Liver Imaging Reporting and Data System (LI-RADS) defines different patient populations for surveillance and for diagnosis and staging. We also discuss general trends pertaining to geographic region, age, gender, ethnicity, impact of surveillance on survival, mortality, and future trends.

ObjectivesThe 8th International Forum for Liver Magnetic Resonance Imaging (MRI), held in Basel, Switzerland, in October 2017, brought together clinical and academic radiologists from around the world to discuss developments in and reach consensus on key issues in the field of gadoxetic acid–enhanced liver MRI since the previous Forum held in 2013.MethodsTwo main themes in liver MRI were considered in detail at the Forum: the use of gadoxetic acid for contrast-enhanced MRI in patients with liver cirrhosis and the technical performance of gadoxetic acid–enhanced liver MRI, both opportunities and challenges. This article summarises the expert presentations and the delegate voting on consensus statements discussed at the Forum.Results and conclusionsIt was concluded that gadoxetic acid–enhanced MRI has higher sensitivity for the diagnosis of hepatocellular carcinoma (HCC), when compared with multidetector CT, by utilising features of hyperenhancement in the arterial phase and hypointensity in the hepatobiliary phase (HBP). Recent HCC management guidelines recognise an increasing role for gadoxetic acid–enhanced MRI in early diagnosis and monitoring post-resection. Additional research is needed to define the role of HBP in predicting microvascular invasion, to better define washout during the transitional phase in gadoxetic acid–enhanced MRI for HCC diagnosis, and to reduce the artefacts encountered in the arterial phase. Technical developments are being directed to shortening the MRI protocol for reducing time and patient discomfort and toward utilising faster imaging and non-Cartesian free-breathing approaches that have the potential to improve multiphasic dynamic imaging.Key Points• Gadoxetic acid–enhanced MRI provides higher diagnostic sensitivity than CT for diagnosing HCC.• Gadoxetic acid–enhanced MRI has roles in early-HCC diagnosis and monitoring post-resection response.• Faster imaging and free-breathing approaches have potential to improve multiphasic dynamic imaging.

ObjectiveEmerging data suggest that a 30% relative decline in liver fat, as assessed by MRI-proton density fat fraction (MRI-PDFF), may be associated with Non-Alcoholic Fatty Liver Disease Activity Score improvement, but the association between decline in MRI-PDFF and fibrosis regression is not known. Therefore, we aimed to examine the association between ≥30% relative decline in MRI-PDFF and fibrosis regression in non-alcoholic fatty liver disease (NAFLD).DesignThis prospective study included 100 well-characterised patients with biopsy-proven NAFLD with paired contemporaneous MRI-PDFF assessment at two time points. MRI-PDFF response was defined as ≥30% relative decline in MRI-PDFF. The primary outcome was ≥1 stage histological fibrosis regression.ResultsThe median (IQR) age was 54 (43–62) years and body mass index was 31.9 (29–36) kg/m2. In multivariable-adjusted logistic regression analysis (adjusted for age, gender, diabetes status, race/ethnicity, interval between biopsies, gamma-glutamyl transferase, liver stiffness by magnetic resonance elastography and change in platelet counts), MRI-PDFF response was an independent predictor of fibrosis regression with an adjusted OR of 6.46 (95% CI 1.1 to 37.0, p=0.04). The proportion of patients with MRI-PDFF response with fibrosis regression, no change in fibrosis and fibrosis progression was 40.0%, 24.6% and 13.0%, respectively, and the proportion of patients with MRI-PDFF response increased with fibrosis regression (p=0.03).Conclusion≥30% reduction in MRI-PDFF in early phase trials can provide a useful estimate of odds of ≥1 stage improvement in fibrosis. These data may be helpful in sample size estimation in non-alcoholic steatohepatitis trials.

The presence of cirrhosis in nonalcoholic-fatty-liver-disease (NAFLD) is the most important predictor of liver-related mortality. Limited data exist concerning the diagnostic accuracy of gut-microbiome-derived signatures for detecting NAFLD-cirrhosis. Here we report 16S gut-microbiome compositions of 203 uniquely well-characterized participants from a prospective twin and family cohort, including 98 probands encompassing the entire spectrum of NAFLD and 105 of their first-degree relatives, assessed by advanced magnetic-resonance-imaging. We show strong familial correlation of gut-microbiome profiles, driven by shared housing. We report a panel of 30 features, including 27 bacterial features with discriminatory ability to detect NAFLD-cirrhosis using a Random Forest classifier model. In a derivation cohort of probands, the model has a robust diagnostic accuracy (AUROC of 0.92) for detecting NAFLD-cirrhosis, confirmed in a validation cohort of relatives of proband with NAFLD-cirrhosis (AUROC of 0.87). This study provides evidence for a fecal-microbiome-derived signature to detect NAFLD-cirrhosis.

The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system that uses standardized terminology, technique, interpretation, and reporting of imaging studies for hepatocellular carcinoma surveillance, diagnosis, and locoregional treatment response assessment. Since its initial release in 2011, LI-RADS has evolved and expanded in scope. In this article, we discuss recent updates intended to address clinical needs and mitigate current challenges.

Purpose To compare the per-lesion sensitivity and positive predictive value (PPV) of ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) for the diagnosis of hepatocellular carcinoma (HCC). Materials and methods The meta-analysis of sensitivity included 242 studies (15,713 patients); 116 studies (7492 patients) allowed calculation of PPV. Pooled per-lesion sensitivity and PPV for HCC detection were compared using empirical Bayes estimates of a beta-binomial model. Results The pooled per-lesion sensitivity and PPV of contrast-enhanced CT (73.6%, 85.8%) and gadolinium-enhanced MRI (77.5%, 83.6%) are not significantly different ( P  = 0.08, P  = 0.2). However, if the hepatobiliary agent gadoxetate is used, MRI has significantly higher pooled per-lesion sensitivity and PPV (85.6%, 94.2%) than CT ( P  < 0.0001) or than MRI with other agents ( P  < 0.0001). Non-contrast-enhanced US has the lowest overall sensitivity and PPV (59.3%, 77.4%). Pooled per-lesion sensitivity and PPV of contrast-enhanced US (84.4%, 89.3%) are relatively high, but no contrast-enhanced US study used the most rigorous reference standards. Conclusion MRI utilizing the hepatobiliary agent gadoxetate has the highest overall sensitivity and PPV, and may be the single optimal method for diagnosis of HCC. Non-contrast-enhanced US has the lowest sensitivity and PPV. More rigorous reference standards are needed to compare the performance of contrast-enhanced US with CT and MRI. Differences in sensitivity and PPV between CT and conventional gadolinium-enhanced MRI are not statistically significant overall.

PurposeTo evaluate whether a three-phase dynamic contrast-enhanced CT protocol, when combined with a deep learning model, has similar accuracy in differentiating hepatocellular carcinoma (HCC) from other focal liver lesions (FLLs) compared with a four-phase protocol.MethodsThree hundred and forty-two patients (mean age 49.1 ± 10.5 years, range 19–86 years, 65.8% male) scanned with a four-phase CT protocol (precontrast, arterial, portal-venous and delayed phases) were retrospectively enrolled. A total of 449 FLLs were categorized into HCC and non-HCC groups based on the best available reference standard. Three convolutional dense networks (CDNs) with the input of four-phase CT images (model A), three-phase images without portal-venous phase (model B) and three-phase images without precontrast phase (model C) were trained on 80% of lesions and evaluated in the other 20% by receiver operating characteristics (ROC) and confusion matrix analysis. The DeLong test was performed to compare the areas under the ROC curves (AUCs) of A with B, B with C, and A with C.ResultsThe diagnostic accuracy in differentiating HCC from other FLLs on test sets was 83.3% for model A, 81.1% for model B and 85.6% for model C, and the AUCs were 0.925, 0.862 and 0.920, respectively. The AUCs of models A and C did not differ significantly (p = 0.765), but the AUCs of models A and B (p = 0.038) and of models B and C (p = 0.028) did.ConclusionsWhen combined with a CDN, a three-phase CT protocol without precontrast showed similar diagnostic accuracy as a four-phase protocol in differentiating HCC from other FLLs, suggesting that the multiphase CT protocol for HCC diagnosis might be optimized by removing the precontrast phase to reduce radiation dose.

Medical imaging plays an important role in the diagnosis and management of hepatocellular carcinoma (HCC). The Liver Imaging Reporting and Data System (LI-RADS) was initially created to standardize the reporting and data collection of CT and MR imaging for patients at risk for HCC. As contrast-enhanced ultrasound (CEUS) has been widely used in clinical practice, it has recently been added to the LI-RADS. While CEUS LI-RADS shares fundamental concepts with CT/MRI LI-RADS, there are key differences between the modalities reflecting dissimilarities in the underlying methods of image acquisition and types of contrast material. This review introduces a recent update of CEUS LI-RADS and explains the key differences from CT/MRI LI-RADS.

PurposeTo assess inter-observer agreement and accuracy of LI-RADS v2018 for differentiating tumor in vein (TIV) from bland thrombus on gadoxetic acid-enhanced magnetic resonance imaging (Gx-MRI). Secondarily, to determine whether a multi-feature model improves accuracy compared to LI-RADS.MethodsWe retrospectively identified consecutive patients at risk for hepatocellular carcinoma with venous occlusion(s) reported on Gx-MRI. Five radiologists independently classified each occlusion as TIV or bland thrombus using the LI-RADS TIV criterion (enhancing soft tissue in vein). They also evaluated imaging features suggestive of TIV or bland thrombus. Intra-class correlation coefficient (ICC) was calculated for individual features. A multi-feature model was developed based on consensus scores of features with > 5% consensus prevalence and > 0.40 ICC. Sensitivity and specificity of the LI-RADS criterion and of the cross-validated multi-feature model were compared.ResultsNinety-eight patients with 103 venous occlusions (58 TIV, 45 bland thrombus) were included. The LI-RADS criterion provided 0.63 ICC and, depending on the reader, 0.62–0.93 sensitivity and 0.87–1.00 specificity. Five other features had > 5% consensus prevalence and > 0.40 ICC, including three LI-RADS suggestive features and two non-LI-RADS features. The optimal multi-feature model incorporated the LI-RADS criterion and one LI-RADS suggestive feature (occluded or obscured vein contiguous with malignant parenchymal mass). After cross-validation, the multi-feature model did not improve sensitivity or specificity compared to the LI-RADS criterion (P = 0.23 and 0.25, respectively).ConclusionUsing Gx-MRI, the LI-RADS criterion for TIV provides substantial inter-observer agreement, variable sensitivity, and high specificity for differentiating TIV from bland thrombus. A cross-validated multi-feature model did not improve diagnostic performance.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as nonalcoholic fatty liver disease, is the fastest-growing cause of chronic liver disease worldwide, affecting approximately 30% of the global population. Imaging is vital for detecting, quantifying, and monitoring hepatic steatosis-the defining abnormality of MASLD-and subsequent fibrosis-the key determinant of liver-related outcomes. This review summarizes the principles, clinical usage, efficacy, and advancements in various imaging modalities for the noninvasive assessment of hepatic steatosis and fibrosis, with an emphasis on ultrasound, CT, and MRI. Additionally, this review explores the evolving landscape of MASLD diagnostic approaches, including machine-learning techniques, opportunistic screening, standardized imaging guidelines, and therapies, emphasizing the pivotal role that radiologists can play in shaping these developments.