We aimed to develop and validate a prediction model to identify HCC in focal liver lesions (FLLs) ≤20 mm among patients at risk for HCC based on clinical and contrast-enhanced ultrasound (CEUS) features.

Between January 2022 and July 2023, 386 patients (mean age 58 ± 11 years; 277 male) at risk for HCC with FLLs ≤20 mm and clinical and preoperative CEUS data from three centers were retrospectively enrolled. Three prediction models based on clinical data (Cli-M), CEUS features (CEUS-M), and combined clinical and CEUS features (Com-M) were constructed using the training cohort (187 patients). Their predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) in the internal and external validation cohorts. All patients were reclassified using the American College of Radiology CEUS Liver Imaging Reporting and Data System (CEUS LI-RADS) and combined with the best-performing model (modified LI-RADS).

The AUCs of Com-M were 0.873-0.951 in the training, internal, and external validation cohorts, which were higher than those of Cli-M (0.749-0.795, all P < 0.05) and CEUS-M (0.848-0.899, all P < 0.05). The sensitivity of LR-5 of modified LI-RADS was significantly improved from 83.1 % to 88.9 % (p＜0.001) in the training, internal and external validation cohort while there was no statistical different on its specificity (82.6 %-94.7 % vs 95.7 %-97.6 %., p = 0.162-0.650).

The model based on clinical and CEUS features can help identify HCC in FLLs ≤ 20 mm in high-risk patients.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide and is the fastest growing cause of cancer death in the United States (U.S.) In the U.S., current national clinical practice guidelines from the 2023 American Association for the Study of Liver Diseases (AASLD) Practice Guidance and the recently updated Liver Imaging Reporting & Data Systems (LI-RADS) Ultrasound (US) Surveillance v2024 core recommend semi-annual serum α-fetoprotein and US screening of patients deemed to be high risk for developing HCC. In this article, we will explore the transition to a patient-centered approach to HCC surveillance, including the role of the new LI-RADS US Surveillance v2024 core and the use of visualization score for determining ultrasound quality, the known risk factors for poor US image quality, and the potential options for alternative surveillance strategies when US may not be a viable option for certain patients, including multiphasic computed tomography (CT), magnetic resonance imaging (MRI), and several abbreviated MRI protocols.

Purpose. To investigate the diagnostic performance of ultrasound (US)-based shear wave speed (SWS), shear wave attenuation (SWA), and combination of them as shear wave viscoelastography (SWVE) methods in patients undergoing US to characterize focal liver nodules.Materials and methods. In this prospective cross-sectional study, 70 patients with 72 nodules were enrolled. Investigational US and clinical magnetic resonance imaging (MRI) examinations were performed in all participants. The composite reference standard included MRI or histopathology to differentiate benign and malignant nodules. A linear discriminant analysis (LDA) was used to assess the combination of SWVE methods. Analyzes included Mann-WhitneyUtest, receiver operating characteristic analysis, and computation of sensitivity and specificity at the point that maximized the Youden index.Results. Mean SWS was significantly higher in malignant than benign nodules (2.49 ± 0.76 m s-1vs. 1.72 ± 0.70,p< 0.001), whereas SWA was lower (0.56 ± 0.30 vs. 1.10 ± 0.43 Np/m/Hz,p< 0.001). To differentiate between malignant and benign nodules, SWS with a threshold of 2.43 m s-1achieved a sensitivity of 0.54 (95% confidence interval (CI): 0.38-0.69) and a specificity of 0.88 (CI: 0.74-0.95). SWA with a threshold of 0.81 Np/m/Hz yielded a sensitivity of 0.81 (CI: 0.66-0.90) and a specificity of 0.74 (CI: 0.58-0.86). Combining these SWVE methods using a LDA resulted in a sensitivity of 0.81 (CI: 0.66-0.91) and a specificity of 0.86 (CI: 0.71-0.94).Conclusion. Malignant nodules had higher SWS and lower SWA than benign ones. The combination of SWS and SWA in a LDA classification algorithm increased the diagnostic performance.

Hepatocellular carcinoma (HCC) is the most common primary carcinoma arising from the liver. Although HCC can arise de novo, the vast majority of cases develop in the setting of chronic liver disease. Hepatocarcinogenesis follows a well-studied process during which chronic inflammation and cellular damage precipitate cellular and genetic aberrations, with subsequent propagation of precancerous and cancerous lesions. Surveillance of individuals at high risk of HCC, early diagnosis, and individualized treatment are keys to reducing the mortality associated with this disease. Radiological imaging plays a critical role in the diagnosis and management of these patients. HCC is a unique cancer in that it can be diagnosed with confidence by imaging that meets all radiologic criteria, obviating the risks associated with tissue sampling. This article discusses conventional and emerging imaging techniques for the evaluation of HCC.

The increasing incidence of hepatocellular carcinoma (HCC), together with the poor effectiveness of the available treatments, make early diagnosis and effective screening of utmost relevance. Liquid biopsy represents a potential novel approach to early HCC detection and monitoring. The identification of blood markers has many desirable features, including the absence of any significant risk for the patients, the possibility of being used as a screening tool, and the ability to perform multiple tests, thus allowing for the real-time monitoring of HCC evolution. Unfortunately, the available blood markers for HCC have several limitations, mostly related to specificity and sensitivity. In this context, employing non-coding RNAs (ncRNAs) may represent an interesting and novel diagnostic approach. ncRNAs, which include, among others, micro interfering RNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), regulate human gene expression via interactions with their target mRNA. Notably, their expression can be altered in HCC, thus reflecting disease status. In this review, we discuss some notable works that describe the use of miRNAs, lncRNAs, and circRNAs as HCC biomarkers. Despite some open aspects related to ncRNA use, the presented works strongly support the potential effectiveness of these molecules as diagnostic/prognostic markers for HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. Early detection of HCC is a key factor in enabling curative therapies and improving overall survival. Worldwide, several guidelines are available for surveillance of at-risk populations and diagnosis of HCC. This article provides a current comprehensive update on screening and diagnosis of HCC.

To perform an intra-individual comparison of LI-RADS category and imaging features in patients at high risk of hepatocellular carcinoma (HCC) on contrast-enhanced CT, gadoxetate disodium-enhanced MRI (EOB-MRI), and extracellular agent-enhanced MRI (ECA-MRI) and to analyze the diagnostic performance of each imaging modality.

This retrospective study included cirrhotic patients with at least one LR-3, LR-4, LR-5, LR-M or LR-TIV observation imaged with at least two imaging modalities among CT, EOB-MRI, or ECA-MRI. Two radiologists evaluated the observations using the LI-RADS v2018 diagnostic algorithm. Reference standard included pathologic confirmation and imaging criteria according to LI-RADS v2018. Imaging features were compared between different exams using the McNemar test. Inter-modality agreement was calculated by using the weighted Cohen's kappa (k) test.

A total of 144 observations (mean size 34.0 ± 32.4 mm) in 96 patients were included. There were no significant differences in the detection of major and ancillary imaging features between the three imaging modalities. When considering all the observations, inter-modality agreement for category assignment was substantial between CT and EOB-MRI (k 0.60; 95%CI 0.44, 0.75), moderate between CT and ECA-MRI (k 0.46; 95%CI 0.22, 0.69) and substantial between EOB-MRI and ECA-MRI (k 0.72; 95%CI 0.59, 0.85). In observations smaller than 20 mm, inter-modality agreement was fair between CT and EOB-MRI (k 0.26; 95%CI 0.05, 0.47), moderate between CT and ECA-MRI (k 0.42; 95%CI -0.02, 0.88), and substantial between EOB-MRI and ECA-MRI (k 0.65; 95%CI 0.47, 0.82). ECA-MRI demonstrated the highest sensitivity (70%) and specificity (100%) when considering LR-5 as predictor of HCC.

Inter-modality agreement between CT, ECA-MRI, and EOB-MRI decreases in observations smaller than 20 mm. ECA-MRI has the provided higher sensitivity for the diagnosis of HCC.

Primary liver cancer is among the most common cancers globally. It is the sixth-most common malignancy encountered and the third-most common cause of cancer-related death. Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, accounting for about 90% of primary liver cancers. The majority of HCCs occur in patients with underlying cirrhosis, which results from chronic liver diseases such as fatty liver, hepatitis B and hepatitis C infections, and chronic alcohol use, which are the leading causes. The obesity pandemic has led to an increased prevalence of nonalcoholic fatty liver disease (NAFLD), which leads to nonalcoholic steatohepatitis and could progress to cirrhosis. As HCC is among the most common cancers and occurs in the setting of chronic liver disease in most patients, screening the population at risk could help in early diagnosis and management, leading to improved survival. Screening for HCC is performed using biochemical marker testing such as α-fetoprotein (AFP) and cross-sectional imaging. It is critical to emphasize that HCC could potentially occur in patients without cirrhosis (non-cirrhotic HCC), which can account for almost 20% of all HCCs. The lack of cirrhosis can cause a delay in surveillance, which could potentially lead to diagnosis at a later stage, worsening the prognosis for such patients. In this article, we discuss the diagnosis of cirrhosis in at-risk populations with details on the different modalities available for screening HCC in patients with cirrhosis, emphasizing the role of abdominal ultrasounds, the primary imaging modality in HCC screening.

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related mortality in Taiwan. The Taiwan Liver Cancer Association and the Gastroenterological Society of Taiwan established HCC management consensus guidelines in 2016 and updated them in 2023. Current recommendations focus on addressing critical issues in HCC management, including surveillance, diagnosis, systemic treatment, and posttreatment monitoring. For surveillance and diagnosis, we updated the guidelines to include the role of protein induced by vitamin K absence or antagonist II (PIVKA-II) and gadoxetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) in detecting HCCs. For systemic treatment, the updated guidelines summarize the multiple choices available for targeted therapy, immune checkpoint inhibitors, and a combination of both, especially for those carcinomas refractory to or unsuitable for transarterial chemoembolization. We have added a new section, posttreatment monitoring, that describes the important roles of PIVKA-II and EOB-MRI after HCC therapy, including surgery, locoregional therapy, and systemic treatment. Through this update of the management consensus guidelines, patients with HCC may benefit from optimal diagnosis, therapeutic modalities, and posttreatment monitoring.

Hepatocellular carcinoma (HCC) is the third most fatal and fifth most common cancer worldwide, with rising incidence due to obesity and nonalcoholic fatty liver disease. Imaging modalities, including ultrasound (US), multidetector computed tomography (MDCT), and magnetic resonance imaging (MRI) play a vital role in detecting HCC characteristics, aiding in early detection, detailed visualization, and accurate differentiation of liver lesions. Liver-specific contrast agents, the Liver Imaging Reporting and Data System, and advanced techniques, including diffusion-weighted imaging and artificial intelligence, further enhance diagnostic accuracy. This review emphasizes the significant role of imaging in managing HCC, from diagnosis to treatment assessment, without the need for invasive biopsies.

Hepatocellular carcinoma (HCC) constitutes the majority of liver cancers and significantly impacts global cancer mortality. While ultrasound (US) with or without alpha-fetoprotein is the mainstay for HCC surveillance, its limitations highlight the necessity for more effective surveillance tools. Therefore, this review explores evolving imaging modalities and abbreviated magnetic resonance imaging (MRI) (AMRI) protocols as promising alternatives, addressing challenges in HCC surveillance.

This comprehensive review delves into the evaluation and challenges of HCC surveillance tools, focusing on non-contrast abbreviated MRI (NC-AMRI) and contrast-enhanced abbreviated MRI protocols. It covers the implementation of AMRI for HCC surveillance, patient preferences, adherence, and strategies for optimizing cost-effectiveness. Additionally, the article provides insights into prospects for HCC surveillance by summarizing meta-analyses, prospective studies, and ongoing clinical trials evaluating AMRI protocols.

The opinions underscore the transformative impact of AMRI on HCC surveillance, especially in overcoming US limitations. Promising results from NC-AMRI protocols indicate its potential for high-risk patient surveillance, though prospective studies in true surveillance settings are essential for validation. Future research should prioritize risk-stratified AMRI protocols and address cost-effectiveness for broader clinical implementation, alongside comparative analyses with US for optimal surveillance strategies.

Hepatocellular Carcinoma (HCC), the most common primary liver cancer, is a significant contributor to worldwide cancer-related deaths. Various medical imaging techniques, including computed tomography, magnetic resonance imaging, and ultrasound, play a crucial role in accurately evaluating HCC and formulating effective treatment plans. Artificial Intelligence (AI) technologies have demonstrated potential in supporting physicians by providing more accurate and consistent medical diagnoses. Recent advancements have led to the development of AI-based multi-modal prediction systems. These systems integrate medical imaging with other modalities, such as electronic health record reports and clinical parameters, to enhance the accuracy of predicting biological characteristics and prognosis, including those associated with HCC. These multi-modal prediction systems pave the way for predicting the response to transarterial chemoembolization and microvascular invasion treatments and can assist clinicians in identifying the optimal patients with HCC who could benefit from interventional therapy. This paper provides an overview of the latest AI-based medical imaging models developed for diagnosing and predicting HCC. It also explores the challenges and potential future directions related to the clinical application of AI techniques.

Ultrasound (US) is recommended for HCC surveillance in high-risk patients but has limited performance in detecting early-stage HCC. We aimed to compare the diagnostic performance of biannual US and annual non-contrast abbreviated magnetic resonance imaging (NC-AMRI) as HCC surveillance modalities in high-risk patients.

This prospective, multicenter cohort study enrolled participants with an estimated annual risk of HCC greater than 5% between October 2015 and April 2017. Participants underwent six rounds of HCC surveillance at 6-month intervals, with both US and NC-AMRI at rounds 1, 3, and 5, and only US at rounds 2, 4, and 6. The sensitivity, diagnostic yield (DY), and false referral rate (FRR) for HCC detection by US and NC-AMRI were compared.

In total, 208 participants underwent 980 US and 516 NC-AMRI examinations during 30 months of follow-up. Among them, 34 HCCs were diagnosed in 31 participants, with 20 (64.5%) classified as very early-stage and 11 (35.5%) as early-stage HCC. The sensitivity of annual NC-AMRI (71.0%, 22/31) was marginally higher than that of biannual US (45.2%, 14/31; p = 0.077). NC-AMRI showed a significantly higher DY than US (4.26% vs. 1.43%, p <0.001), with a similar FRR (2.91% vs. 3.06%, p = 0.885). A simulation of alternating US and NC-AMRI at 6-month intervals yielded a sensitivity of 83.9% (26/31), significantly exceeding that of biannual US (p = 0.006).

Annual NC-AMRI showed a marginally higher sensitivity than biannual US for HCC detection in high-risk patients. The DY of annual NC-AMRI was significantly higher than that of biannual US, without increasing the FRR. Thus, alternating US and NC-AMRI at 6-month intervals could be an optimal surveillance strategy for high-risk patients.

Current guidelines permit the use of magnetic resonance imaging (MRI) as a surveillance tool for hepatocellular carcinoma in patients in whom ultrasonography (US) is inadequate. However, the specific indications, imaging sequences, and intervals for MRI surveillance remain unclear. In our study, we found that annual non-contrast abbreviated MRI exhibited marginally higher sensitivity and significantly better diagnostic yield than biannual US in patients at high risk of hepatocellular carcinoma. Alternating US and non-contrast abbreviated MRI at 6-month intervals led to significantly improved sensitivity compared to biannual US, making it a potentially optimal surveillance strategy for high-risk patients.

NCT02551250.

So far, there have been published several meta-analyses which focused on hepatocellular carcinoma (HCC) detection with hepatobiliary phase (HBP) contrast agents. However, only a few of them aimed at establishing whether there is any added value of the HBP itself for HCC diagnosis. To answer the question, we performed a systematic literature search with the time limit going back to 2010.

True positive, false positive, false negative, and true negative values with and without the HBP were extracted from the included studies. Pooled sensitivities and specificities with and without the HBP were calculated and summary receiver operating characteristics curves were drawn to assess the diagnostic performance of the studies with and without the HBP.

A total of 13 studies were included involving 1184 HCC lesions. In 13 studies without the HBP, the pooled sensitivity, specificity, and area under the curve (AUC) were 0.83, 0.89 and 0.94 respectively. In 13 studies with the HBP, the pooled sensitivity, specificity and AUC were 0.91, 0.85 and 0.98 respectively.

We found no statistically significant differences in sensitivities between studies with and without the HBP (p = 0.1651).

Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer globally, poses a substantial health burden. Influenced by risk factors such as hepatitis B or C virus infections, chronic consumption of alcohol, and metabolic dysfunction, its exact etiology likely involves a complex interplay between viral infection, hepatocyte mutations, and chronic liver diseases like cirrhosis and metabolic dysfunction-associated steatohepatitis, and demographic variables like sex, race, and age. Disease stage significantly impacts the prognosis of HCC. There is significant potential for life-saving and socioeconomic benefits through the implementation of surveillance programs and the introduction of low-cost screening measures for high-risk groups; these screening measures include ultrasound imaging and blood tests. Treatment options for HCC encompass liver resection, transplantation, transarterial chemoembolization, radiation therapy, chemotherapy, targeted therapy, and immunotherapy. Despite therapeutic advances, treating advanced HCC remains challenging, emphasizing the need for continued efforts in prevention, early detection, and development of treatments to improve prognosis and long-term survival.

Hepatocellular carcinoma (HCC) is a primary liver tumor generally diagnosed based on radiographic findings. Metastatic disease is typically associated with increased tumor diameter, multifocality, and vascular invasion. We report a case of a patient who presented with extrahepatic HCC metastasis to a portocaval lymph node with occult hepatic primary on computed tomography (CT). We review the literature for cases of extrahepatic HCC presentation without known hepatic lesions and discuss strategies to differentiate between metastatic and ectopic HCC.

A 67-year-old male with remotely treated hepatis C was referred for evaluation of an enlarging portocaval, mixed cystic-solid mass. Serial CT evaluations demonstrated steatosis, but no cirrhosis or liver lesions. Endoscopic ultrasound demonstrated a normal-appearing pancreas, biliary tree, and liver. Fine needle aspiration yielded atypical cells. The differential diagnosis included duodenal or pancreatic cyst, lymphoproliferative cyst, stromal or mesenchymal lesions, nodal involvement from gastrointestinal or hematologic malignancy, or duodenal gastro-intestinal stromal tumor. After review by a multidisciplinary tumor board, the patient underwent open surgical resection of a 5.2 cm × 5.5 cm retroperitoneal mass with pathology consistent with moderately-differentiated HCC. Magnetic resonance imaging (MRI) subsequently demonstrated a 1.2 cm segment VIII hepatic lesion with late arterial enhancement, fatty sparing, and intrinsic T1 hyperintensity. Alpha fetoprotein was 23.3 ng/mL. The patient was diagnosed with HCC with portocaval nodal involvement. Review: We surveyed the literature for HCC presenting as extrahepatic masses without history of concurrent or prior intrahepatic HCC. We identified 18 cases of extrahepatic HCC ultimately found to represent metastatic lesions, and 30 cases of extrahepatic HCC found to be primary, ectopic HCC.

Hepatocellular carcinoma can seldomly present with extrahepatic metastasis in the setting of occult primary. In patients with risk factors for HCC and lesions suspicious for metastatic disease, MRI may be integral to identifying small hepatic lesions and differentiating from ectopic HCC. Tumor markers may also have utility in establishing the diagnosis.

Using external actuation sources to navigate untethered drug-eluting microrobots in the bloodstream offers great promise in improving the selectivity of drug delivery, especially in oncology, but the current field forces are difficult to maintain with enough strength inside the human body (>70-centimeter-diameter range) to achieve this operation. Here, we present an algorithm to predict the optimal patient position with respect to gravity during endovascular microrobot navigation. Magnetic resonance navigation, using magnetic field gradients in clinical magnetic resonance imaging (MRI), is combined with the algorithm to improve the targeting efficiency of magnetic microrobots (MMRs). Using a dedicated microparticle injector, a high-precision MRI-compatible balloon inflation system, and a clinical MRI, MMRs were successfully steered into targeted lobes via the hepatic arteries of living pigs. The distribution ratio of the microrobots (roughly 2000 MMRs per pig) in the right liver lobe increased from 47.7 to 86.4% and increased in the left lobe from 52.2 to 84.1%. After passing through multiple vascular bifurcations, the number of MMRs reaching four different target liver lobes had a 1.7- to 2.6-fold increase in the navigation groups compared with the control group. Performing simulations on 19 patients with hepatocellular carcinoma (HCC) demonstrated that the proposed technique can meet the need for hepatic embolization in patients with HCC. Our technology offers selectable direction for actuator-based navigation of microrobots at the human scale.

Hepatocellular carcinoma (HCC) accounts for 75% of primary liver tumors. Controlling risk factors associated with its development and implementing screenings in risk populations does not seem sufficient to improve the prognosis of these patients at diagnosis. The development of a predictive prognostic model for mortality at the diagnosis of HCC is proposed.

In this retrospective multicenter study, the analysis of data from 191 HCC patients was conducted using machine learning (ML) techniques to analyze the prognostic factors of mortality that are significant at the time of diagnosis. Clinical and analytical data of interest in patients with HCC were gathered.

Meeting Milan criteria, Barcelona Clinic Liver Cancer (BCLC) classification and albumin levels were the variables with the greatest impact on the prognosis of HCC patients. The ML algorithm that achieved the best results was random forest (RF).

The development of a predictive prognostic model at the diagnosis is a valuable tool for patients with HCC and for application in clinical practice. RF is useful and reliable in the analysis of prognostic factors in the diagnosis of HCC. The search for new prognostic factors is still necessary in patients with HCC.

At present, although there are tumor markers for hepatocellular carcinoma (HCC), markers with better predictive efficiency are needed. SAA4 gene expression in liver tumor and paracancerous tissues was analyzed using The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were analyzed and visualized by heatmap and volcano plot. Survival analysis was performed based on SAA4 expression. SAA4 expression was compared in patients grouped based on clinicopathological features, and gene set enrichment analysis (GSEA) was conducted. Immunohistochemical staining was used to verify the SAA4 protein staining intensity from The Human Protein Atlas database and our center's samples. The diagnostic value of SAA4 for HCC was evaluated by receiver operating characteristic curves. SAA4 was expressed at low levels in HCC tissues, and low SAA4 expression was associated with a poor prognosis in HCC. In addition, SAA4 expression decreased with HCC progression. There were 188 upregulated DEGs and 1551 downregulated DEGs between the high and low SAA4 expression groups. Complement and coagulation cascades, fatty acid metabolism, and ECM receptor interaction were significantly enriched in the GSEA. SAA4 had good predictive efficacy for HCC and even early HCC and was superior to AFP. In general, low SAA4 expression was associated with advanced HCC stage and a poor prognosis. In addition, SAA4 may be helpful for the diagnosis of early HCC and may become a novel tumor marker with good predictive power for HCC.

Based on the Liver Imaging Data and Reporting System (LI-RADS) guidelines, Hepatocellular Carcinoma (HCC) can be diagnosed using imaging criteria in patients at risk of HCC.

This study aimed to assess the diagnostic value of LI-RADS in high-risk patients with HCC.

This systematic review is conducted on international databases, including Google Scholar, Web of Science, PubMed, Embase, PROQUEST, and Cochrane Library, with appropriate keywords. Using the binomial distribution formula, the variance of each study was calculated, and all the data were analyzed using STATA version 16. The pooled sensitivity and specificity were determined using a random-effects meta-analysis approach. Also, we used the chi-squared test and I2 index to calculate heterogeneity among studies, and Funnel plots and Egger tests were used for evaluating publication bias.

The pooled sensitivity was estimated at 0.80 (95% CI 0.76-0.84). According to different types of Liver Imaging Reporting and Data Systems (LI-RADS), the highest pooled sensitivity was in version 2018 (0.83 (95% CI 0.79-0.87) (I2: 80.6%, P of chi 2 test for heterogeneity <0.001 and T2: 0.001). The pooled specificity was estimated as 0.89 (95% CI 0.87-0.92). According to different types of LI-RADS, the highest pooled specificity was in version 2014 (93.0 (95% CI 89.0-96.0) (I2: 81.7%, P of chi 2 test for heterogeneity <0.001 and T2: 0.001).

LI-RADS can assist radiologists in achieving the required sensitivity and specificity in high-risk patients suspected to have HCC. Therefore, this strategy can serve as an appropriate tool for identifying HCC.

The sensitivity of the Liver Imaging Reporting and Data System (LI-RADS) in the diagnosis of hepatocellular carcinoma (HCC) on gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) was suboptimal. This study evaluated the LI-RADS diagnostic performance in HCC when modifying the definition of washout using the transition phase (TP) or hepatobiliary phase (HBP) hypointensity on EOB-MRI.

This retrospective study included patients at high risk of HCC who underwent EOB-MRI from June 2016 to June 2021. Three modified LI-RADS (mLI-RADS) algorithms were formulated according to different definitions of washout as follows: (a) portal venous phase (PVP) or TP hypointensity, (b) PVP or HBP hypointensity, and (c) PVP or TP or HBP hypointensity. Diagnostic performance, including sensitivity, specificity, and accuracy, was compared between mLI-RADS and LI-RADS v2018 using McNemar's test.

A total of 379 patients with 426 pathologically confirmed hepatic observations (250 HCCs, 88 nonHCC malignancies, and 88 benign lesions) were included in our study. The sensitivity rates of mLI-RADS a-c (80.0 %, 80.8 %, and 80.8 %) were all higher than that of LI-RADS v2018 (74.4 %) (all p < 0.05). The specificity rates of mLI-RADS a-c (86.9 %, 85.8 %, and 85.8 %) were all slightly lower than that of LI-RADS v2018 (88.6 %), although no statistically significant difference was noted (all p > 0.05). The accuracies of the three mLI-RADS algorithms were the same and were all higher than that of LI-RADS v2018 (82.9 % vs. 80.3 %, all p < 0.05).

When the definition of washout appearance was extended to TP or HBP hypointensity on EOB-MRI, the diagnostic sensitivity of LI-RADS for HCC improved without decreasing specificity.

Ultrasonography has a low sensitivity for detecting early-stage hepatocellular carcinoma (HCC) in cirrhotic patients. Non-contrast abbreviated magnetic resonance imaging (aMRI) demonstrated a comparable performance to that of magnetic resonance imaging without the risk of contrast media exposure and at a lower cost than that of full diagnostic MRI. We aimed to investigate the cost-effectiveness of non-contrast aMRI for HCC surveillance in cirrhotic patients, using ultrasonography with alpha-fetoprotein (AFP) as a reference.

Cost-utility analysis was performed using a Markov model in Thailand and the United States. Incremental cost-effectiveness ratios were calculated using the total costs and quality-adjusted life years (QALYs) gained in each strategy. Surveillance protocols were considered cost-effective based on a willingness-to-pay value of $4,665 (160,000 Thai Baht) in Thailand and $50,000 in the United States.

aMRI was cost-effective in both countries with incremental cost-effectiveness ratios of $3,667/QALY in Thailand and $37,062/QALY in the United States. Patient-level microsimulations showed consistent findings that aMRI was cost-effective in both countries. By probabilistic sensitivity analysis, aMRI was found to be more cost-effective than combined ultrasonography and AFP with a probability of 0.77 in Thailand and 0.98 in the United States. By sensitivity analyses, annual HCC incidence was revealed as the most influential factor affecting cost-effectiveness. The cost-effectiveness of aMRI increased in settings with a higher HCC incidence. At a higher HCC incidence, aMRI would remain cost-effective at a higher aMRI-to-ultrasonography with AFP cost ratio.

Compared to ultrasonography with AFP, non-contrast aMRI is a cost-effective strategy for HCC surveillance and may be useful for such surveillance in cirrhotic patients, especially in those with high HCC risks.

The 10th Global Forum for Liver Magnetic Resonance Imaging (MRI) was held as a virtual 2-day meeting in October 2021, attended by delegates from North and South America, Asia, Australia, and Europe. Most delegates were radiologists with experience in liver MRI, with representation also from specialists in liver surgery, oncology, and hepatology. Presentations, discussions, and working groups at the Forum focused on the following themes: • Gadoxetic acid in clinical practice: Eastern and Western perspectives on current uses and challenges in hepatocellular carcinoma (HCC) screening/surveillance, diagnosis, and management • Economics and outcomes of HCC imaging • Radiomics, artificial intelligence (AI) and deep learning (DL) applications of MRI in HCC. These themes are the subject of the current manuscript. A second manuscript discusses multidisciplinary tumor board perspectives: how to approach early-, mid-, and late-stage HCC management from the perspectives of a liver surgeon, interventional radiologist, and oncologist (Taouli et al, 2023). Delegates voted on consensus statements that were developed by working groups on these meeting themes. A consensus was considered to be reached if at least 80% of the voting delegates agreed on the statements. CLINICAL RELEVANCE STATEMENT: This review highlights the clinical applications of gadoxetic acid-enhanced MRI for liver cancer screening and diagnosis, as well as its cost-effectiveness and the applications of radiomics and AI in patients with liver cancer. KEY POINTS: • Interpretation of gadoxetic acid-enhanced MRI differs slightly between Eastern and Western guidelines, reflecting different regional requirements for sensitivity vs specificity. • Emerging data are encouraging for the cost-effectiveness of gadoxetic acid-enhanced MRI in HCC screening and diagnosis, but more studies are required. • Radiomics and artificial intelligence are likely, in the future, to contribute to the detection, staging, assessment of treatment response and prediction of prognosis of HCC-reducing the burden on radiologists and other specialists and supporting timely and targeted treatment for patients.

To estimate the prevalence of Liver Imaging Reporting and Data System (LI-RADS, LR) v2018 categories reported on CT or MRI performed for hepatocellular carcinoma (HCC) screening.

This retrospective study included all reports for CT and MRI exams performed for HCC screening patients between 8/2018 and 4/2020. Patients with ultrasound, CT, or MRI of the abdomen within two years of the index exam were excluded. From each radiology report, we extracted number of reported liver observations, and LI-RADS v2018 category for each observation.

There were 329 patients (170 [52%] male, mean age 59 years [SD 12]), of whom 177 (54%) had MRI with gadoxetate, 72 (22%) had MRI with extracellular contrast, 7 (2%) had MRI with unspecified contrast, and 73 (22%) had CT. Of 329 patients, 199 (60%) had no reported observations; 130 patients had 166 reported observations: 114 (68.7%) LR-1, 8 (4.8%) LR-2, 21 (12.6%) LR-3, 6 (3.6%) LR-4, 13 (7.8%) LR-5, 3 (1.8%) LR-M, and 1 (0.6%) LR-TIV. Of 114 LR-1 observations, 78 (68%) were cysts, 17 (15%) were hemangiomas, 12 (11%) were vascular shunts, 3 (3%) were focal nodular hyperplasia, 2 (2%) were siderotic nodules, 1 (1%) was a lipoma, and 1 (1%) was biliary hamartoma. There were 23 observations with probably or definitely malignant categories (LR-4, LR-5, LR-M or LR- TIV), reported in 20/329 (6%) of patients.

In a cohort of at-risk patients undergoing contrast-enhanced CT/MRI for HCC screening, 60% of had no liver observations, and 6 % had probably or definitely malignant observations.

The prevalence of LI-RADS v2018 categories on CT or MR exams used for HCC screening can help develop screening criteria and assess cost-effectiveness of surveillance strategies with CT and MRI.

Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, represents a growing health challenge worldwide. The incidence of HCC is rising, which, in turn, has led to a corresponding increase in the associated number of deaths. HCC will become the third leading cause of cancer-related deaths in the United States by 2030. HCC usually develops in the setting of chronic liver disease. Individuals at increased risk of HCC are recommended to undergo surveillance with ultrasound every 6 months along with serum α-fetoprotein testing. Computed tomography (CT) and magnetic resonance imaging (MRI) are considered alternatives based on specific patient factors. Lesions suspicious for HCC are recommended to undergo a diagnostic testing, which includes contrast-enhanced multiphase CT or MRI and liver biopsy when findings are indeterminate. The Barcelona Clinic Liver Cancer prognosis and treatment strategy is the most used assessment for patients with HCC ( Fig. 2 ). Curative therapies include resection, liver transplantation, and ablation. Locoregional therapies, such as transarterial chemoembolization and radioembolization, can be used for patients with intermediate-stage HCC. For patients with advanced-stage HCC, systemic therapy is often used. This review aims to provide an overview of HCC from a hepatologist's perspective, including epidemiology, screening, surveillance, diagnosis, and management.

Globally, hepatocellular carcinoma (HCC) is the fourth most common cause of death from cancer. The prevalence of this pathology, which has been on the rise in the last 30 years, has been predicted to continue increasing. HCC is the most common cause of cancer-related morbidity and mortality in Egypt and is also the most common cancer in males. Chronic liver diseases, including chronic hepatitis C, which is a primary health concern in Egypt, are considered major risk factors for HCC. However, HCC surveillance is recommended for patients with chronic hepatitis B virus (HBV) and liver cirrhosis; those above 40 with HBV but without cirrhosis; individuals with hepatitis D co-infection or a family history of HCC; and Nonalcoholic fatty liver disease (NAFLD) patients exhibiting significant fibrosis or cirrhosis. Several international guidelines aid physicians in the management of HCC. However, the availability and cost of diagnostic modalities and treatment options vary from one country to another. Therefore, the current guidelines aim to standardize the management of HCC in Egypt. The recommendations presented in this report represent the current management strategy at HCC treatment centers in Egypt. Recommendations were developed by an expert panel consisting of hepatologists, oncologists, gastroenterologists, surgeons, pathologists, and radiologists working under the umbrella of the Egyptian Society of Liver Cancer. The recommendations, which are based on the currently available local diagnostic aids and treatments in the country, include recommendations for future prospects.

Abbreviated MRI for surveillance in patients at risk for hepatocellular carcinoma (HCC) has recently gained interest.

To compare the performance among the three types of abbreviated MRI protocols for the detection of hepatic malignancies in patients at risk for HCC.

This retrospective review using data from a prospective-registry study included 221 patients with one or more hepatic nodules detected during surveillance for chronic liver disease. Patients underwent MRI with extracellular contrast agents (ECA-MRI) and MRI with hepatobiliary agents (HBA-MRI) before surgery. Sequences from each MRI were extracted to create three simulated abbreviated MRI (aMRI) sets: noncontrast aMRI (NC-aMRI), dynamic aMRI (Dyn-aMRI), and hepatobiliary phase aMRI (HBP-aMRI). Two readers evaluated each set and reported the probability of malignancy and possibility of non-HCC malignancy per lesion. Using the pathology report as reference, the diagnostic performance of each aMRI was compared.

This study included 289 observations (219 HCCs, 22 non-HCC malignancies, and 48 benign lesions). Defining category definite malignancy as test positive, the performance of each aMRI was as follows: sensitivity, 94.6%, 88.8%, and 92.5%; and specificity, 83.3%, 91.7%, and 85.4% for HBP-aMRI, Dyn-aMRI, and NC-aMRI, respectively. Pairwise comparison revealed higher sensitivity of HBP-aMRI than both Dyn-aMRI (P = 0.003) and NC-aMRI (P = 0.025), and higher specificity of Dyn-aMRI than HBP-aMRI (P = 0.046).

HBP-aMRI showed better sensitivity than Dyn-aMRI or NC-aMRI, whereas the sensitivity of NC-aMRI was comparable to Dyn-aMRI in the detection of malignancy in high-risk patients. Dyn-aMRI showed better specificity than HBP-aMRI.

To investigate the image quality and lesion conspicuity of a deep-learning-based contrast-boosting (DL-CB) algorithm on double-low-dose (DLD) CT of simultaneous reduction of radiation and contrast doses in participants at high-risk for hepatocellular carcinoma (HCC).

Participants were recruited and underwent four-phase dynamic CT (NCT04722120). They were randomly assigned to either standard-dose (SD) or DLD protocol. All CT images were initially reconstructed using iterative reconstruction, and the images of the DLD protocol were further processed using the DL-CB algorithm (DLD-DL). The primary endpoint was the contrast-to-noise ratio (CNR), the secondary endpoint was qualitative image quality (noise, hepatic lesion, and vessel conspicuity), and the tertiary endpoint was lesion detection rate. The t-test or repeated measures analysis of variance was used for analysis.

Sixty-eight participants with 57 focal liver lesions were enrolled (20 with HCC and 37 with benign findings). The DLD protocol had a 19.8% lower radiation dose (DLP, 855.1 ± 254.8 mGy·cm vs. 713.3 ± 94.6 mGy·cm, p = .003) and 27% lower contrast dose (106.9 ± 15.0 mL vs. 77.9 ± 9.4 mL, p < .001) than the SD protocol. The comparative analysis demonstrated that CNR (p < .001) and portal vein conspicuity (p = .002) were significantly higher in the DLD-DL than in the SD protocol. There was no significant difference in lesion detection rate for all lesions (82.7% vs. 73.3%, p = .140) and HCCs (75.7% vs. 70.4%, p = .644) between the SD protocol and DLD-DL.

DL-CB on double-low-dose CT provided improved CNR of the aorta and portal vein without significant impairment of the detection rate of HCC compared to the standard-dose acquisition, even in participants at high risk for HCC.

• Deep-learning-based contrast-boosting algorithm on double-low-dose CT provided an improved contrast-to-noise ratio compared to standard-dose CT. • The detection rate of focal liver lesions was not significantly differed between standard-dose CT and a deep-learning-based contrast-boosting algorithm on double-low-dose CT. • Double-low-dose CT without a deep-learning algorithm presented lower CNR and worse image quality.

This review was undertaken to assess the diagnostic value of the Liver Imaging Reporting and Data System (LI-RADS) in patients with a high risk of hepatocellular carcinoma (HCC). Google Scholar, PubMed, Web of Science, Embase, PROQUEST, and Cochrane Library, as the international databases, were searched with appropriate keywords. Using the binomial distribution formula, the variance of all studies was calculated, and using Stata version 16 (StataCorp LLC, College Station, TX, USA), the obtained data were analyzed. Using a random-effect meta-analysis approach, we determined the pooled sensitivity and specificity. Utilizing the funnel plot and Begg's and Egger's tests, we assessed publication bias. The results exhibited pooled sensitivity and pooled specificity of 0.80% and 0.89%, respectively, with a 95% confidence interval (CI) of 0.76-0.84 and 0.87-0.92, respectively. The 2018 version of LI-RADS showed the greatest sensitivity (0.83%; 95% CI 0.79-0.87; I ² = 80.6%; P < 0.001 for heterogeneity; T ² = 0.001). The maximum pooled specificity was detected in LI-RADS version 2014 (American College of Radiology, Reston, VA, USA; 93.0%; 95% CI 89.0-96.0; I ² = 81.7%; P < 0.001 for heterogeneity; T ² = 0.001). In this review, the results of estimated sensitivity and specificity were satisfactory. Therefore, this strategy can serve as an appropriate tool for identifying HCC.

To show the effectiveness of plane wave HighFrame-Rate CEUS (HiFR-CEUS) compared with "conventional" (plane wave) CEUS (C-CEUS) in the characterization of small (< 2 cm) focal liver lesions (FLLs) not easily detected by CT in cirrhotic patients. HiFR-CEUS exploit an ultra-wideband nonlinear process to combine fundamental, second and higher-order harmonic signals generated by ultrasound contrast agents to increase the frame rate. C-CEUS is limited by the transmission principle, and its frame-rate is around 10 FPS. With HiFR-CEUS (Shenzhen Mindray Bio-Medical Electronics Co., China), the frame-rate reached 60 FPS.

Ultrasound detected small FLLs (< 2 cm) in 63 cirrhotic patients during follow-up (June 2019-February 2020); (7 nodules < 1 cm and were not evaluable by spiral CT). Final diagnosis was obtained with MRI (47) or fine needle aspiration (16 cases) C-CEUS was performed and HiFR-CEUS was repeated after 5 min; 0.8-1.2 ml of contrast media (SonoVue, Bracco, Italy) was used. 57 nodules were better evaluable with HiFR-CEUS; 6 nodules were equally evaluable by both techniques; final diagnosis was: 44 benign lesions (29 hemangiomas, 1 amartoma, 2 hepatic cysts; 2 focal nodular hyperplasias, 3 regenerative macronodules, 3 AV-shunts, 3 hepatic sparing areas and 1 focal steatosis) and 19 malignant one (17 HCCs, 1 cholangioca, 1 metastasis); statistical evaluation for better diagnosis with X2 test (SPSS vers. 26); we used LI-RADS classification for evaluating sensitivity, specificity PPV, NPV and diagnostic accuracy of C- and HFR-CEUS. Corrispective AU-ROC were calculated.

C-CEUS and HiFR-CEUS reached the same diagnosis in 29 nodules (13 nodules > 1 < 1.5 cm; 16 nodules > 1.5 < 2 cm); HiFR-CEUS reached a correct diagnosis in 32 nodules where C-CEUS was not diagnostic (6 nodules < 1 cm; 17 nodules > 1 < 1.5 cm; 9 nodules > 1.5 < 2 cm); C-CEUS was better in 2 nodules (1 < 1 cm and 1 > 1 < 1.5 cm). Some patient's (sex, BMI, age) and nodule's characteristics (liver segment, type of diagnosis, nodule's dimensions (p = 0.65)) were not correlated with better diagnosis (p ns); only better visualization (p 0.004) was correlated; C-CEUS obtained the following LI-RADS: type-1: 18 Nodules, type-2: 21; type-3: 7, type-4: 7; type-5: 8; type-M: 2; HiFR-CEUS: type-1: 38 Nodules, type-2: 2; type-3:4, type-4: 2; type-5: 15; type-M: 2; In comparison with final diagnosis: C-CEUS: TP: 17; TN: 39; FP: 5; FN:2; HIFR-CEUS: TP: 18; TN: 41; FP: 3; FN:1; C-CEUS: sens: 89.5%; Spec: 88.6%, PPV: 77.3%; NPV: 95.1%; Diagn Acc: 88.6% (AU-ROC: 0.994 ± SEAUC: 0.127; CI: 0.969-1.019); HiHFR CEUS: sens: 94.7%; Spec: 93.2%, PPV: 85.7%; NPV: 97.6%; Diagn Acc: 93.2% (AU-ROC: 0.9958 ± SEAUC: 0.106; CI: 0.975-1.017) FLL vascularization in the arterial phase was more visible with HiFR-CEUS than with C-CEUS, capturing the perfusion details in the arterial phase due to a better temporal resolution. With a better temporal resolution, the late phase could be evaluated longer with HiFR-CEUS (4 min C-CEUS vs. 5 min HiFR-CEUS).

Both C-CEUS and HIFR-CEUS are good non invasive imaging system for the characterization of small lesions detected during follow up of cirrhotic patients. HiFR-CEUS allowed better FLL characterization in cirrhotic patients with better temporal and spatial resolution capturing the perfusion details that cannot be easily observed with C-CEUS.

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the fourth most common cancer among men in South Korea, where the prevalence of chronic hepatitis B infection is high in middle and old age. The current practice guidelines will provide useful and sensible advice for the clinical management of patients with HCC. A total of 49 experts in the fields of hepatology, oncology, surgery, radiology, and radiation oncology from the Korean Liver Cancer Association-National Cancer Center Korea Practice Guideline Revision Committee revised the 2018 Korean guidelines and developed new recommendations that integrate the most up-to-date research findings and expert opinions. These guidelines provide useful information and direction for all clinicians, trainees, and researchers in the diagnosis and treatment of HCC.

To investigate the added value of contrast enhancement boost (CE-boost) images in multiphasic contrast-enhanced CT (CE-CT) for diagnosing small (<20 mm) hypervascular hepatocellular carcinoma (HCC).

This retrospective study included 69 patients (age, 74 ± 8 years; 52 men) with 70 hypervascular HCCs (<20 mm) who underwent multiphasic CE-CT (pre-contrast, late arterial phase [LAP], portal venous phase [PVP], and equilibrium phase). Two types of CE-boost images were generated by subtracting PVP from LAP (LA-PV) images and LAP from PVP (PV-LA) images to enhance the contrast effect of hepatic arterial and portal venous perfusion more selectively. Tumor-to-liver contrast-to-noise ratios (CNRs) in CE-boost images were compared with those in CE-CT images using the Wilcoxon signed-rank test. Two independent readers reviewed the imaging datasets: CE-CT alone and CE-CT with CE-boost images. The diagnostic performance of each dataset was compared using jackknife alternative free-response receiver operating characteristics (JAFROC-1).

The tumor-to-liver CNRs in the LA-PV (6.4 ± 3.0) and PV-LA (-3.3 ± 2.1) images were greater than those in the LAP (3.2 ± 1.7) and PVP images (-1.1 ± 1.4) (p <.001 for both). The reader-averaged figures of merit were 0.751 for CE-CT alone and 0.807 for CE-CT with CE-boost images (p <.001). Sensitivities increased by adding CE-boost images for both readers (p <.001 and = 0.03), while positive predictive values were equivalent (p >.99).

Adding CE-boost images to multiphasic CE-CT can improve the diagnostic accuracy and sensitivity for small hypervascular HCC by increasing the tumor-to-liver CNR.

Preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is essential in obtaining a successful surgical treatment, in decreasing recurrence, and in improving survival.

To investigate the value of multiparametric magnetic resonance imaging (MRI)-based radiomics in the prediction of peritumoral MVI in HCC.

A total of 102 patient with pathologically proven HCC after surgical resection from June 2014 to March 2018 were enrolled in this retrospective study. Histological analysis of resected specimens confirmed positive MVI in 48 patients and negative MVI in 54 patients. Radiomics features were extracted from four MRI sequences and selected with the least absolute shrinkage and selection operator (LASSO) regression and used to analyze the tumoral and peritumoral regions for MVI. Univariate logistic regression was employed to identify the most important clinical factors, which were integrated with the radiomics signature to develop a nomogram.

In total, 11 radiomics features were selected and used to build the radiomics signature. The serum level of alpha-fetoprotein was identified as the clinical factor with the highest predictive value. The developed nomogram achieved the highest AUC in predicting MVI status. The decision curve analysis confirmed the potential clinical utility of the proposed nomogram.

The multiparametric MRI-based radiomics nomogram is a promising tool for the preoperative diagnosis of peritumoral MVI in HCCs and helps determine the appropriate medical or surgical therapy.

Background The Liver Imaging Reporting and Data System (LI-RADS) CT and MRI algorithm applies equally to CT, MRI with extracellular contrast agents (ECA-MRI), and MRI with gadoxetate (Gx-MRI). Purpose To estimate pooled percentages of hepatocellular carcinoma (HCC) and overall malignancy for each LI-RADS category with CT and MRI. Materials and Methods MEDLINE and EMBASE databases were searched for research articles (January 2014-April 2021) reporting the percentages of observations in each LI-RADS category with use of versions 2014, 2017, or 2018. Study design, population characteristics, imaging modality, reference standard, and numbers of HCC and non-HCC malignancies in each category were recorded. A random-effects model evaluated the pooled percentage of HCC and overall malignancy for each category. Results There were 49 studies with 9620 patients and a total 11 562 observations, comprising 7921 HCCs, 1132 non-HCC malignancies, and 2509 benign entities. No HCC or non-HCC malignancies were reported with any modality in the LR-1 category. The pooled percentages of HCC for CT, ECA-MRI, and Gx-MRI, respectively, were 10%, 6%, and 1% for LR-2 (P = .16); 48%, 31%, and 38% for LR-3 (P = .42); 76%, 64%, and 77% for LR-4 (P = .62); 96%, 95%, and 96% for LR-5 (P = .76); 88%, 76%, and 78% for LR-5V or LR-TIV (tumor in vein) (P = .42); and 20%, 30%, and 35% for LR-M (P = .32). Most LR-M (93%-100%) and LR-5V or LR-TIV (99%-100%) observations were malignant, regardless of modality. Conclusion There was no difference in percentages of hepatocellular carcinoma and overall malignancy between CT, MRI with extracellular contrast agents, and MRI with gadoxetate for any Liver Imaging Reporting and Data System categories. © RSNA, 2023 Supplemental material is available for this article See also the editorial by Ronot in this issue.

A contrast-free ultrasound microvasculature imaging technique was evaluated in this study to determine whether extracting morphological features of the vascular networks in hepatic lesions can be beneficial in differentiating benign and malignant tumors (hepatocellular carcinoma (HCC) in particular).

A total of 29 lesions from 22 patients were included in this work. A post-processing algorithm consisting of clutter filtering, denoising, and vessel enhancement steps was implemented on ultrasound data to visualize microvessel structures. These structures were then further characterized and quantified through additional image processing. A total of nine morphological metrics were examined to compare different groups of lesions. A two-sided Wilcoxon rank sum test was used for statistical analysis.

In the malignant versus benign comparison, six of the metrics manifested statistical significance. Comparing only HCC cases with the benign, only three of the metrics were significantly different. No statistically significant distinction was observed between different malignancies (HCC versus cholangiocarcinoma and metastatic adenocarcinoma) for any of the metrics.

Obtained results suggest that designing predictive models based on such morphological characteristics on a larger sample size may prove helpful in differentiating benign from malignant liver masses.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and currently the third-leading cause of cancer-related death worldwide. Recently, artificial intelligence (AI) has emerged as an important tool to improve clinical management of HCC, including for diagnosis, prognostication and evaluation of treatment response. Different AI approaches, such as machine learning and deep learning, are both based on the concept of developing prediction algorithms from large amounts of data, or big data. The era of digital medicine has led to a rapidly expanding amount of routinely collected health data which can be leveraged for the development of AI models. Various studies have constructed AI models by using features extracted from ultrasound imaging, computed tomography imaging and magnetic resonance imaging. Most of these models have used convolutional neural networks. These tools have shown promising results for HCC detection, characterization of liver lesions and liver/tumor segmentation. Regarding treatment, studies have outlined a role for AI in evaluation of treatment response and improvement of pre-treatment planning. Several challenges remain to fully integrate AI models in clinical practice. Future research is still needed to robustly evaluate AI algorithms in prospective trials, and improve interpretability, generalizability and transparency. If such challenges can be overcome, AI has the potential to profoundly change the management of patients with HCC. The purpose of this review was to sum up current evidence on AI approaches using imaging for the clinical management of HCC.

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the fourth most common cancer among men in South Korea, where the prevalence of chronic hepatitis B infection is high in middle and old age. The current practice guidelines will provide useful and sensible advice for the clinical management of patients with HCC. A total of 49 experts in the fields of hepatology, oncology, surgery, radiology, and radiation oncology from the Korean Liver Cancer Association-National Cancer Center Korea Practice Guideline Revision Committee revised the 2018 Korean guidelines and developed new recommendations that integrate the most up-to-date research findings and expert opinions. These guidelines provide useful information and direction for all clinicians, trainees, and researchers in the diagnosis and treatment of HCC.

Despite advances in diagnostic and therapeutic methods, the prognosis of patients with hepatocellular carcinoma (HCC) remains poor due to the delay in diagnosis. Herein, we aimed to discover a highly sensitive and specific biomarker for HCC based on genomic big data analysis and create an HCC-targeted imaging probe using carbon nanodots (CNDs) as contrast agents. In genomic analysis, we selected glucose transporter 2 (GLUT2) as a potential imaging target for HCC. We confirmed the target suitability by immunohisto-chemistry tests of 339 patient samples, where 81.1% of the patients exhibited underexpression of GLUT2, i.e., higher GLUT2 intensity in non-tumor tissues than in tumor tissues. To visualize GLUT2, we conjugated CNDs with glucosamine (GLN) as a targeting ligand to yield glucosamine-labeled CNDs (GLN-CNDs). A series of in vitro and in vivo experiments were conducted on GLUT2-modified HepG2 cells to confirm the specificity of the GLN-CNDs. Since the GLUT2 expression is higher in hepatocytes than in HCC cells, the GLUT2-targeted contrast agent is highly attached to normal cells. However, it is possible to produce images in the same form as the images obtained with a cancer cell-targeted contrast agent by inverting color scaling. Our results indicate that GLUT2 is a promising target for HCC and that GLN-CNDs may potentially be used as targeted imaging probes for diagnosing HCC.