To evaluate the performance of Liver Imaging Reporting and Data System (LI-RADS) contrast-enhanced ultrasound (CEUS) Nonradiation treatment response assessment (TRA) categorization v2024 for detecting viable tumors of ablated hepatocellular carcinoma (HCC).

Between June 2020 and December 2022, standardized CEUS data of HCC patients were prospectively collected. A retrospective analysis of LI-RADS CEUS Nonradiation TRA v2024 evaluation on HCCs was conducted by 2 independent radiologists assigning per-lesion TRA (TR-nonviable, TR-equivocal, or TR-viable) categorizations. Inter-reader agreement between the 2 readers and inter-modality agreement between LI-RADS CEUS and CT/MRI LI-RADS TRA were assessed. The diagnostic performance of imaging criteria was explored. The potential influencing factors of LI-RADS TRA categorization across modalities were further analyzed.

A total of 101 CEUS-LI-RADS TRA category evaluations of 88 lesions in 83 patients were included. Inter-reader agreement for the 2 readers were substantial to almost perfect (intralesional tumor viability: κ = 0.92, 95% CI: 0.76-1.0; perilesional tumor viability: κ = 0.72, 95% CI: 0.57-0.87; CEUS LR-TR: κ = 0.71, 95% CI: 0.55-0.88). Inter-modality agreements between CEUS and CT/MRI LI-RADS TRA categorizations were excellent (ICC = 0.90). CEUS LR-TRA categorization demonstrated good diagnostic performance, particularly in specificity (88.1%-100 %) and negative predictive value (NPV: 93.9%-97.9 %). Time period and abstract shape were identified as significant factors influencing reader evaluations (p < 0.05).

LI-RADS CEUS Nonradiation TRA v2024 demonstrates fine inter-reader and inter-modality agreement, with outstanding diagnostic performance, supporting its potential for clinical application in assessing treatment response for ablated HCC.

To develop a model combining contrast-enhanced ultrasound (CEUS) and ethoxybenzyl-enhanced magnetic resonance imaging (EOB-MRI) for predicting microvascular invasion (MVI) in solitary hepatocellular carcinoma (HCC) ≤5 cm.

Patients between December 2019 and May 2024 in one center were retrospectively enrolled and randomly divided into the training cohort and internal validation cohort in a ratio of 7:3. Patients in a separate center were enrolled between January 2022 and December 2023 to be included as the external validation cohort. CEUS and EOB-MRI image features were extracted and used to develop models in the training cohort, and verified in the two validation cohorts. The predictive accuracy and clinical utility of models were evaluated using area under receiver operating characteristic curve (AUROC), Brier score, calibration plot and decision curve analysis (DCA). Net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to compare different models.

From the two centers a total of 493 patients, of which 134 were MVI positive, were evaluated. The CEUS+EOB model included seven image features and showed better discrimination ability than the individual CEUS/EOB-MRI model, with AUROCs of 0.92, 0.94, and 0.90 in the training cohort and two validation cohorts, respectively (p<0.05). The lowest Brier score of the combined model indicated the highest predictive precision. DCA also showed that the combined model added more net benefits. Both the NRI and IDI values >0 indicated that the combined model had significantly positive improvement (p<0.05).

The CEUS+EOB model was developed to assist clinicians in evaluating MVI in solitary HCC ≤5 cm.

In all imaging methods, including contrast-enhanced ultrasound (CEUS), enhancement in the late phase (LP) is an important criterion for differentiating between benign and malignant focal liver lesions (FLLs). In general, malignant liver lesions are characterized by hypoenhancement and washout in the LP. A lesion with LP hyperenhancement or isoenhancement in the non-cirrhotic liver is usually benign. However, LP hypoenhancement in benign lesions is not so rare, and is even normal and the standard for some lesions, and there are exceptions for each tumor entity that can represent a diagnostic challenge. Knowing these contrast patterns and exceptions is key for correct diagnosis and patient management. The following narrative review describes the contrast behaviors and the frequency of washout and LP hypoenhancement for common as well as rare benign liver lesions and analyzes its causes.

This meta-analysis examined the diagnostic accuracy of Sonazoid-enhanced ultrasonography (SZ-CEUS) in discriminating malignant from benign focal liver lesions (FLLs) and HCC from non-HCC FLLs. Finding relevant studies required a rigorous PubMed, EMBASE, and other database search. To distinguish malignant from benign FLLs, SZ-CEUS had a pooled sensitivity of 94% (95% CI: 0.91-0.95) and specificity of 84% (95%: 0.78-0.89). HCC distinction had 83% sensitivity and 96% specificity (95% CI: 0.80-0.85 and 0.95-0.97). SZ-CEUS accurately distinguishes malignant from benign FLLs and HCC from non-HCC lesions, especially smaller HCC lesions.

Promoting the early detection and diagnosis of hepatocellular carcinoma (HCC) is a critical strategy to improve patient outcomes as this can lead to greater access to curative treatments. This review highlights the diagnostic tests for HCC, including the use of the Liver Imaging Reporting and Data System systems and histopathology. Staging is essential for informing prognosis and guiding treatment decisions; this review also covers a widely used and well-validated staging system called the Barcelona-Clinic Liver Cancer (BCLC) algorithm. The BCLC incorporates tumor status, liver function, and patient performance to stage patients with newly diagnosed HCC.

Ovarian-Adnexal Reporting and Data System (O-RADS) US provides a standardized lexicon for ovarian and adnexal lesions, facilitating risk stratification based on morphological features for malignancy assessment, which is essential for proper management. However, systematic determination of inter-reader reliability in O-RADS US categorization remains unexplored. This study aimed to systematically determine the inter-reader reliability of O-RADS US categorization and identify the factors that affect it.

Original articles reporting the inter-reader reliability of O-RADS US in lesion categorization were identified in the MEDLINE, EMBASE, and Web of Science databases from January 2018 to December 2023. DerSimonian-Laird random-effects models were used to determine the meta-analytic pooled inter-reader reliability of the O-RADS US categorization. Subgroup meta-regression analysis was performed to identify the factors causing study heterogeneity.

Fourteen original articles with 5139 ovarian and adnexal lesions were included. The inter-reader reliability of O-RADS US in lesion categorization ranged from 0.71 to 0.99, with a meta-analytic pooled estimate of 0.83 (95% CI, 0.78-0.88), indicating almost perfect reliability. Substantial study heterogeneity was observed in the inter-reader reliability of the O-RADS US categorization (I2 = 96.9). In subgroup meta-regression analysis, reader experience was the only factor associated with study heterogeneity. Pooled inter-reader reliability of the O-RADS US categorization was higher in studies with all experienced readers (0.86; 95% CI, 0.81-0.91) compared to those with multiple readers including trainees (0.74; 95% CI, 0.70-0.78; P = 0.009). The inter-reader reliability of US descriptors ranged from 0.39 to 0.97, with ascites and peritoneal nodules showing almost perfect reliability (0.79- 0.97).

The O-RADS US risk stratification system demonstrated almost perfect inter-reader reliability in lesion categorization. Our results highlight the importance of targeted training and descriptor simplification to improve inter-reader reliability and clinical adoption.

Contrast-enhanced ultrasound (CEUS) offers a distinctive approach to liver mass diagnosis by utilizing intravenous contrast agents for enhanced visualization of vascular structures and tissue characterization. This review highlights the unique advantages of CEUS compared to computed tomography (CT) and magnetic resonance imaging (MRI), particularly focusing on the Liver Imaging Reporting and Data System framework. Key differences include CEUS's realtime imaging capability, which minimizes arterial phase mistiming and improves detection of hyperenhancing lesions, and its ability to provide detailed washout patterns. Also, CEUS's intravascular nature and lower risk of adverse reactions make it a safer alternative for patients with renal impairment or those contraindicated for CT/MRI.

Background Indeterminate focal liver observations in patients at risk for hepatocellular carcinoma (HCC) may require invasive biopsy or follow-up, which could lead to delays in definitive categorization and to postponement of treatment. Purpose To examine clinical effect of contrast-enhanced US (CEUS) in participants with high-risk indeterminate liver observations categorized as Liver Imaging Reporting and Data System (LI-RADS) category LR-4 (probably HCC) or LI-RADS category LR-M (probably or definitely malignant but not HCC specific) at CT or MRI. Materials and Methods This was a secondary analysis of a prospective international multicenter validation study for CEUS LI-RADS (January 2018 to August 2021). CEUS was performed within 4 weeks of CT or MRI. Tissue histologic and CT or MRI follow-up data were used as reference standards. Clinical effect of CEUS for HCC was evaluated in observations 10 mm or larger categorized as CT/MRI LR-4 and LR-M. Results Included were 109 participants (mean age, 64.3 years ± 8.3 [SD]; 68.8% [75 of 109] male participants) with 113 observations (≥10 mm) categorized as CT/MRI LR-4 (53.1%; 60 of 113) or LR-M (46.9%; 53 of 113). CEUS resulted in management recommendation changes in 33.6% (95% CI: 25, 43; 38 of 113) of observations; among these, 95% (95% CI: 82, 99; 36 of 38) were correct. A total of 30.1% (34 of 113) of CT/MRI LR-4 and LR-M observations were categorized at CEUS as LI-RADS category LR-5 (definite HCC), making biopsy unnecessary; 94% (32 of 34) of these categorizations were correct. Of CT/MRI LR-4 observations, 7% (four of 60) were categorized as CEUS LR-M; subsequent biopsy confirmed non-HCC malignancy in all participants. Clinical impact of CEUS was more substantial for observations 20 mm or larger (n = 68); CEUS helped appropriately categorize both LR-5 and LR-M lesions as HCC and non-HCC malignancies, respectively, and resulted in management recommendation changes in 40% (27 of 68) of observations with 100% accuracy. Conclusion CEUS resolved some high-risk indeterminate liver observations (categorized as LR-4 and LR-M at CT or MRI), with particularly high clinical impact for observations measuring at least 20 mm. Clinical trial registration no. NCT03318380 © RSNA, 2025 Supplemental material is available for this article.

Large language models (LLMs) offer opportunities to enhance radiological applications, but their performance in handling complex tasks remains insufficiently investigated.

To evaluate the performance of LLMs integrated with Contrast-enhanced Ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS) in diagnosing small (≤20mm) hepatocellular carcinoma (sHCC) in high-risk patients.

From November 2014 to December 2023, high-risk HCC patients with untreated small (≤20mm) focal liver lesions (sFLLs), were included in this retrospective study. ChatGPT-4.0, ChatGPT-4o, ChatGPT-4o mini, and Google Gemini were integrated with imaging features from structured CEUS LI-RADS reports to assess their diagnostic performance for sHCC. The diagnostic efficacy of LLMs for small HCC were compared using McNemar test.

The final population consisted of 403 high-risk patients (52 years ± 11, 323 men). ChatGPT-4.0 and ChatGPT-4o demonstrated substantial to almost perfect intra-agreement for CEUS LI-RADS categorization (κ values: 0.76-1.0 and 0.7-0.94, respectively), outperforming ChatGPT-4o mini (κ values: 0.51-0.72) and Google Gemini (κ values: -0.04-0.47). ChatGPT-4.0 had higher sensitivity in detecting sHCC than ChatGPT-4o (83%-89% vs. 70%-78%, p < 0.02) with comparable specificity (76%-90% vs. 83%-86%, p > 0.05). Compared to human readers, ChatGPT-4.0 showed superior sensitivity (83%-89% vs. 63%-78%, p < 0.004) and comparable specificity (76%-90% vs. 90%-95%, p > 0.05) in diagnosing sHCC.

LLM integrated with CEUS LI-RADS offers potential tool in diagnosing sHCC for high-risk patients. ChatGPT-4.0 demonstrated satisfactory consistency in CEUS LI-RADS categorization, offering higher sensitivity in diagnosing sHCC while maintaining comparable specificity to that of human readers.

In 2017, the American College of Radiology introduced the US Liver Imaging Reporting and Data System (LI-RADS) as a framework for US surveillance of patients at risk for developing hepatocellular carcinoma. This has aided in the standardization of technique, clinical reporting, patient management, data collection, and research. Emerging evidence has helped inform changes to the algorithm, now released as LI-RADS US Surveillance version 2024. The updated algorithm, the rationale for changes, and its alignment with the 2023 American Association for the Study of Liver Diseases Practice Guidance are presented.

Intravenous contrast-enhanced ultrasound (CEUS) is a rapidly evolving imaging technique that uses a microbubble contrast agent to enhance ultrasonographic images by augmenting characterization of blood vessels and organ perfusion. CEUS is considered as a useful problem-solving tool and as an indicated first-line imaging modality in select settings. CEUS technique has an inherent advantage over its predecessor B-mode and Doppler imaging. This article reviews different approved and off-label use of CEUS in the pediatric and adult population and also discusses Food and Drug Administration-approved contrast agents in the United States, their reported side effects, and ongoing efforts in the field.

To enhance the accuracy of hepatocellular carcinoma (HCC) diagnosis using contrast-enhanced (CE) US, the American College of Radiology developed the CEUS Liver Imaging Reporting and Data System (LI-RADS). However, the system still exhibits limitations in distinguishing between HCC and non-HCC lesions.

To investigate the viability of employing machine learning methods based on quantitative parameters of contrast-enhanced ultrasound for distinguishing HCC within LR-M nodules.

This retrospective analysis was conducted on pre-treatment CEUS data from liver nodule patients across multiple centers between January 2013 and June 2022. Quantitative analysis was performed using CEUS images, and the machine learning diagnostic models based on quantitative parameters were utilized for the classification diagnosis of LR-M nodules. The performance of the model was assessed using the area under the receiver operating characteristic curve (AUC) and compared with the performance of four radiologists.

The training and internal testing datasets comprised 168 patients (median age, 53 years [IQR, 18 years]), while the external testing datasets from two other centers included 110 patients (median age, 54 years [IQR, 16 years]). In the internal independent test set, the top-performing Random Forest model achieved an AUC of 0.796 (95%CI: 0.729-0.853) for diagnosing HCC. This model exhibited a sensitivity of 0.752 (95%CI: 0.750-0.755) and a specificity of 0.761 (95%CI: 0.758-0.764), outperforming junior radiologists who achieved an AUC of 0.619 (95%CI: 0.543-0.691, p < .01) with sensitivity and specificity of 0.716 (95%CI: 0.713-0.718) and 0.522 (95%CI: 0.519-0.526), respectively.

Significant differences in contrast-enhanced ultrasound quantitative parameters are observed between HCC and non-HCC lesions. Machine learning models leveraging these parameters effectively distinguish HCC categorized as LR-M, offering a valuable adjunct for the accurate classification of liver nodules within the CEUS LI-RADS framework.

To assess the diagnostic efficacy of the CEUS LI-RADS combined with a model constructed on the basis of age, sex, AFP, and PIVKA-II (ASAP) for the diagnosis of HCC in high-risk patients.

This retrospective study included 366 liver lesions from 366 patients who underwent liver CEUS. All liver lesions were characterized and categorized according to CEUS LI-RADS v2017. Two modified methods were applied: LR-3/4/M nodules accompanied by AFP > 200 ng/mL (Criterion 2) or ASAP model score > 0.5256 and CA 19-9 in the normal range (Criterion 3) were recategorized as LR-5. The reference criteria included histopathological or comprehensive imaging and the clinical follow-up results. The diagnostic performance was evaluated and compared by the sensitivity, specificity, PPV, and NPV.

The incidence of HCC in LR-3, LR-4, LR-5, and LR-M was 33.3% (4/12), 86.4% (38/44), 98.5% (191/194) and 82.7% (81/98), respectively. After using Criterion 2 compared to CEUS LI-RADS v2017, the sensitivity of the modified LR-5 for diagnosing HCC increased from 60.8% to 70.7% (p < 0.01) with little effect on its specificity (94.2% vs. 92.3%, p = 1.00) or PPV (98.5% vs. 98.2%, p = 0.86). After using Criterion 3, the sensitivity of the modified LR-5 for the diagnosis of HCC was further improved to 86.9% (p < 0.01), and its specificity and PPV were not significantly changed (92.3% and 98.6%, both p > 0.05).

CEUS LI-RADS combined with the serum biomarker-based ASAP model improved the sensitivity of LR-5 in diagnosing HCC with little effect on its specificity and PPV.

Due to the trend towards increased use of imaging and rising awareness among high-risk patients, gastroenterologists and hepatologists are more frequently confronted with patients with focal liver lesions. In the differentiation of these lesions, CT and MRI have increasingly found their way into primary diagnostic steps in everyday clinical practice. Contrast-enhanced sonography, on the other hand, is a very effective and cost-efficient method for assessing focal liver lesions. The success of the method is not only based on the visualisation of microvascularisation in real time. If sonography is performed by the treating physician, he can use the exact knowledge of history and clinical findings to specifically adapt the examination procedure and to interpret the sonographic findings with greater accuracy ("clinical sonography"). At the same time, the method enables the practitioner to combine diagnostics and management decisions in his or her own hands. To achieve excellent results with contrast-enhanced sonography-as with any other imaging method-it is necessary that the examiner is sufficiently qualified.This article systematically presents the sonographic characteristics of the most common liver lesions and clearly shows their contrast patterns using videos (available via QR code). The article illustrates that CEUS could-and from the authors' point of view, should-have an even greater significance in the future.

To investigate the consistency of LI-RADS of CEUS and EOB-MRI in the categorization of liver nodules ≤2cm in patients at high risk for HCC.

Patients at high risk for HCC with nodules ≤2cm who underwent CEUS and EOB-MRI in our hospital were prospectively enrolled. The CEUS images and EOB-MRI imaging of each liver nodule were observed to evaluate inter-observer consistency and category according to CEUS LI-RADS V2017 and CT/MRI LI-RADS V2017 criteria double blinded. Pathology and/or follow-up were used as reference standard.

A total of 127 nodules in 119 patients met the inclusion criteria. The inter-observer agreement was good on CEUS and EOB-MRI LI-RADS (kappa = 0.76, 0.76 p < 0.001). The inter-modality agreement was fair (kappa=0.21, p < 0.001). There was no statistical difference in PPV and specificity between CEUS and EOB-MRI LR-5 for HCC, while the difference in AUC was statistically significant. We used new criteria (CEUS LR-5 and EOB-MRI LR-4/5 or CEUS LR-4/5 and EOB-MRI LR-5) to diagnose HCC. The sensitivity, specificity, and AUC of this criteria was 63.4%, 95.6%, and 0.80.

CEUS and EOB-MRI showed fair inter-modality agreement in LI-RADS categorization of nodules ≤2 cm. The inter-observer agreement of CEUS and EOB-MRI LI-RADS were substantial. CEUS and EOB-MRI LR-5 have equally good positive predictive value and specificity for HCC ≤ 2cm, and combining these two modalities may better diagnose HCC ≤ 2 cm.

https://clinicaltrials.gov/, identifier NCT04212286.

To develop a contrast-enhanced ultrasound (CEUS) clinic-radiomics nomogram for individualized assessment of Ki-67 expression in hepatocellular carcinoma (HCC).

A retrospective cohort comprising 310 HCC individuals who underwent preoperative CEUS (using SonoVue) at three different centers was partitioned into a training set, a validation set, and an external test set. Radiomics signatures indicating the phenotypes of the Ki-67 were extracted from multiphase CEUS images. The radiomics score (Rad-score) was calculated accordingly after feature selection and the radiomics model was constructed. A clinic-radiomics nomogram was established utilizing multiphase CEUS Rad-score and clinical risk factors. A clinical model only incorporated clinical factors was also developed for comparison. Regarding clinical utility, calibration, and discrimination, the predictive efficiency of the clinic-radiomics nomogram was evaluated.

Seven radiomics signatures from multiphase CEUS images were selected to calculate the Rad-score. The clinic-radiomics nomogram, comprising the Rad-score and clinical risk factors, indicated a good calibration and demonstrated a better discriminatory capacity compared to the clinical model (AUCs: 0.870 vs 0.797, 0.872 vs 0.755, 0.856 vs 0.749 in the training, validation, and external test set, respectively) and the radiomics model (AUCs: 0.870 vs 0.752, 0.872 vs 0.733, 0.856 vs 0.729 in the training, validation, and external test set, respectively). Furthermore, both the clinical impact curve and the decision curve analysis displayed good clinical application of the nomogram.

The clinic-radiomics nomogram constructed from multiphase CEUS images and clinical risk parameters can distinguish Ki-67 expression in HCC patients and offer useful insights to guide subsequent personalized treatment.

The American College of Radiology Liver Imaging Reporting and Data System (LI-RADS) standardizes the imaging technique, reporting lexicon, disease categorization, and management for patients with or at risk for hepatocellular carcinoma (HCC). LI-RADS encompasses HCC surveillance with US; HCC diagnosis with CT, MRI, or contrast-enhanced US (CEUS); and treatment response assessment (TRA) with CT or MRI. LI-RADS was recently expanded to include CEUS TRA after nonradiation locoregional therapy or surgical resection. This report provides an overview of LI-RADS CEUS Nonradiation TRA v2024, including a lexicon of imaging findings, techniques, and imaging criteria for posttreatment tumor viability assessment. LI-RADS CEUS Nonradiation TRA v2024 takes into consideration differences in the CEUS appearance of viable tumor and posttreatment changes within and in close proximity to a treated lesion. Due to the high sensitivity of CEUS to vascular flow, posttreatment reactive changes commonly manifest as areas of abnormal perilesional enhancement without washout, especially in the first 3 months after treatment. To improve the accuracy of CEUS for nonradiation TRA, different diagnostic criteria are used to evaluate tumor viability within and outside of the treated lesion margin. Broader criteria for intralesional enhancement increase sensitivity for tumor viability detection. Stricter criteria for perilesional enhancement limit miscategorization of posttreatment reactive changes as viable tumor. Finally, the TRA algorithm reconciles intralesional and perilesional tumor viability assessment and assigns a single LI-RADS treatment response (LR-TR) category: LR-TR nonviable, LR-TR equivocal, or LR-TR viable.

The aim of the work described here was to explore a potential method for improving the diagnostic detection of hepatocellular carcinoma (HCC) based on the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) Version 2017.

We retrospectively evaluated 585 liver nodules in 427 patients at risk for HCC from December 2020 to March 2023. The nodules were categorized as LR-1 to LR-M based on CEUS LI-RADS Version 2017 and were randomly subclassified into a developmental cohort (DC) and a validation cohort (VC) at 3:1. In the DC, the cutoff value of the time difference (∆T) for differentiating HCC from other malignancies by LR-M was calculated and used to reclassify nodules in the VC. The diagnostic effect on HCC detection before and after reclassification was further assessed.

According to the current CEUS LI-RADS, 140 of 426 (32.9%) confirmed HCC nodules were misclassified as LR-M. In the DC (439 nodules), the receiver operating characteristic (ROC) curve revealed that the cutoff value of ∆T (wash-out onset time minus contrast arrival time) recommended for HCC diagnosis was greater than 21 s. In the VC (146 nodules), 34 HCCs were correctly categorized as LR-5 according to the cutoff value, and after reclassification, LR-5 had higher accuracy (67.1% vs. 89.0%, p < 0.001) and sensitivity (56.0% vs. 87.2%, p < 0.001) for HCC diagnosis with high specificity (100% vs. 94.6%, p = 0.500).

Using the time difference method could identify HCC nodules misdiagnosed as LR-M and improve the diagnostic performance of current CEUS LI-RADS.

Reporting contrast-enhanced ultrasound (CEUS) for focal liver masses in at risk patients is a challenging task. Traditionally used prose reporting (PR) is inconsistent and lacks standardization. We propose synoptic reporting (SR), encompassing algorithmic interpretation and liver imaging and reporting data system (LI-RADS) categorization.

A software worksheet from Kailo Medical (Melbourne, AU), incorporates the CEUS algorithm for liver interpretation and CEUS LI-RADS categorization. Part 1. Feasibility of SR: twenty participants of varying experience were presented a brief lecture on SR, algorithmic approach to liver mass interpretation, and CEUS LI-RADS categorization. Ten representative liver masses were shown as unknown cases. Participants inputted data into SR worksheets. Results and LI-RADS category were generated solely by SR. Data were categorized as "correct" or "incorrect." Part 2. Prospective Analysis: Ninety-one patients for SR and 56 for PR, all were tested for completeness, efficiency, and user satisfaction.

Part 1: Junior participants, pass rate 81.6%, and senior participants, pass rate 83.3% showed no difference in performance. Part 2: Completeness: SR 98.4% and PR 87.0%. Efficiency: Average total time to completion: SR 11 minutes and PR 20 minutes. User satisfaction: Ultrasound technologists, all referring physicians, and six out of seven radiologists preferred SR over PR. Major benefits cited were total time saved, consistency and accuracy in documentation, and report completeness.

SR is a reliable and useful tool in clinical practice to report liver masses on ultrasound and assign an appropriate LI-RADS categorization and management pathway. This ultimately improves communication with referring clinicians and leads to better patient outcomes.

Screening ultrasound for hepatocellular carcinoma (HCC) identifies lesions which require further characterization by a contrast-enhanced exam to non-invasively diagnose HCC. While ultrasound is recommended in screening, some HCC can be occult on grayscale imaging. The purpose of this study was to determine if the addition of ultrasound contrast (sulfahexafluoride) to screening ultrasound for HCC can identify more HCC lesions than grayscale sonographic imaging alone.

All HCC screening ultrasounds that also had contrast were evaluated in this retrospective study. Patients with a focal lesion seen only after administration of contrast (OAC) were noted, as well as any follow-up imaging or pathology results. Additional variables collected included patient demographics, cirrhosis type, and laboratory values.

230 unique patients were included, of which 160 had imaging or pathology follow-up. 18 of these patients had an OAC lesion, of which 17 had follow-up. Among these OACs, there was one LIRADS M lesion (1/18, 5.6 %) and one bland portal vein thrombus identified, which were both confirmed on follow-up imaging. All LIRADS 4 OAC lesions were downgraded. No additional HCC were identified on follow-up imaging or pathology of these patients.

Addition of contrast to screening ultrasound did identify additional lesions, portal vein thrombus, and high grade malignancy. However, as the incidence of OAC lesions was low (7.8 %, 18/230) and most of the lesions were not malignant, addition of post contrast sweeps through the liver is of low value in the low to medium at-risk cirrhotic population in identifying occult HCC.

To identify the risk factors for predicting the malignant progression of LR-3/4 observations on the baseline and contrast-enhanced ultrasound (CEUS).

In total, 245 liver nodules assigned to LR-3/4 in 192 patients from January 2010 to December 2016 were followed up by baseline US and CEUS. The differences in the rate and time of progression to hepatocellular carcinoma (HCC) among subcategories (defined as P1-P7) of LR-3/4 in CEUS Liver Imaging Reporting and Data System (LI-RADS) were analyzed. The risk factors to predict progression to HCC were analyzed by univariate and multivariate Cox proportional hazard model analysis.

A total of 40.3% of LR-3 nodules and 78.9% of LR-4 nodules eventually progressed to HCC. The cumulative incidence of progression was significantly higher for LR-4 than LR-3 (p < 0.001). The rate of progression was 81.2% in nodules with arterial phase hyperenhancement (APHE), 64.7% in nodules with late and mild washout, and 100% in nodules with both characteristics. The overall progression rate and median progression time of subcategory P1 nodules (LR-3a) were lower (38.0% vs. 47.6-100.0%) and later (25.1 months vs. 2.0-16.3 months) than those of other subcategories. The cumulative incidence of progression of LR-3a (P1), LR-3b (P2/3/4), and LR-4 (P5/6/7) categories were 38.0%, 52.9%, and 78.9%. The risk factors of HCC progression were Visualization score B/C, CEUS characteristics (APHE, washout), LR-4 classification, echo changes, and definite growth.

CEUS is a useful surveillance tool for nodules at risk of HCC. CEUS characteristics, LI-RADS classification, and changes in nodules provide useful information for the progress of LR-3/4 nodules.

CEUS characteristics, LI-RADS classification, and nodule changes provide important predictions for LR-3/4 nodule progression to HCC, which may stratify the risk of malignant progression to provide a more optimized and refined, more cost-effective, and time-efficient management strategy for patients.

• CEUS is a useful surveillance tool for nodules at risk of HCC, CEUS LI-RADS successfully stratified the risks that progress to HCC. • CEUS characteristics, LI-RADS classification, and changes in nodules can provide important information on the progression of LR-3/4 nodules, which may be helpful for a more optimized and refined management strategy.

The high proportion of HCC in CEUS LR-M decreases the sensitivity of LR-5 for the diagnosis of HCC. However, when modifying LR-M criteria to further improve the sensitivity of LR-5, it is also important not to compromise the diagnostic performance (especially sensitivity) of LR-M for non-hepatocellular carcinoma malignancies (non-HCCMs). The purpose of this study was to evaluate the diagnostic performance of CEUS LI-RADS (2017 version) for non-HCCMs and to explore the impact of modified CEUS LI-RADS on the diagnostic performance of LR-M.

In this retrospective study, patients with pathologically confirmed non-HCCMs were evaluated. Two radiologists independently interpreted the major CEUS features and categorized the liver lesions. New LR-M criteria were applied: early washout (< 45 s) or marked washout (< 5 min). The sensitivity values of the current and modified CEUS LR-M were assessed and then compared using a paired χ2 test. Cohen's κ was used to compare the inter-reader agreement of the LI-RADS categories.

A total of 131 non-HCCMs were ultimately selected, including 71 intrahepatic cholangiocarcinomas, 26 combined hepatocellular cholangiocarcinomas, 29 metastases, and 5 other non-HCCMs. The numbers of LR-M, LR-5, LR-4, and LR-3 in liver lesions were 111, 18, 1, and 1, respectively. The inter-reader agreement of the LI-RADS categories for non-HCCMs was 0.59. The sensitivity of the current CEUS LR-M in diagnosing non-HCCMs was 84.7%. By adjusting the early washout time to < 45 s, the sensitivity of LR-M was 80.9%. By adjusting the marked washout time within 5 min, the sensitivity of LR-M was 72.5%.

CEUS LR-M has high sensitivity in diagnosing non-HCCMs. For LR-M nodules with nonrim arterial phase hyperenhancement and early washout, advancing the time of early washout to < 45 s has a minimal impact on the sensitivity of LR-M in diagnosing non-HCCMs compared to the condition of increasing the marked washout within 5 min.

In high-BMI patients with and without fatty liver, we evaluate performance of a commercially available specially designed ultrasound probe (SDP) for scanning at depth. Greyscale and contrast-enhanced ultrasound (CEUS) capability of SDP for parenchymal assessment and liver mass characterization, emphasizing HCC, is compared with standard curvilinear probes.

This retrospective study included 60 patients. Fifty-five with measured BMI included 46/55 (84%) overweight or obese, and 9/55(16%) in the normal range with severe fatty liver. Fifty-six patients with focal liver abnormality included 37 with a mass and 19 with post-ablative treatment site. Masses included 23 confirmed malignancies, 15 HCC, 4 ICC, and 4 metastases. SDP followed suboptimal ultrasound using a standard probe. Images with varying fat content were compared for depth of penetration on greyscale and ability of CEUS to diagnose tumors.

SDP showed statistically significant improvement P = <.05 in CEUS penetration for all degrees of fatty liver (mild, moderate, and severe). In malignant tumors, SDP improved detection of lesion washout in the portal venous/late phase (PVP/LP) at depth >10 cm, and in all malignant masses (P < .05). Fifteen confirmed deep HCC showed arterial phase hyperenhancement on standard probe in 10/15 (67%) and 15/15 (100%) on SDP. PVP/LP washout on standard probe was shown in 4/15 (26%) and on SDP, 14/15, (93%). Therefore, 93% of LR-5 tumors were diagnosed with SDP. Removing necessity for biopsy.

Metabolic syndrome and obesity challenge ultrasound, especially CEUS. SDP overcame limitations of standard probes for CEUS penetration especially in fatty liver. SDP was optimal for the liver mass characterization by detecting washout.

Recent advances in the field of ultrasonography offer promising tools for the evaluation of liver tumors. We aim to assess the value of multimodal ultrasound in differentiating hepatocellular carcinomas (HCCs) from other liver lesions. We prospectively included 66 patients with 72 liver tumors. The histological analysis was the reference standard for the diagnosis of malignant liver lesions, and partially for benign tumors. All liver lesions were assessed by multiparametric ultrasound: standard ultrasound, contrast-enhanced ultrasound (CEUS), the point shear wave elastography (pSWE) using shear wave measurement (SWM) method and real-time tissue elastography (RTE). To diagnose HCCs, CEUS achieved a sensitivity, specificity, accuracy and positive predictive value (PPV) of 69.05%, 92.86%, 78.57% and 93.55%, respectively. The mean shear-wave velocity (Vs) value in HCCs was 1.59 ± 0.29 m/s, which was lower than non-HCC malignancies (p < 0.05). Using a cut-off value of 1.58 m/s, SWM achieved a sensitivity of 54.76%, and 82.35% specificity, for differentiating HCCs from other malignant lesions. The combination of SWM and CEUS showed higher sensitivity (79.55%) compared with each technique alone, while maintaining a high specificity (89.29%). In RTE, most HCCs (61.53%) had a mosaic pattern with dominant blue areas corresponding to type "c" elasticity. Elasticity type "c" was 70.59% predictive for HCCs. In conclusion, combining B-mode ultrasound, CEUS, pSWE and RTE can provide complementary diagnostic information and potentially decrease the requirements for other imaging modalities.

To assess the diagnostic performance of the contrast-enhanced ultrasound liver imaging reporting and data system (CEUS LI-RADS) version 2017 for small hepatic lesions of ≤3 cm before and after changing the LR-M criteria.

We retrospectively analyzed the CEUS examination of 179 patients who were at high risk of hepatocellular carcinoma (HCC) with focal hepatic lesions ≤3 cm (194 lesions in total) and evaluated the diagnostic capability of the American College of Radiology and modified CEUS LI-RADS algorithms.

Revision of the early washout time to 45 seconds increased the sensitivity of LR-5 in predicting HCC (P = .004), with no significant decrease in specificity (P = .118). It also made better the specificity of LR-M in predicting non-HCC malignancies (P = .001), with no significant decrease in sensitivity (P = .094). However, using within 3 minutes as the criterion for marked washout time improved the LR-5 sensitivity (P < .001) but decreased its specificity (P = .009) in predicting HCC, whereas the specificity of LR-M in predicting non-HCC malignancies increased (P < .001), but the sensitivity decreased (P = .027).

CEUS LI-RADS (v2017) is a valid method for predicting HCC risk in high-risk patients. The diagnostic performance of LR-5 and LR-M could boost when the early washout time is revised to 45 seconds.

Contrast-enhanced ultrasonography (CEUS) is a noninvasive imaging modality used to diagnose hepatocellular carcinoma (HCC) based on specific imaging features, without the need for pathologic confirmation. Two types of ultrasound contrast agents are commercially available: pure intravascular agents (such as SonoVue) and Kupffer agents (such as Sonazoid). Major guidelines recognize CEUS as a reliable imaging method for HCC diagnosis, although they differ depending on the contrast agents used. The Korean Liver Cancer Association-National Cancer Center guideline includes CEUS with either SonoVue or Sonazoid as a second-line diagnostic technique. However, Sonazoid-enhanced ultrasound is associated with several unresolved issues. This review provides a comparative overview of these contrast agents regarding pharmacokinetic features, examination protocols, diagnostic criteria for HCC, and potential applications in the HCC diagnostic algorithm.

To compare the inter-modality consistency and diagnostic performances of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) and contrast-enhanced computed tomography (CECT) LI-RADS in patients at risk for hepatocellular carcinoma (HCC), so as to help clinicians to select a more appropriate modality to follow the focal liver lesions (FLLs).

This retrospective study included untreated 277 FLLs from 247 patients who underwent both CEUS and CECT within 1 month. The ultrasound contrast medium used was SonoVue. FLL categories were independently assigned by two ultrasound physicians and two radiologists using CEUS LI-RADS v2017 and CECT LI-RADS v2018, respectively. The diagnostic performances of CEUS and CECT LI-RADS were evaluated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value. Cohen's Kappa was employed to evaluate the concordance of the LI-RADS category.

The inter-modality consistency for CEUS and CECT LI-RADS was 0.31 (p < 0.001). HCC was more frequently observed in CECT LR-3 and LR-4 hepatic lesions than in CEUS (7.3% vs. 19.5%, p < 0.001). The specificity and PPV of CEUS and CECT LR-5 for the diagnosis of HCC were 89.5%, 95.0%, and 82.5%, 94.4%, respectively. The sensitivity of CEUS LR-5 + LR-M for the diagnosis of hepatic malignancies was higher than that of CECT (93.7% vs. 82.7%, p < 0.001). The specificity and PPV of CEUS LR-M for the diagnosis of non-HCC malignancies were lower than those of CECT (59.7% vs. 95.5%, p < 0.001; 23.4% vs. 70.3%, p < 0.001).

The inter-modality consistency between the CEUS and CECT LI-RADS categories is fair. CEUS LI-RADS was more sensitive than CECT LI-RADS in terms of identifying hepatic malignancies, but weaker in terms of separating HCC from non-HCC malignancies.

The purpose of this study is to establish microvascular invasion (MVI) prediction models based on preoperative contrast-enhanced ultrasound (CEUS) and ethoxybenzyl-enhanced magnetic resonance imaging (EOB-MRI) in patients with a single hepatocellular carcinoma (HCC) ≤ 5 cm.

Patients with a single HCC ≤ 5 cm and accepting CEUS and EOB-MRI before surgery were enrolled in this study. Totally, 85 patients were randomly divided into the training and validation cohorts in a ratio of 7:3. Non-radiomics imaging features, the CEUS and EOB-MRI radiomics scores were extracted from the arterial phase, portal phase and delayed phase images of CEUS and the hepatobiliary phase images of EOB-MRI. Different MVI predicting models based on CEUS and EOB-MRI were constructed and their predictive values were evaluated.

Since univariate analysis revealed that arterial peritumoral enhancement on the CEUS image, CEUS radiomics score, and EOB-MRI radiomics score were significantly associated with MVI, three prediction models, namely the CEUS model, the EOB-MRI model, and the CEUS-EOB model, were developed. In the validation cohort, the areas under the receiver operating characteristic curve of the CEUS model, the EOB-MRI model, and the CEUS-EOB model were 0.73, 0.79, and 0.86, respectively.

Radiomics scores based on CEUS and EOB-MRI, combined with arterial peritumoral enhancement on CEUS, show a satisfying performance of MVI predicting. There was no significant difference in the efficacy of MVI risk evaluation between radiomics models based on CEUS and EOB-MRI in patients with a single HCC ≤ 5 cm.

Radiomics models based on CEUS and EOB-MRI are effective for MVI predicting and conducive to pretreatment decision-making in patients with a single HCC within 5 cm.

• Radiomics scores based on CEUS and EOB-MRI, combined with arterial peritumoral enhancement on CEUS, show a satisfying performance of MVI predicting. • There was no significant difference in the efficacy of MVI risk evaluation between radiomics models based on CEUS and EOB-MRI in patients with a single HCC ≤ 5 cm.

Cirrhosis is the end stage of chronic liver disease and causes architectural distortion and perfusional anomalies. It is a major risk factor for developing hepatocellular carcinoma (HCC). Common disease entities in noncirrhotic livers, such as hemangiomas, can be rare in cirrhotic livers, and benign entities such as confluent hepatic fibrosis and focal nodular hyperplasia-like lesions may mimic the appearance of malignancies,. HCC usually has typical imaging characteristics, such as the major features established by the Liver Imaging Reporting and Data System. However, HCC can also have a spectrum of atypical or uncommon appearances, such as cystic HCC, hypovascular HCC, or macroscopic fat-containing HCC. HCCs with certain genetic mutations such as CTNNB-1-mutated HCC can harbor unique imaging features not seen in other types of HCC. In addition, malignancies that are less common than HCC, such as cholangiocarcinoma and metastases, which can be difficult to differentiate, can still occur in cirrhotic livers. Atypical imaging features of benign and malignant lesions can be challenging to accurately diagnose. Therefore, familiarity with these features and an understanding of the prevalence of disease entities in cirrhotic livers are key in the daily practice of radiologists for evaluation of cirrhotic livers. The authors illustrate the typical and atypical features of benign and malignant lesions in cirrhosis and discuss the technical pitfalls and unique advantages associated with various imaging modalities in assessing cirrhotic livers, including noncontrast and contrast-enhanced US, CT, and MRI. Work of the U.S. Government published under an exclusive license with the RSNA. Quiz questions for this article are available in the supplemental material.

For the treatment of tumor hypoxia, microbubbles comprising oxygen as a majority component of the gas core with a stabilizing shell may be used to deliver and release oxygen locally at the tumor site through ultrasound destruction. Previous work has revealed differences in circulation half-life in vivo for perfluorocarbon-filled microbubbles, typically used as ultrasound imaging contrast agents, as a function of anesthetic carrier gas. These differences in circulation time in vivo were likely due to gas diffusion as a function of anesthetic carrier gas, among other variables. This work has motivated studies to evaluate the effect of anesthetic carrier gas on oxygen microbubble circulation dynamics.

Circulation time for oxygen microbubbles was derived from ultrasound image intensity obtained during longitudinal kidney imaging. Studies were constructed for rats anesthetized on inhaled isoflurane with either pure oxygen or medical air as the anesthetic carrier gas.

Results indicated that oxygen microbubbles were highly visible via contrast-specific imaging. Marked signal enhancement and duration differences were observed between animals breathing air and oxygen. Perhaps counterintuitively, oxygen microbubbles disappeared from circulation significantly faster when the animals were breathing pure oxygen compared with medical air. This may be explained by nitrogen counterdiffusion from blood into the bubble, effectively changing the gas composition of the core, as has been observed in perfluorocarbon core microbubbles.

Our findings suggest that the apparent longevity and persistence of oxygen microbubbles in circulation may not be reflective of oxygen delivery when the animal is anesthetized breathing air.

Contrast-enhanced ultrasound (CEUS) is a promising imaging modality in predicting the efficacy of neoadjuvant chemotherapy for pancreatic cancer, a tumor with high mortality. In this study, we proposed a deep-learning-based strategy for analyzing CEUS videos to predict the prognosis of pancreatic cancer neoadjuvant chemotherapy. Pre-trained convolutional neural network (CNN) models were used for binary classification of the chemotherapy as effective or ineffective, with CEUS videos collected before chemotherapy as the model input, and with the efficacy after chemotherapy as the reference standard. We proposed two deep learning models. The first CNN model used videos of ultrasound (US) and CEUS (US+CEUS), while the second CNN model only used videos of selected regions of interest (ROIs) within CEUS (CEUS-ROI). A total of 38 patients with strict restriction of clinical factors were enrolled, with 76 original CEUS videos collected. After data augmentation, 760 and 720 videos were included for the two CNN models, respectively. Seventy-six-fold and 72-fold cross-validations were performed to validate the classification performance of the two CNN models. The areas under the curve were 0.892 and 0.908 for the two models. The accuracy, recall, precision and F1 score were 0.829, 0.759, 0.786, and 0.772 for the first model. Those were 0.864, 0.930, 0.866, and 0.897 for the second model. A total of 38.2% and 40.3% of the original videos could be clearly distinguished by the deep learning models when the naked eye made an inaccurate classification. This study is the first to demonstrate the feasibility and potential of deep learning models based on pre-chemotherapy CEUS videos in predicting the efficacy of neoadjuvant chemotherapy for pancreas cancer.

A differentiation between hepatocellular carcinoma (HCC) and benign liver lesions is required. The aim of the study was to perform an analysis of the time of enhancement of focal liver lesions in a contrast-enhanced ultrasound (CEUS) examination. The curves of enhancement and the homogeneity of the tumor enhancement were assessed. The study included 52 patients with diagnoses of hepatocellular adenoma (18), focal nodular hyperplasia (11) and HCC (28). The study included magnetic resonance imaging or computed tomography and a comparison of the obtained information with CEUS. In the benign lesions groups after 20-30 s, the enhancement was similar to the liver parenchyma. In the HCC group, the enhancement was slightly less intense compared to the liver parenchyma and the benign lesions. The difference of the enhancement in the arterial phase (benign lesions vs. HCC) was p = 0.0452, and the difference of enhancement in the late venous phase (benign lesions vs. HCC) was p = 0.000003. The homogeneity of the enhancement (benign lesions vs. HCC), respectively, was p = 0.001 in the arterial phase, p = 0.0003 in the portal venous phase and p = 0.00000007 in the late venous phase. Liver tumors can be classified as benign when they are homogenous in the arterial phase and don't present washout. HCC in the arterial phase is inhomogeneous and washout is observed in the venous phases. When radiological symptoms suggest malignant lesion, CEUS can be used to select the best biopsy access.

Sonazoid, a second-generation ultrasound contrast agent, was introduced for the diagnosis of hepatic nodules. To clarify the issues with Sonazoid contrast-enhanced ultrasonography for the diagnosis of hepatocellular carcinoma (HCC), the Korean Society of Radiology and Korean Society of Abdominal Radiology collaborated on the guidelines. The guidelines are de novo, evidence-based, and selected using an electronic voting system for consensus. These include imaging protocols, diagnostic criteria for HCC, diagnostic value for lesions that are inconclusive on other imaging results, differentiation from non-HCC malignancies, surveillance of HCC, and treatment response after locoregional and systemic treatment for HCC.

Hepatocellular carcinoma (HCC) incidence and mortality continue to rise worldwide. Society guidelines recommend HCC screening for patients with chronic hepatitis B (CHB) or cirrhosis. Unfortunately, HCC screening rates remain relatively low, and the performance characteristics of current screening modalities are suboptimal.

The aim of the study was to discuss the current state of HCC screening and imaging diagnosis utilising standard and emerging imaging modalities in addition to outlining areas of need and ongoing study.

A review of the field was performed combining literature searches and expert opinion.

The development of the Liver Imaging Reporting and Data System (LI-RADS version 2018) algorithms have advanced and standardised the imaging diagnosis of HCC. While guidelines recommend US for HCC screening, the sensitivity of ultrasound is highly variable for the detection of early-stage HCC with sensitivity reports ranging from 40% to 80%. Biomarker-based scores such as GALAD and alternative imaging modalities such as abbreviated MRI are promising tools to improve HCC early detection. Patients with non-alcoholic fatty liver disease (NAFLD) and patients hepatitis C (HCV) who have achieved sustained virologic response (SVR) can present a clinical dilemma regarding the need for HCC screening. Biomarkers and elastography can aid in identification of individuals at high risk for HCC in these populations.

The LI-RADS system has standardised the imaging interpretation and diagnosis of HCC. Work remains regarding screening in special populations and optimization of screening modalities.

The World Federation for Ultrasound in Medicine and Biology (WFUMB) is addressing the issue of incidental findings (IFs) with a series of publications entitled "Incidental imaging findings-the role of ultrasound". IFs in the liver of newborns and children are rare and much less commonly encountered than in adults; as a result, they are relatively much more frequently malignant and life-threatening, even when they are of benign histology. Conventional B-mode ultrasound is the well-established first line imaging modality for the assessment of liver pathology in pediatric patients. US technological advances, resulting in image quality improvement, contrast-enhanced ultrasound (CEUS), liver elastography and quantification tools for steatosis have expanded the use of ultrasound technology in daily practice. The following overview is intended to illustrate incidentally detected liver pathology covering all pediatric ages. It aims to aid the examiner in establishing the final diagnosis. Management of incidentally detected focal liver lesions (FLL) needs to take into account the diagnostic accuracy of each imaging modality, the patient's safety issues (including ionizing radiation and nephrotoxic contrast agents), the delay in diagnosis, the psychological burden on the patient and the cost for the healthcare system. Moreover, this paper should help the pediatric clinician and ultrasound practitioner to decide which pathologies need no further investigation, which ones require interval imaging and which cases require further and immediate diagnostic procedures.

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer, being the third most common cause of cancer-related death globally. HCC most frequently develops in the context of hepatic cirrhosis. HCC can manifest as various morphologic subtypes. Each pattern exhibits distinct behaviors in terms of imaging features, disease progression, response to therapy, and prognosis. While the nodular pattern is the most frequent subtype, infiltrative HCC is the least prevalent and makes up about 8%-20% of all HCC cases. Infiltrative HCC manifests as small tumor nodules that often spread across the entire liver or across a hepatic segment/lobe and is not identified as a focal tumor. On ultrasonography, infiltrative HCC presents as a markedly heterogeneous area with ill-defined echotexture, making it difficult to distinguish from background hepatic cirrhosis. On magnetic resonance imaging (MRI), infiltrating HCC typically manifests as a mild, poorly defined hepatic region with heterogeneous or homogenous aberrant signal intensity. Specifically, on T1-weighted MRI scans, infiltrating HCC frequently appears as largely hypointense and typically homogenous and mildly to moderately hyperintense on T2-weighted imaging. Infiltrative HCC frequently lacks a clearly defined boundary on cross-sectional imaging and can consequently fade into the background of the cirrhotic liver. As a result, infiltrating HCC is frequently not discovered until an advanced stage and has an associated poor prognosis. Thus, understanding imaging features associated with infiltrative HCC diagnosis is crucial for abdominal radiologists to ensure effective and timely care. We herein review imaging characteristics of infiltrative 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.

Hemoperitoneum in cirrhosis is a life-threatening condition that requires emergent evaluation. Contrast-enhanced ultrasound (CEUS) permits multiple dynamic characterizations of abdominal structures through all vascular phases, and contrast extravasation or the presence of microbubbles in the ascites could be a sensitive tool. We reviewed 13 patients with cirrhosis that underwent CEUS due to high suspicion for intra-abdominal bleeding. In 10 cases, CEUS demonstrated extravasation of contrast, including 2 instances where CEUS detected active bleeding despite negative computed tomography. These data support further study of CEUS in direct comparison to other imaging modalities in this clinical context.