To compare the diagnostic performance of two algorithms for HCC diagnosis: SonoVue-CEUS based on CEUS LI-RADS version 2017 and a modified algorithm incorporating Kupffer-phase findings for Sonazoid-CEUS.

This single center prospective study enrolled high-risk patients for HCC. Each participant underwent SonoVue-CEUS and Sonazoid-CEUS. Each liver observation was assigned two LI-RADS categories according to each algorithm: SonoVue-CEUS LI-RADS and modified Sonazoid-CEUS LI-RADS. For the latter method, observations at least 10 mm with non-rim arterial phase hyperenhancement were upgraded LR-4 to LR-5 if there was no washout with a Kupffer defect and were reassigned LR-M to LR-5 if there was early washout with mild Kupffer defect. The reference standard was pathologic confirmation.

Overall, 66 patients (mean age, 61.2 years ± 10.9; 54 male patients, 12 female patients) with 66 observations (mean size, 31 mm ± 16) were eventually enrolled. The results of Sonazoid-CEUS LI-RADS showed significant changes in sensitivity (82% vs. 65%, p < 0.001), accuracy (85% vs. 71%, p < 0.001) compared with the SonoVue-CEUS LI-RADS. There was no significant difference in specificity (93% vs. 87%, p = 0.26).

When incorporating Kupffer-phase findings, Sonazoid-CEUS LI-RADS had higher sensitivity without loss of specificity compared with SonoVue-CEUS LI-RADS.

Alveolar echinococcosis (AE), caused by the larval stage of the tapeworm Echinococcus multilocularis, is a serious parasitic disease that presents significant health risks and challenges for both patients and healthcare systems. Accurate and timely diagnosis is essential for effective management and improved patient outcomes. This review summarizes the latest diagnostic methods for AE, focusing on serological tests and imaging techniques such as ultrasonography (US), computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography/computed tomography (PET/CT). Each imaging modality has its strengths and limitations in detecting and characterizing AE lesions, such as their location, size, and invasiveness. US is often the first-line method due to its non-invasiveness and cost-effectiveness, but it may have limitations in assessing complex lesions. CT provides detailed anatomical information and is particularly useful for assessing bone involvement and calcification. MRI, with its excellent soft tissue contrast, is superior for delineating the extent of AE lesions and their relationship to adjacent structures. PET/CT combines functional and morphological imaging to provide insights into the metabolic activity of lesions, which is valuable for monitoring treatment response and detecting recurrence. Overall, this review emphasizes the importance of a multifaceted diagnostic approach that combines serological and imaging techniques for accurate and early AE diagnosis, which is crucial for effective management and improved patient outcomes.

Hepatocellular carcinoma (HCC) is characterized by a high mortality rate. The Liver Imaging Reporting and Data System (LI-RADS) results in a considerable number of indeterminate observations, rendering an accurate diagnosis difficult.

We developed four deep learning models for diagnosing HCC on computed tomography (CT) via a training-validation-testing approach. Thin-slice triphasic CT liver images and relevant clinical information were collected and processed for deep learning. HCC was diagnosed and verified via a 12-month clinical composite reference standard. CT observations among at-risk patients were annotated using LI-RADS. Diagnostic performance was assessed by internal validation and independent external testing. We conducted sensitivity analyses of different subgroups, deep learning explainability evaluation, and misclassification analysis.

From 2,832 patients and 4,305 CT observations, the best-performing model was Spatio-Temporal 3D Convolution Network (ST3DCN), achieving area under receiver-operating-characteristic curves (AUCs) of 0.919 (95% CI, 0.903-0.935) and 0.901 (95% CI, 0.879-0.924) at the observation (n = 1,077) and patient (n = 685) levels, respectively during internal validation, compared with 0.839 (95% CI, 0.814-0.864) and 0.822 (95% CI, 0.790-0.853), respectively for standard of care radiological interpretation. The negative predictive values of ST3DCN were 0.966 (95% CI, 0.954-0.979) and 0.951 (95% CI, 0.931-0.971), respectively. The observation-level AUCs among at-risk patients, 2-5-cm observations, and singular portovenous phase analysis of ST3DCN were 0.899 (95% CI, 0.874-0.924), 0.872 (95% CI, 0.838-0.909) and 0.912 (95% CI, 0.895-0.929), respectively. In external testing (551/717 patients/observations), the AUC of ST3DCN was 0.901 (95% CI, 0.877-0.924), which was non-inferior to radiological interpretation (AUC 0.900; 95% CI, 0.877--923).

ST3DCN achieved strong, robust performance for accurate HCC diagnosis on CT. Thus, deep learning can expedite and improve the process of diagnosing HCC.

The clinical applicability of deep learning in HCC diagnosis is potentially huge, especially considering the expected increase in the incidence and mortality of HCC worldwide. Early diagnosis through deep learning can lead to earlier definitive management, particularly for at-risk patients. The model can be broadly deployed for patients undergoing a triphasic contrast CT scan of the liver to reduce the currently high mortality rate of HCC.

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies, which is associated with a low 5-year survival rate. The importance of effective disease monitoring and prognostic evaluation is undeniable. For the present study, a systematic review was performed using extensive searches in Medline, Embase, Web of Science and Scopus up to December 29, 2023. The aim of the present study was to examine whether N-glycomics could predict the risk of developing HCC in adults with chronic liver disease and, if HCC was present, predict overall survival. As a secondary outcome, the prediction capability of HCC recurrence was assessed. After deduplication, 3,904 studies were identified, of which 30 were included. Overall, the median size of the study cohort was 144 patients, with a median follow-up time of 63.6 months. Three studies explored N-glycomics in whole serum, whereas the rest focused on individual glycoproteins, with Mac-2 binding protein glycosylation isomer (M2BPGi) being the most commonly studied. Most articles investigated baseline M2BPGi values as predictors for the development of HCC and demonstrated a median area under the curve of 0.83 with a cut-off index value of 1.8. In conclusion, it was revaled that N-glycan changes exhibit added value in determining patient prognosis in terms of survival, monitoring HCC development and recurrence.

Given the crucial role of imaging in HCC diagnosis, LI-RADS CT/MRI was developed to standardize the imaging interpretation and reporting of HCC in patients at risk for HCC and categorize hepatic observations on an ordinal scale according to the likelihood of HCC. LI-RADS has since been expanded to include 5 algorithms: LI-RADS US Surveillance, contrast-enhanced US (CEUS) LI-RADS, LI-RADS CT/MRI, and LI-RADS Treatment Response Assessment. LI-RADS has been adopted broadly in North America, however with less ubiquitous adoption outside of North America. Further elucidation of the perceived strengths and weakness of the LI-RADS algorithm, as it pertains to various geographic regions, will continue to inform a future system that may be more readily adopted globally. Therefore, the aim of this article is to summarize HCC risk factors and imaging guidelines in select geographically disparate regions, and to solicit feedback from liver imaging experts on the limitations and barriers to adoption of LI-RADS algorithms in their patient populations.

The objective of this study is to build and verify the performance of machine learning-based ultrasomics in predicting the objective response to combination therapy involving a tyrosine kinase inhibitor (TKI) and anti-PD-1 antibody for individuals with unresectable hepatocellular carcinoma (HCC). Radiomic features can reflect the internal heterogeneity of the tumor and changes in its microenvironment. These features are closely related to pathological changes observed in histology, such as cellular necrosis and fibrosis, providing crucial non-invasive biomarkers to predict patient treatment response and prognosis.

Clinical, pathological, and pre-treatment ultrasound image data of 134 patients with recurrent unresectable or advanced HCC who treated with a combination of TKI and anti-PD-1 antibody therapy at Henan Provincial People's Hospital and the First Affiliated Hospital of Zhengzhou University between December 2019 and November 2023 were collected and retrospectively analyzed. Using stratified random sampling, patients from the two hospitals were assigned to training cohort (n = 93) and validation cohort (n = 41) at a 7:3 ratio. After preprocessing the ultrasound images, regions of interest (ROIs) were delineated. Ultrasomic features were extracted from the images for dimensionality reduction and feature selection. By utilizing the extreme gradient boosting (XGBoost) algorithm, three models were developed: a clinical model, an ultrasomic model, and a combined model. By analyzing the area under the receiver operating characteristic (ROC) curve (AUC), specificity, sensitivity, and accuracy, the predicted performance of the models was evaluated. In addition, we identified the optimal cutoff for the radiomic score using the Youden index and applied it to stratify patients. The Kaplan-Meier (KM) survival curves were used to examine differences in progression-free survival (PFS) between the two groups.

Twenty ultrasomic features were selected for the construction of the ultrasomic model. The AUC of the ultrasomic model for the training cohort and validation cohort were 0.999 (95%CI: 0.997-1.000) and 0.828 (95%CI: 0.690-0.966), which compared significant favorably to those of the clinical model [AUC = 0.876 (95%CI: 0.815-0.936) for the training cohort, 0.766 (95%CI: 0.597-0.935) for the validation cohort]. Compared to the ultrasomic model, the combined model demonstrated comparable performance within the training cohort (AUC = 0.977, 95%CI: 0.957-0.998) but higher performance in the validation cohort (AUC = 0.881, 95%CI: 0.758-1.000). However, there was no statistically significant difference (p > 0.05). Furthermore, ultrasomic features were associated with PFS, which was significantly different between patients with radiomic scores (Rad-score) greater than 0.057 and those with Rad-score less than 0.057 in both the training (HR = 0.488, 95% CI: 0.299-0.796, p = 0.003) and validation cohorts (HR = 0.451, 95% CI: 0.229-0.887, p = 0.02).

The ultrasomic features demonstrates excellent performance in accurately predicting the objective response to TKI in combination with anti-PD-1 antibody immunotherapy among patients with unresectable or advanced HCC.

The use of hepatobiliary-specific contrast agents in liver MRI is a crucial diagnostic tool for evaluating liver disease, enabling the detection and characterisation of focal lesions and vascular alterations, as well as the assessment and grading of chronic hepatopathy. Paramagnetic hepatobiliary-specific contrast agents are gadolinium-based, partially taken up by hepatocytes, and excreted via both renal and biliary pathways. There are two linear ionic molecules that are currently commercially available: gadobenic acid (Gd-BOPTA) and gadoxetic acid (Gd-EOB-DTPA). Their main clinical indications include distinguishing and characterising focal liver lesions on healthy liver tissue, diagnosing and staging hepatocellular carcinoma in patients with chronic hepatopathy, and increasing reliability in the detection of hepatic metastases in oncology patients, especially prior to surgery. They are also useful in the evaluation of the biliary tract and in assessing complications of hepatic surgery such as bile leaks.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, and prognosis assessment is crucial for guiding treatment decisions. In this study, we aimed to develop a personalized prognostic model for HCC based on RNA editing. RNA editing is a post-transcriptional process that can affect gene expression and, in some cases, play a role in cancer development. By analyzing RNA editing sites in HCC, we sought to identify a set of sites associated with patient prognosis and use them to create a prognostic model. We gathered RNA editing data from the Synapse database, comprising 9990 RNA editing sites and 250 HCC samples. Additionally, we collected clinical data for 377 HCC patients from the Cancer Genome Atlas (TCGA) database. We employed a multi-step approach to identify prognosis-related RNA editing sites (PR-RNA-ESs). We assessed how patients in the high-risk and low-risk groups, as defined by the model, fared in terms of survival. A nomogram was developed to predict the precise survival prognosis of HCC patients and assessed the prognostic model's utility through a receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Our analysis identified 33 prognosis-related RNA editing sites (PR-RNA-ESs) associated with HCC patient prognosis. Using a combination of LASSO regression and cross-validation, we constructed a prognostic model based on 13 PR-RNA-ESs. Survival analysis demonstrated significant differences in the survival outcomes of patients in the high-risk and low-risk groups defined by this model. Additionally, the differential expression of the 13 PR-RNA-ESs played a role in shaping patient survival. Risk-prognostic investigations further distinguished patients based on their risk levels. The nomogram enabled precise survival prognosis prediction. Our study has successfully developed a highly personalized and accurate prognostic model for individuals with HCC, leveraging RNA editing data. This model has the potential to revolutionize clinical evaluation and medical management by providing individualized prognostic information. The identification of specific RNA editing sites associated with HCC prognosis and their incorporation into a predictive model holds promise for improving the precision of treatment strategies and ultimately enhancing patient outcomes in HCC.

Combined 18F-fluorodeoxyglucose (FDG) and 11C-acetate (dual-tracer) positron-emission tomography/computed tomography (PET/CT) is being increasingly performed for the management of hepatocellular carcinoma (HCC), although its role is not well defined. Therefore, we evaluated its effectiveness in (i) staging, (ii) characterization of indeterminate lesions on conventional imaging, and (iii) detection of HCC in patients with unexplained elevations in serum alpha-fetoprotein (AFP) levels.

We retrospectively assessed 525 consecutive patients from three tertiary centers between 2014 and 2020. For staging, we recorded new lesion detection rates, changes in the Barcelona Clinic Liver Cancer (BCLC) classification, and treatment allocation due to dual-tracer PET/CT. To characterize indeterminate lesions and unexplained elevation of serum AFP levels, the sensitivity and specificity of dual-tracer PET/CT in diagnosing HCC were evaluated. A multidisciplinary external review and a cost-benefit analysis of patients for metastatic screening were also performed.

Dual-tracer PET/CT identified new lesions in 14.3% of 273 staging patients, resulting in BCLC upstaging in 11.7% and treatment modifications in 7.7%. It upstaged 8.1% of 260 patients undergoing metastatic screening, with estimated savings of US$495 per patient. It had a sensitivity and specificity of 80.7% (95% CI 71.2-88.6%) and 94.8% (95% CI 90.4-98.6%), respectively, for diagnosing HCC in 201 indeterminate lesions. It detected HCC in 45.1% of 51 patients with unexplained elevations in serum AFP concentrations. External review revealed substantial agreement between local and external image interpretation and patient assessment (n = 273, κ = 0.822; 95% CI 0.803-0.864).

Dual-tracer PET/CT provides added value beyond conventional imaging in patients with HCC by improving staging, confirming HCC diagnosis with high accuracy in patients with indeterminate lesions, and detecting HCC in patients with unexplained elevation of serum AFP.

Compared to CT or MRI, dual-tracer positron-emission tomography/computed tomography (PET/CT) led to upstaging in 12% of patients with hepatocellular carcinoma (HCC) undergoing staging, resulting in treatment modification in 8% of cases and a cost saving of US$495 per patient. It also accurately detected HCC in high-risk cases where CT or MRI were equivocal or normal. Dual-tracer PET/CT provides added value beyond conventional imaging in patients with HCC by improving staging, confirming HCC diagnosis with high accuracy in patients with indeterminate lesions, and detecting HCC in patients with unexplained elevation of serum AFP.

The GALAD score has improved early hepatocellular carcinoma (HCC) detection rate. The role of the GALAD score in staging and predicting tumor characteristics or clinical outcome of HCC remains of particular interest.

To determine the diagnostic/prognostic performances of the GALAD score at various phases of initial diagnosis, tumor features, and 1-year mortality of HCC and compare the performance of the GALAD score with those of other serum biomarkers.

This prospective, diagnostic/prognostic study was conducted among patients with newly diagnosed HCC at the liver center of Vajira Hospital. Eligible patients had HCC staging allocation using the Barcelona Clinic Liver Cancer (BCLC) categorization. Demographics, HCC etiology, and HCC features were recorded. Biomarkers and the GALAD score were obtained at baseline. The performance of the GALAD score and biomarkers were prospectively assessed.

Exactly 115 individuals were diagnosed with HCC. The GALAD score increased with disease severity. Between BCLC-0/A and BCLC-B/C/D, the GALAD score predicted HCC staging with an area under the curve (AUC) of 0.868 (95%CI: 0.80-0.93). For identifying the curative HCC, the AUC of GALAD score was significantly higher than that of Alpha-fetoprotein (AFP) (0.753) and Lens culinaris agglutinin-reactive fraction of AFP-L3 (0.706), and as good as that of Protein induced by vitamin K absence-II (PIVKA-II) (0.897). For detecting aggressive features, the GALAD score gave an AUC of 0.839 (95%CI: 0.75-0.92) and significantly outperformed compared to that of AFP (0.761) and AFP-L3 (0.697), with a trend of superiority to that of PIVKA-II (0.772). The performance to predict 1-year mortality of GALAD score (AUC: 0.711, 95%CI: 0.60-0.82) was better than that of AFP (0.541) and as good as that of PIVKA-II (0.736). The optimal cutoff value of GALAD score was ≥ 6.83, with a specificity of 72.63% for exhibiting substantial reduction in the 1-year mortality.

The GALAD model can diagnose HCC at the curative stage, including the characteristic of advanced disease, more than that by AFP and AFP-L3, but not PIVKA-II. The GALAD score can be used to predict the 1-year mortality of HCC.

To retrospectively explored whether systematic training in the use of Liver Imaging Reporting and Data System (LI-RADS) v2018 on computed tomography (CT) can improve the interobserver agreements and performances in LR categorization for focal liver lesions (FLLs) among different radiologists.

A total of 18 visiting radiologists and the liver multiphase CT images of 70 hepatic observations in 63 patients at high risk of HCC were included in this study. The LI-RADS v2018 training procedure included three thematic lectures, with an interval of 1 month. After each seminar, the radiologists had 1 month to adopt the algorithm into their daily work. The interobserver agreements and performances in LR categorization for FLLs among the radiologists before and after training were compared.

After training, the interobserver agreements in classifying the LR categories for all radiologists were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.053). After systematic training, the areas under the curve (AUCs) for LR categorization performance for all participants were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.062).

Systematic training in the use of the LI-RADS can improve the interobserver agreements and performances in LR categorization for FLLs among radiologists with different levels of experience.

Hepatocellular carcinoma (HCC) can be noninvasively diagnosed through dynamic computed tomography (CT) and magnetic resonance imaging (MRI). We compared the diagnostic performance of CT and gadoxetic acid-enhanced MRI (EOB-MRI) in categorizing tumors by using the 2018 version of the Liver Imaging Reporting And Data System (LI-RADS v2018) and assessing liver tumors before resection.

Data from a prospective cohort from October 2011 to March 2019 on 106 hepatic tumors in 96 patients with suspected malignancy were included in this study. We performed preoperative CT and EOB-MRI, and reviewed these images retrospectively. Ninety-seven tumors from 87 patients were pathologically diagnosed as HCC, and nine tumors were non-HCC. The clinical data, imaging characteristics, diagnostic performance, and outcomes of CT and EOB-MRI were analyzed and compared.

EOB-MRI had more favorable diagnostic performance (area under curve: 0.920 vs. 0.868) and significantly higher sensitivity (86.87% vs. 69.70%, p = 0.005) than did CT. However, the specificity of EOB-MRI did not differ from that of CT (88.89% vs. 88.89%, p > 0.999). Fourteen (14.5%) patients with pathologically verified HCC had lesions categorized as LI-RADS 4 through CT and as LI-RADS 5 through EOB-MRI. Patients with EOB-MRI-categorized but not CT-categorized LI-RADS 5 lesions had significantly longer overall survival than did those with LI-RADS 4 lesions (p < 0.001).

EOB-MRI had higher sensitivity than did CT in diagnosing HCC. Patients with EOB-MRI-categorized LI-RADS 5 lesions had more favorable outcomes than did those with LI-RADS 4 lesions after liver resection.

Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based denoising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstruction (MBIR). Materials and Methods In this prospective, multicenter, noninferiority study, individuals referred for liver CT scans were enrolled from three tertiary referral hospitals between February 2021 and August 2022. All liver CT scans were conducted using a dual-source scanner with the dose split into tubes A (67% dose) and B (33% dose). Blended images from tubes A and B were created using MBIR to produce SDCT images, whereas LDCT images used data from tube B and were reconstructed with DLD. The noise in liver images was measured and compared between imaging techniques. The diagnostic performance of each technique in detecting malignant liver tumors was evaluated by three independent radiologists using jackknife alternative free-response receiver operating characteristic analysis. Noninferiority of LDCT compared with SDCT was declared when the lower limit of the 95% CI for the difference in figure of merit (FOM) was greater than -0.10. Results A total of 296 participants (196 men, 100 women; mean age, 60.5 years ± 13.3 [SD]) were included. The mean noise level in the liver was significantly lower for LDCT (10.1) compared with SDCT (10.7) (P < .001). Diagnostic performance was assessed in 246 participants (108 malignant tumors in 90 participants). The reader-averaged FOM was 0.880 for SDCT and 0.875 for LDCT (P = .35). The difference fell within the noninferiority margin (difference, -0.005 [95% CI: -0.024, 0.012]). Conclusion Compared with SDCT with MBIR, LDCT using 33% of the standard radiation dose had reduced image noise and comparable diagnostic performance in detecting malignant liver tumors. Keywords: CT, Abdomen/GI, Liver, Comparative Studies, Diagnosis, Reconstruction Algorithms Clinical trial registration no. NCT05804799 © RSNA, 2024 Supplemental material is available for this article.

Stress granules (SGs) as membrane-less cytoplasmic foci formed in response to unfavorable external stimuli could promote cancer cells to adapt to hostile environments. Hepatocellular carcinoma (HCC) is prone to be highly aggressive once diagnosed, which markedly reduces patient survival time. Therefore, it is crucial to develop valid diagnostic markers to prognosticate HCC patient prognosis, which promotes individualized precision therapeutics in HCC. Considering the pro-tumorigenic activity of SGs, it is of great potential value to construct a prognostic tool for HCC based on the expression profiles of SG-related genes (SGGs).

Bioinformatic analysis was employed to establish an SGG-based prognostic signature. Western blotting and real-time polymerase chain reaction assays were used to assess the expression patterns of the related SGGs. Loss-of-function experiments were performed to analyze the effect of the SGGs on SG formation and cell survival.

A four-SGG signature (KPNA2, MEX3A, WDR62, and SFN) targeting HCC was established and validated to exhibit a robust performance in predicting HCC prognosis. Consistently, all four genes were further found to be highly expressed in human HCC tissues. More important, we demonstrated that individually knocking down the four SGGs significantly reduced HCC cell proliferation and metastasis by compromising the SG formation process.

We developed an SGG-based predictive signature that can be used as an independent prognostic tool for HCC. The strong predictive power of this signature was further elucidated by the carcinogenic activity of KPNA2, MEX3A, WDR62, and SFN in HCC cells by regulating SG formation.

To evaluate the diagnostic performance for hepatocellular carcinoma (HCC) detection of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 on gadoxetic acid-enhanced MRI, comparing liver transplant candidates (LT group) with patients who underwent surgical resection (SR group), and to determine significant clinical factors for diagnostic performance of LI-RADS v2018.

Patients who underwent gadoxetic acid-enhanced MRI and subsequent SR or LT for HCC were retrospectively included between January 2019 and December 2020. The sensitivity and specificity of LI-RADS LR-5 for HCC were compared between the two groups using generalized estimating equations. The accuracy of patient allocation according to the Milan criteria was calculated for the LT group. Univariable and multivariable logistic regression analyses were performed to determine significant clinical factors associated with the sensitivity of LI-RADS.

Of the 281 patients, 237 were assigned to the SR group, and 44 were assigned to the LT group. The LT group showed significantly lower per-patient (48.5% vs. 79.6%, p < .001) and per-lesion sensitivity (31.0% vs. 75.9%, p < .001) than the SR group, whereas no significant difference in both per-patient (100.0% vs. 91.7%, p > .99) and per-lesion specificities (100.0% vs. 94.1%, p > .99). The accuracy of patient allocation was 50.0%. Sensitivity was significantly lower in patients with a smaller lesion size (p < .001), a larger lesion number (p = .002), and a higher Child-Pugh score (p = .009).

LI-RADS v2018 on gadoxetic acid-enhanced MRI might be insufficient in liver transplant candidates and other diagnostic imaging tests should be considered in patients with these significant clinical factors.

In liver transplant candidates with a smaller lesion size, a larger lesion number, and a higher Child-Pugh score, imaging tests other than gadoxetic acid-enhanced MRI may be clinically useful to determine the transplant eligibility.

• The sensitivity of the Liver Imaging Reporting and Data System (LI-RADS) was lower in liver transplant candidates than in those who underwent surgical resection. • With the use of gadoxetic acid-enhanced MRI, the accuracy of patient allocation for liver transplantation on the basis of the Milan criteria was suboptimal. • The sensitivity of LI-RADS v2018 was significantly associated with lesion size, lesion number, and Child-Pugh classification.

To develop a risk stratification based on MRI features to predict hypervascular transformation for hepatobiliary-phase (HBP) hypointense nodules without arterial-phase hyperenhancement (APHE).

This retrospective observational cohort study included 55 HBP hypointense nodules without APHE in 35 patients with chronic liver disease, cirrhosis, or current hepatocellular carcinoma (HCC) who underwent gadoxetic acid-enhanced MRI. The hypervascular transformation during the follow-up MRI(s) was the primary endpoint analyzed for the nodules. Univariable and multivariable Cox proportional hazard regression analyses were performed to identify risk features predicting transformation and assess their predictive value.

Among the 55 nodules, 27 developed hypervascular transformation, while 28 did not. Diffusion-weighted imaging (DWI) hyperintensity (hazard ratio [HR], 4.98; 95% confidence interval [CI]: 1.60, 15.54; p = 0.006) and portal venous phase (PVP) hypointensity (HR, 4.08; 95% CI: 1.43, 11.64; p = 0.009) were associated with hypervascular transformation. DWI hyperintensity and PVP hypointensity had 44.4% (95% CI: 26.0%, 64.4%) and 81.9% (95% CI: 61.3%, 93.0%) sensitivity, while their specificity was 78.2% (95% CI: 64.6%, 87.8%) and 67.9 (95% CI: 47.6%, 83.4%), respectively. The specificity of the combination of two features was 100% (95% CI: 85.0%, 100%). The hypervascular transformation rates for nodules with both, either and neither of the risk MRI findings were 100% (10/10), 60.9% (14/23), and 13.6% (3/22), respectively; the median intervals for transformation were 312 (range: 73-838), 409 (range: 50-1643) and 555 (range: 423-968) days, respectively.

The combination of DWI hyperintensity and PVP hypointensity may be used as a high-risk indicator for the hypervascular transformation of HBP hypointense nodules without APHE; nodules without either feature may be treated as low-risk nodules and could adopt an extended interval follow-up schedule.

BACKGROUND AND OBJECTIVE: The role of threshold growth, as one of the major features (MFs) of hepatocellular carcinoma (HCC) in the Liver Imaging Reporting and Data System (LI-RADS) is inconsistent. This study evaluated the LI-RADS diagnostic performance for HCC when threshold growth was removed or replaced by independently significant ancillary features (AFs). MATERIALS AND METHODS: This retrospective institutional review board-approved study included patients with a high HCC risk who underwent gadoxetic acid-enhanced MRIs. The MRI findings were consistent with pathologically proven focal hepatic observations. The pathological results were used as the gold standard reference. The sizes of the lesions with and without threshold growth were compared. Univariate and multivariate logistic regression analyses were used to confirm the independently significant AFs of HCC. In addition to the classification criteria of LI-RADS version 2018 (LI-RADS v2018), the lesions were also reclassified according to the following two schemes: scheme A, using all MFs except threshold growth, with threshold growth feature treated as an AF favouring malignancy; and scheme B, replacing the threshold growth feature with independently significant AFs and treated them as new MFs. The diagnostic performance of the above two LI-RADS schemes for HCC was calculated and compared with that of LI-RADS v2018. RESULTS: A total of 379 patients and 426 observations were included. Threshold growth was not an independent significant MF for HCC diagnosis [odds ratio (OR), 1.0; 95% confidence interval (CI), 0.6-1.8; p = 0.927]. For all three groups of observations (HCCs, non-HCC malignancies, and benign lesions), the mean size with threshold growth was smaller than that without threshold growth (all p < 0.05). The nodule-in-nodule feature was an independent significant AF (OR, 9.8; 95% CI, 1.2-79.3; p = 0.032) and was used to replace threshold growth as a new MF in scheme B. The sensitivities of schemes A and B were 74.0% and 75.6%, respectively. The specificities of schemes A and B were the same (88.6%). None of the diagnostic performance metrics for HCC (sensitivity, specificity, accuracy) of either scheme A or B was significantly different from those of LI-RADS v2018 (all p > 0.05). CONCLUSION: Threshold growth is not an independently significant MF for HCC diagnosis. The diagnostic performance of LI-RADS for HCC is not affected regardless of whether threshold growth is removed from the list of MFs or replaced with an independently significant and more HCC-specific AF, which is the nodule-in-nodule feature.

Image-based detection of intralesional fat in focal liver lesions has been established in diagnostic guidelines as a feature indicative of hepatocellular carcinoma (HCC) and associated with a favorable prognosis. Given recent advances in MRI-based fat quantification techniques, we investigated a possible relationship between intralesional fat content and histologic tumor grade in steatotic HCCs.

Patients with histopathologically confirmed HCC and prior MRI with proton density fat fraction (PDFF) mapping were retrospectively identified. Intralesional fat of HCCs was assessed using an ROI-based analysis and the median fat fraction of steatotic HCCs was compared between tumor grades G1-3 with non-parametric testing. ROC analysis was performed in case of statistically significant differences (p < 0.05). Subgroup analyses were conducted for patients with/without liver steatosis and with/without liver cirrhosis.

A total of 57 patients with steatotic HCCs (62 lesions) were eligible for analysis. The median fat fraction was significantly higher for G1 lesions (median [interquartile range], 7.9% [6.0─10.7%]) than for G2 (4.4% [3.2─6.6%]; p = .001) and G3 lesions (4.7% [2.8─7.8%]; p = .036). PDFF was a good discriminator between G1 and G2/3 lesions (AUC .81; cut-off 5.8%, sensitivity 83%, specificity 68%) with comparable results in patients with liver cirrhosis. In patients with liver steatosis, intralesional fat content was higher than in the overall sample, with PDFF performing better in distinguishing between G1 and G2/3 lesions (AUC .92; cut-off 8.8%, sensitivity 83%, specificity 91%).

Quantification of intralesional fat using MRI PDFF mapping allows distinction between well- and less-differentiated steatotic HCCs.

PDFF mapping may help optimize precision medicine as a tool for tumor grade assessment in steatotic HCCs. Further investigation of intratumoral fat content as a potential prognostic indicator of treatment response is encouraged.

• MRI proton density fat fraction mapping enables distinction between well- (G1) and less- (G2 and G3) differentiated steatotic hepatocellular carcinomas. • In a retrospective single-center study with 62 histologically proven steatotic hepatocellular carcinomas, G1 tumors showed a higher intralesional fat content than G2 and G3 tumors (7.9% vs. 4.4% and 4.7%; p = .004). • In liver steatosis, MRI proton density fat fraction mapping was an even better discriminator between G1 and G2/G3 steatotic hepatocellular carcinomas.

Hepatocellular carcinoma (HCC) can be diagnosed without pathologic confirmation in high-risk patients. Therefore, it is necessary to compare current imaging criteria for noninvasive-diagnosis of HCC.

To systematically compare performance of 2018 European Association for the Study of the Liver (EASL) criteria and Liver Imaging Reporting and Data System (LI-RADS) for noninvasive-diagnosis of HCC.

Systematic review and meta-analysis.

Eight studies with 2232 observations, including 1617 HCCs.

1.5 T, 3.0 T/T2-weighted, unenhanced T1-weighted in-/opposed-phases, multiphase T1-weighted imaging.

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers independently reviewed and extracted data, including patient characteristics, index test, reference standard and outcomes, from studies intraindividually comparing the sensitivities and specificities of 2018 EASL-criteria and LR-5 of LI-RADS for HCC. Risk of bias and concerns regarding applicability were evaluated using QUADAS-2 tool. Subgroup analysis was performed based on observation size (≥20 mm, 10-19 mm).

Bivariate random-effects model to calculate pooled per-observation sensitivity and specificity of both imaging criteria, and pooled estimates of intraindividual paired data were compared considering the correlation. Forest and linked-receiver-operating-characteristic plots were drawn, and study heterogeneity was assessed using Q-test and Higgins-index. Publication bias was evaluated by Egger's test. A P-value <0.05 was considered statistically significant, except for heterogeneity (P < 0.10).

The sensitivity for HCC did not differ significantly between the imaging-based diagnosis using EASL-criteria (61%; 95% CI, 50%-73%) and LR-5 (64%; 95% CI, 53%-76%; P = 0.165). The specificities were also not significantly different between EASL-criteria (92%; 95% CI, 89%-94%) and LR-5 (94%; 95% CI, 91%-96%; P = 0.257). In subgroup analysis, no statistically significant differences were identified in the pooled performances between the two criteria for observations ≥20 mm (sensitivity P = 0.065; specificity P = 0.343) or 10-19 mm (sensitivity P > 0.999; specificity P = 0.851). There was no publication bias for EASL (P = 0.396) and LI-RADS (P = 0.526).

In the present meta-analysis of paired comparisons, the pooled sensitivities and specificities were not significantly different between 2018 EASL-criteria and LR-5 of LI-RADS for noninvasive-diagnosis of HCC.

3.

Stage 2.

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.

Gadoxetic disodium (Primovist) is a hepatocyte-specific magnetic resonance imaging (MRI) contrast agent with increasing popularity with its unique dual dynamic and excretory properties in focal liver lesion detection and characterisation. In-depth knowledge of its diagnostic utility and pitfalls in hepatocellular carcinoma (HCC) and liver metastases is crucial in facilitating clinical management. The current article reviews the pearls and pitfalls in these aspects with highlights from the latest research evidence. Pearls for common usage of Primovist in HCC includes detection of precursor cancer lesions in cirrhotic patients. Hepatobiliary phase hypointensity precedes arterial phase hyperenhancement (APHE) in hepatocarcinogenesis. Hepatobiliary phase hypointense nodules without APHE can represent early or progressed hepatocellular carcinoma (HCC) and high-grade dysplastic nodules. In addition, Primovist is useful to differentiate HCC from pseudolesions. Pitfalls in diagnosing HCC include transient tachypnoea in the arterial phase, rare hepatobiliary phase hyperintense HCC, and decompensated liver cirrhosis compromising image quality. Primovist is currently the most sensitive technique in diagnosing liver metastases before curative hepatic resection. Other patterns of enhancement of liver metastases, "disappearing" liver metastases are important pitfalls. Radiologists should be aware of the diagnostic utility, limitations, and potential pitfalls for the common usage of hepatobiliary specific contrast agent in liver MRI.

The aim of the work described here was to evaluate the diagnostic performance of perfluorobutane (PFB)-enhanced ultrasound in differentiating hepatocellular carcinoma (HCC) from non-HCC malignancies and other benign lesions using different acquisition methods.

This prospective study included 69 patients with solid liver lesions larger than 1 cm who were scheduled for biopsy or radiofrequency ablation between September 2020 and March 2021. Lesion diagnosis was designated by three blinded radiologists after reviewing three different sets of acquired images selected according to the following presumed acquisition methods: (i) method A, acquisition up to 5 min after contrast injection; (ii) method B, acquisition up to 1 min after contrast injection with additional Kupffer phase; and (iii) method C, acquisition up to 5 min after contrast injection with additional Kupffer phase.

After excluding 7 technical failures, 62 patients with liver lesions (mean size: 24.2 ± 14.8 mm), which consisted of 7 benign lesions, 37 non-HCC malignancies and 18 HCCs. For the HCC diagnosis, method C had the highest sensitivity (75.9%), followed by method B (72.2%) and method A (68.5%), but failed to exhibit statistical significance (p = 0.12). There was no significant difference with respect to the pooled specificity between the three methods (p = 0.28). Diagnostic accuracy was the highest with method C (87.1%) but failed to exhibit statistical significance (p = 0.24).

Image acquisition up to 5 min after contrast injection with additional Kupffer phase could potentially result in high accuracy and sensitivity without loss of specificity in diagnosing HCC with PFB-enhanced ultrasound.

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.

The present study aimed to evaluate the influence of biological characteristics of hepatocellular carcinoma (HCC) on the Liver Imaging Reporting and Data System (LI-RADS) v2017 category of contrast-enhanced ultrasound (CEUS) in patients with high risk and compare the outcomes among different categories after radical resection.

Between June 2017 and December 2020, standardized CEUS data of liver nodules were prospectively collected from multiple centers across China. We conducted a retrospective analysis of the prospectively collected data on HCCs measuring no more than 5 cm, as diagnosed by pathology. LI-RADS categories were assigned after thorough evaluation of CEUS features. Then, CEUS LI-RADS categories and major features were compared in different differentiation, Ki-67, and microvascular invasion (MVI) statuses. Differences in recurrence-free survival (RFS) among different LI-RADS categories were further analyzed.

A total of 293 HCC nodules in 293 patients were included. This study revealed significant differences in the CEUS LI-RADS category of HCCs among differentiation (p < 0.001) and levels of Ki-67 (p = 0.01) and that poor differentiation (32.7% in LR-M, 12% in LR-5, and 6.2% in LR-4) (p < 0.001) and high level of Ki-67 (median value 30%) were more frequently classified into the LR-M category, whereas well differentiation (37.5% in LR-4, 15.1% in LR-5, and 11.5% in LR-M) and low levels of Ki-67 (median value 11%) were more frequently classified into the LR-4 category. No significant differences were found between MVI and CEUS LI-RADS categories (p > 0.05). With a median follow-up of 23 months, HCCs assigned to different CEUS LI-RADS classes showed no significant differences in RFS after resection.

Biological characteristics of HCC, including differentiation and level of Ki-67 expression, could influence major features of CEUS and impact the CEUS LI-RADS category. HCCs in different CEUS LI-RADS categories showed no significant differences in RFS after resection.

To explore the potential value of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) magnetic resonance imaging (MRI) in the diagnosis of hepatocellular carcinoma (HCC) in LR-3/4 lesions by adding computed tomography (CT) delayed images based on the Liver Imaging Reporting And Data System (LI-RADS).

The differences in clinical and imaging characteristics between hepatocellular carcinoma and non-HCC were compared, and logistic regression was used to analyze the imaging risk factors for the diagnosis of HCC. Based on the main and HCC-specific auxiliary features of Gd-EOB-DTPA MRI, the HCC diagnostic model 1 was established, and the diagnostic efficacy was analyzed. Based on model 1, delayed phase CT images were added to establish model 2 to find reliable predictors of HCC diagnosis. Receiver operating characteristic (ROC) analysis and the DeLong test were used to compare the two models.

There was a significant difference in serum AFP between HCC and non-HCC (P = 0.008). Based on main and HCC-specific auxiliary features of Gd-EOB-DTPA MRI, enhancing capsule (OR = 0.197, 95% CI = 0.06-0.595, P = 0.005) and washout (OR = 10.345, 95% CI = 3.460-30.930, P < 0.001) were independent risk factors in Model 1. After adding CT delayed-phase images to build model 2, enhancing capsule (OR = 0.132, 95% CI = 0.139-0.449, P = 0.001), MRI and (or) CT washout (OR = 0.052, 95% CI = 0.016-0.172, P < 0.001) were reliable predictors for HCC diagnosis. The AUC of model 1 was 0.808, sensitivity was 63.46%, and specificity was 85.00%. The AUC of model 2 was 0.854, the sensitivity was 71.20%, and the specificity was 85.00%. DeLong test (P = 0.040) demonstrated the diagnostic efficacy of model 2 significantly superior than model 1.

Tumor washout and enhanced capsule are reliable factors for the diagnosis of HCC. Gd-EOB-DTPA MRI with delayed phase CT images can improve the sensitivity and diagnostic efficiency of HCC in LR-3/4 lesions on the premise of maintaining high specificity. Future studies are required to reinforce our finding.

To investigate the ability of ultrasomics to predict Ki-67 expression in hepatocellular carcinoma (HCC).

A total of 244 patients from three hospitals were retrospectively recruited (training dataset, n = 168; test dataset, n = 43; and validation dataset, n = 33). Lesion segmentation of the ultrasound images was performed manually by two radiologists. In total, 1409 ultrasomics features were extracted. Feature selection was conducted using the intra-class correlation coefficient, variance threshold, mutual information, and recursive feature elimination plus eXtreme Gradient Boosting. The support vector machine was combined with the learning curve and grid search parameter tuning to construct the clinical, ultrasomics, and combined models. The predictive performance of the models was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity and accuracy.

The ultrasomics model performed well on the training, test, and validation datasets. The AUC (95% confidence interval [CI]) for these datasets were 0.955 (0.912-0.981), 0.861 (0.721-0.947), and 0.665 (0.480-0.819), respectively. The combination of ultrasomics and clinical features significantly improved model performance on all three datasets. The AUC (95% CI), sensitivity, specificity, and accuracy were 0.986 (0.955-0.998), 0.973, 0.840, and 0.869 on the training dataset; 0.871 (0.734-0.954), 0.750, 0.829, and 0.814 on the test dataset; and 0.742 (0.560-0.878), 0.714, 0.808, and 0.788 on the validation dataset, respectively.

Ultrasomics was proved to be a potential noninvasive method to predict Ki-67 expression in HCC.

Multikinase inhibitors (MKIs) such as sorafenib and lenvatinib are first-line treatments for unresectable hepatocellular carcinoma (HCC) and are known to have immunomodulatory effects. However, predictive biomarkers of MKI treatment in HCC patients need to be elucidated. In the present study, thirty consecutive HCC patients receiving lenvatinib (n = 22) and sorafenib (n = 8) who underwent core-needle biopsy before treatment were enrolled. The associations of CD3, CD68, and programmed cell death-ligand-1 (PD-L1) immunohistochemistry with patient outcomes, including overall survival (OS), progression-free survival (PFS), and objective response rate (ORR), were evaluated. High and low subgroups were determined according to median CD3, CD68, and PD-L1 values. Median CD3 and CD68 counts were 51.0 and 46.0 per 20,000 µm2, respectively. The median combined positivity score (CPS) of PD-L1 was 2.0. Median OS and PFS were 17.6 and 4.4 months, respectively. ORRs of the total, lenvatinib, and sorafenib groups were 33.3% (10/30), 12.5% (1/8), and 40.9% (9/22), respectively. The high CD68+ group had significantly better PFS than the low CD68+ group. The high PD-L1 group had better PFS than the low subgroup. When we analyzed the lenvatinib subgroup, PFS was also significantly better in the high CD68+ and PD-L1 groups. These findings suggest that high numbers of PD-L1-expressing cells within tumor tissue prior to MKI treatment can serve as a biomarker to predict favorable PFS in HCC patients.

Post-hepatectomy liver failure (PHLF) represents the major source of mortality after liver resection (LR) in hepatocellular carcinoma (HCC) patients. Child-Pugh (CP) score 5 is always considered to indicate a normal liver function but represents a heterogeneous population with a considerable number suffering from PHLF. The present study aimed to access the ability of liver stiffness (LS) measured by two-dimensional shear wave elastography (2D-SWE) to predict PHLF in HCC patients with a CP score of 5.

From August 2018 to May 2021, 146 HCC patients with a CP score of 5 who underwent LR were reviewed. The patients were randomly divided into training (n = 97) and validation (n = 49) groups. Logistic analyses were conducted for the risk factors and a linear model was built to predict the development of PHLF. The discrimination and calibration were assessed in the training and validation cohorts by the areas under the receiver operating characteristic curve (AUC).

Analyses revealed that the minimum of LS (Emin) higher than 8.05 (p = 0.006, OR = 4.59) and future liver remnant / estimated total liver volume (FLR/eTLV) (p < 0.001, OR < 0.01) were independent predictors of PHLF in HCC patients with CP score 5, and the AUC calculated by the model based on them for differentiation of PHLF in the training and validation group was 0.78 and 0.76, respectively.

LS was associated with the development of PHLF. A model combining Emin and FLR/eTLV showed proper ability in predicting PHLF in HCC patients with a CP score of 5.

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.

This study aimed to determine the diagnostic performance of 2022 Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) imaging criteria compared with the 2018 KLCA-NCC for hepatocellular carcinoma (HCC) in high-risk patients using magnetic resonance imaging (MRI).

This retrospective study included 415 treatment-naïve patients (152 patients who underwent extracellular contrast agent [ECA]-MRI and 263 who underwent hepatobiliary agent [HBA]-MRI; 535 lesions, including 412 HCCs) with a high risk of HCC who underwent contrast-enhanced MRI. Two readers evaluated all lesions according to the 2018 and 2022 KLCA-NCC imaging diagnostic criteria, and the per-lesion diagnostic performances were compared.

In "definite" HCC category of both 2018 and 2022 KLCA-NCC, HBA-MRI showed a significantly higher sensitivity for the diagnosis of HCC than ECA-MRI (77.0% vs. 64.3%, P=0.006) without a significant difference in specificity (94.7% vs. 95.7%, P=0.801). On ECAMRI, "definite" or "probable" HCC categories of the 2022 KLCA-NCC had significantly higher sensitivity than those of the 2018 KLCA-NCC (85.3% vs. 78.3%, P=0.002) with identical specificity (93.6%). On HBA-MRI, the sensitivity and specificity of "definite" or "probable" HCC categories of both 2018 and 2022 KLCA-NCC were not significantly different (83.3% vs. 83.6%, P>0.999 and 92.1% vs. 90.8%, P>0.999, respectively).

In "definite" HCC category of both 2018 and 2022 KLCA-NCC, HBA-MRI provides better sensitivity than ECA-MRI without compromising specificity. On ECA-MRI, "definite" or "probable" HCC categories of the 2022 KLCA-NCC may improve sensitivity in the diagnosis of HCC compared with the 2018 KLCA-NCC.

To compare the pathologic diagnosis and survival of patients with subcentimeter and 1-2 cm nodules that present with diagnostic hallmarks of hepatocellular carcinoma (HCC).

Diagnostic hallmarks of HCC were defined as hyperintensity on T2 weighted imaging, restricted diffusion, arterial phase hyperenhancement, washout on portal venous phase, and hypointensity on hepatobiliary phase. We retrospectively included 139 patients undergoing curative resection with single nodules ≤2 cm that present imaging features described above on gadoxetic acid-enhanced MRI. The final diagnosis was confirmed by histopathological assessment. Recurrence-free survival (RFS) was compared using Kaplan-Meier analysis with the Log-rank test. Factors associated with overall and early recurrence were identified using Cox regression analysis.

Among 139 nodules (49 nodules <1 cm), there was no significant difference in the percentage of HCC between subcentimeter and 1-2 cm nodules (94.0% vs 94.4%, P > 0.999). Microvascular invasion (MVI) was less common in subcentimeter HCC (4.3% vs 17.6%, P = 0.032). There were 27 recurrences during a median follow-up time of 46.7 months. Patients with subcentimeter HCC achieved less recurrence, with a 5-year RFS rate of 87.3%. The MVI-positive patients had more early and overall recurrence. A tumor size <1 cm was associated with lower overall recurrence (HR, 0.336; P = 0.047). No factors were independently associated with early recurrence.

Subcentimeter nodules with diagnostic hallmarks of HCC are highly associated with HCC diagnosis and achieve less tumor recurrence after resection. Early diagnosis and treatment of subcentimeter HCC may be more appropriate.

 The Liver Imaging Reporting and Data System (LI-RADS v2018) standardizes the interpretation and reporting of MDCT and MRI examinations in patients at risk for hepatocellular carcinoma (HCC).

 For focal liver lesions (called "observations") it assigns categories (LR-1 to 5, LR-M, LR-TIV, LR-TR), which reflect the probability of benignity or malignancy (HCC or other non-HCC malignancies) of the respective observation. The categories assigned are based on major and ancillary image features, which have been developed by the American College of Radiology (ACR), revised several times (now v2018), and validated in many studies. The value of ancillary features to modify LI-RADS categories assigned to observations based on major features is shown.

 This review summarizes the relevant CT and MRI features and presents a step-by-step approach for readers not familiar with LI-RADS on how to use the system. Relevant imaging features and the value of different modalities (contrast-enhanced CT, MRI with extracellular gadolinium chelates or liver-specific contrast agents) is explained.

 The widespread adoption of LI-RADS for CT/MRI reporting in high-risk patients would help to reduce inter-reader variability. It could improve communication between radiologists, oncologists, hepatologists, pathologists, and liver surgeons, and lead to better patient management.

  · LI-RADS has been developed and revised to address the need for improved diagnosis and standardized categorization of findings in chronic liver disease.. · CT/MRI LI-RADS consists of major criteria and ancillary features to classify observations.. · LI-RADS terminology helps to clarify the communication of liver observations between radiologists and referring physicians..

· Schima W, Kopf H, Eisenhuber E. LI-RADS made Easy. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1990-5924.

To investigate added value of late portal venous phase (LPVP) for identification of enhancing capsule (EC) on gadoxetate disodium-enhanced MRI (GD-MRI) for diagnosing hepatocellular carcinoma (HCC) in patients with chronic liver disease (CLD).

This retrospective study comprised 116 high-risk patients with 128 pathologically proven HCCs who underwent GD-MRI including arterial phase, conventional portal venous phase (CPVP, 60 s), LPVP (mean, 104.4 ± 6.7 s; range, 90-119 s), and transitional phase (TP, 3 min). Two independent radiologists assessed the presence of major HCC features, including EC on CPVP and/or TP (CPVP/TP) and EC on LPVP. The frequency of EC was compared on GD-MRI between with and without inclusion of LPVP. The radiologists assigned Liver Imaging Reporting and Data System (LI-RADS) v2018 categories before and after identifying EC on LPVP.

Of the total 128 HCCs, 74 and 73 revealed EC on CPVP/TP for reviewer 1 and 2, respectively. After inclusion of LPVP, each reviewer identified seven more EC [Reviewer 1, 57.8% (74/128) vs. 63.3% (81/128); Reviewer 2, 57.0% (73/128) vs. 62.5% (80/128); P = 0.016, respectively]. Sensitivities of LR-5 assignment for diagnosing HCCs were not significantly different in GD-MRI with or without LPVP for EC identification [Reviewer 1, 71.9% (92/128) vs. 72.7% (93/128); Reviewer 2, 75.0% (96/128) vs. 75.8% (97/128); P = 1.000, respectively].

Including the LPVP in GD-MRI may improve identification of EC of HCC in patients with CLD. However, LI-RADS v2018 using GD-MRI showed comparable sensitivity for diagnosing HCC regardless of applying LPVP for EC.

To investigate the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) features on the pathologic grade, microvascular invasion (MVI), and cytokeratin-19 (CK19) expression in hepatocellular carcinomas (HCC), and to evaluate their association with postoperative recurrence of HCC.

This retrospective study included 147 patients with surgically confirmed HCCs who underwent gadoxetic-enhanced MRI. The lesions were evaluated quantitatively in terms of the relative enhancement ratio (RER), and qualitatively based on imaging features and clinical parameters. Logistic regression analyses were performed to investigate the value of these parameters in predicting the pathologic grade, MVI, and CK19 in HCC. Predictive factors for postoperative recurrence were determined using a Cox proportional hazards model.

Peritumoral enhancement (odds ratio [OR], 3.396; p = 0.025) was an independent predictor of high pathologic grades. Serum protein induced by vitamin K absence or antagonist (PIVKA) level > 40 mAU/mL (OR, 3.763; p = 0.018) and peritumoral hypointensity (OR, 4.343; p = 0.003) were independent predictors of MVI. Predictors of CK19 included serum alpha-fetoprotein (AFP) level > 400 ng/mL (OR, 4.576; p = 0.005), rim enhancement (OR, 5.493; p = 0.024), and lower RER (OR, 0.013; p = 0.011). Peritumoral hypointensity (hazard ratio [HR], 1.957; p = 0.027) and poor pathologic grades (HR, 2.339; p = 0.043) were independent predictors of recurrence.

We demonstrated the value of preoperative gadoxetic-enhanced MRI in predicting aggressive pathological features of HCC. Poor pathologic grades and peritumoral hypointensity may independently predict the recurrence of HCC.