CT and MRI Liver Imaging Reporting and Data System Version 2018 for Hepatocellular Carcinoma: A Systematic Review With Meta-Analysis

Do Risk Factors for HCC Impact the Association of CT/MRI LIRADS Major Features With HCC? An Individual Participant Data Meta-Analysis

Background: Guidelines suggest the Liver Imaging Reporting and Data System (LI-RADS) may not be applicable for some populations at risk for hepatocellular carcinoma (HCC). However, data assessing the association of HCC risk factors with LI-RADS major features are lacking. Purpose: To evaluate whether the association between HCC risk factors and each CT/MRI LI-RADS major feature differs among individuals at-risk for HCC. Methods: Databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched from 2014 to 2022. Individual participant data (IPD) were extracted from studies evaluating HCC diagnosis using CT/MRI LI-RADS and reporting HCC risk factors. IPD from studies were pooled and modelled with one-stage meta-regressions. Interactions were assessed between major features and HCC risk factors, including age, sex, cirrhosis, chronic hepatitis B virus (HBV), and study location. A mixed effects model that included the major features, as well as separate models that included interactions between each risk factor and each major feature, were fit. Differences in interactions across levels of each risk factor were calculated using adjusted odds-ratios (ORs), 95% confidence-intervals (CI), and z-tests. Risk of bias was assessed using QUADAS-2. (Protocol: https://osf.io/tdv7j/). Results: Across 23 studies (2958 patients and 3553 observations), the associations between LI-RADS major features and HCC were consistent across several HCC risk factors (P-value range: .09-.99). A sensitivity analysis among the 4 studies with a low risk of bias did not differ from the primary analysis. Conclusion: The association between CT/MRI LI-RADS major features and HCC risk factors do not significantly differ in individuals at-risk for HCC. These findings suggest that CT/MR LI-RADS should be applied to all patients considered at risk by LI-RADS without modification or exclusions, regardless of the presence or absence of the risk factors evaluated in this study.

LI-RADS in 2024: recent updates, planned refinements, and future directions

Initially released in 2011, liver imaging reporting and data (LI-RADS) CT/MRI diagnostic algorithm categorizes hepatic observations on an ordinal scale based on the probability of hepatocellular carcinoma, malignancy, or benignity, and guides reproducible interpretation, clear communication, and standardized terminology for liver imaging. LI-RADS has significantly expanded in scope in the past decade, with the inclusion of algorithms that address screening and surveillance, diagnosis with contrast enhanced ultrasound (CEUS), and treatment response assessment with both CEUS and CT/MRI. LI-RADS algorithms undergo periodic refinements based on accumulating scientific evidence, user feedback, and technological advancements. This manuscript discusses recent LI-RADS algorithm refinements, planned updates, with a focus on LI-RADS CT/MRI diagnostic algorithm, and future goals.

Performance of LI-RADS category 5 vs combined categories 4 and 5: a systemic review and meta-analysis

OBJECTIVE

Computed tomography (CT)/magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS, LR) category 5 has high specificity and modest sensitivity for diagnosis of hepatocellular carcinoma (HCC). The purpose of this study was to compare the diagnostic performance of LR-5 vs combined LR-4 and LR-5 (LR-4/5) for HCC diagnosis.

METHODS

MEDLINE and EMBASE databases through January 03, 2023 were searched for studies reporting the performance of LR-5 and combined LR-4/5 for HCC diagnosis, using CT/MRI LI-RADS version 2014, 2017, or 2018. A bivariate random-effects model was used to calculate the pooled per-observation diagnostic performance. Subgroup analysis was performed based on imaging modalities and type of MRI contrast material.

RESULTS

Sixty-nine studies (15,108 observations, 9928 (65.7%) HCCs) were included. Compared to LR-5, combined LR-4/5 showed significantly higher pooled sensitivity (83.0% (95% CI [80.3-85.8%]) vs 65.7% (95% CI [62.4-69.1%]); p < 0.001), lower pooled specificity (75.0% (95% CI [70.5-79.6%]) vs 91.7% (95% CI [90.2-93.1%]); p < 0.001), lower pooled positive likelihood ratio (3.60 (95% CI [3.06-4.23]) vs 6.18 (95% CI [5.35-7.14]); p < 0.001), and lower pooled negative likelihood ratio (0.22 (95% CI [0.19-0.25]) vs 0.38 (95% CI [0.35-0.41]) vs; p < 0.001). Similar results were seen in all subgroups.

CONCLUSIONS

Our meta-analysis showed that combining LR-4 and LR-5 would increase sensitivity but decrease specificity, positive likelihood ratio, and negative likelihood ratio. These findings may inform management guidelines and individualized management.

CLINICAL RELEVANCE STATEMENT

This meta-analysis estimated the magnitude of changes in the sensitivity and specificity of imaging criteria when LI-RADS categories 4 and 5 were combined; these findings can inform management guidelines and individualized management.

KEY POINTS

There is no single worldwide reporting system for liver imaging, partly due to regional needs. Combining LI-RADS categories 4 and 5 increased sensitivity and decreased specificity and positive and negative likelihood ratios. Changes in the sensitivity and specificity of imaging criteria can inform management guidelines and individualized management.

State-of-the-art imaging of hepatocellular carcinoma

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

Comparative Performance of 2018 LI-RADS versus Modified LIRADS (mLI-RADS): An Individual Participant Data Meta-Analysis

BACKGROUND

LI-RADS version 2018 (v2018) is used for non-invasive diagnosis of hepatocellular carcinoma (HCC). A recently proposed modification (known as mLI-RADS) demonstrated improved sensitivity while maintaining specificity and positive predictive value (PPV) of LI-RADS category 5 (definite HCC) for HCC. However, mLI-RADS requires multicenter validation.

PURPOSE

To evaluate the performance of v2018 and mLI-RADS for liver lesions in a large, heterogeneous, multi-national cohort of patients at risk for HCC.

STUDY TYPE

Systematic review and meta-analysis using individual participant data (IPD) [Study Protocol: https://osf.io/duys4].

POPULATION

2223 observations from 1817 patients (includes all LI-RADS categories; females = 448, males = 1361, not reported = 8) at elevated risk for developing HCC (based on LI-RADS population criteria) from 12 retrospective studies.

FIELD STRENGTH/SEQUENCE

1.5T and 3T; complete liver MRI with gadoxetate disodium, including axial T2w images and dynamic axial fat-suppressed T1w images precontrast and in the arterial, portal venous, transitional, and hepatobiliary phases. Diffusion-weighted imaging was used when available.

ASSESSMENT

Liver observations were categorized using v2018 and mLI-RADS. The diagnostic performance of each system's category 5 (LR-5 and mLR-5) for HCC were compared.

STATISTICAL TESTS

The Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2 was applied to determine risk of bias and applicability. Diagnostic performances were assessed using the likelihood ratio test for sensitivity and specificity and the Wald test for PPV. The significance level was P < 0.05.

RESULTS

17% (2/12) of the studies were considered low risk of bias (244 liver observations; 164 patients). When compared to v2018, mLR-5 demonstrated higher sensitivity (61.3% vs. 46.5%, P < 0.001), similar PPV (85.3% vs. 86.3%, P = 0.89), and similar specificity (85.8% vs. 90.8%, P = 0.16) for HCC.

DATA CONCLUSION

This study confirms mLR-5 has higher sensitivity than LR-5 for HCC identification, while maintaining similar PPV and specificity, validating the mLI-RADS proposal in a heterogeneous, international cohort.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Artificial intelligence in liver cancer - new tools for research and patient management

Liver cancer has high incidence and mortality globally. Artificial intelligence (AI) has advanced rapidly, influencing cancer care. AI systems are already approved for clinical use in some tumour types (for example, colorectal cancer screening). Crucially, research demonstrates that AI can analyse histopathology, radiology and natural language in liver cancer, and can replace manual tasks and access hidden information in routinely available clinical data. However, for liver cancer, few of these applications have translated into large-scale clinical trials or clinically approved products. Here, we advocate for the incorporation of AI in all stages of liver cancer management. We present a taxonomy of AI approaches in liver cancer, highlighting areas with academic and commercial potential, and outline a policy for AI-based liver cancer management, including interdisciplinary training of researchers, clinicians and patients. The potential of AI in liver cancer is immense, but effort is required to ensure that AI can fulfil expectations.

Liver Imaging Reporting and Data System version 2018 category 5 for diagnosing hepatocellular carcinoma: an updated meta-analysis

OBJECTIVE

We performed an updated meta-analysis to determine the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS, LR) 5 category for hepatocellular carcinoma (HCC) using LI-RADS version 2018 (v2018), and to evaluate differences by imaging modalities and type of MRI contrast material.

METHODS

The MEDLINE and Embase databases were searched for studies reporting the performance of LR-5 using v2018 for diagnosing HCC. A bivariate random-effects model was used to calculate the pooled per-observation sensitivity and specificity. Subgroup analysis was performed based on imaging modalities and type of MRI contrast material.

RESULTS

Forty-eight studies qualified for the meta-analysis, comprising 9031 patients, 10,547 observations, and 7216 HCCs. The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC were 66% (95% CI, 61-70%) and 91% (95% CI, 89-93%), respectively. In the subgroup analysis, MRI with extracellular agent (ECA-MRI) showed significantly higher pooled sensitivity (77% [95% CI, 70-82%]) than CT (66% [95% CI, 58-73%]; p = 0.023) or MRI with gadoxetate (Gx-MRI) (65% [95% CI, 60-70%]; p = 0.001), but there was no significant difference between ECA-MRI and MRI with gadobenate (gadobenate-MRI) (73% [95% CI, 61-82%]; p = 0.495). Pooled specificities were 88% (95% CI, 80-93%) for CT, 92% (95% CI, 86-95%) for ECA-MRI, 93% (95% CI, 91-95%) for Gx-MRI, and 91% (95% CI, 84-95%) for gadobenate-MRI without significant differences (p = 0.084-0.803).

CONCLUSIONS

LI-RADS v2018 LR-5 provides high specificity for HCC diagnosis regardless of modality or contrast material, while ECA-MRI showed higher sensitivity than CT or Gx-MRI.

CLINICAL RELEVANCE STATEMENT

Refinement of the criteria for improving sensitivity while maintaining high specificity of LR-5 for HCC diagnosis may be an essential future direction.

KEY POINTS

• The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC using LI-RADSv2018 were 66% and 91%, respectively. • ECA-MRI showed higher sensitivity than CT (77% vs 66%, p = 0.023) or Gx-MRI (77% vs 65%, p = 0.001). • LI-RADS v2018 LR-5 provides high specificity (88-93%) for HCC diagnosis regardless of modality or contrast material type.

Based on Gadolinium Ethoxybenzyl DTPA-Enhanced MRI: Diagnostic Performance of the Category-Modified LR-5 Criteria in Patients At Risk for Hepatocellular Carcinoma

Introduction: We aimed to modify the LR-5 strategy to improve the diagnostic sensitivity for hepatocellular carcinoma (HCC) in high-risk patients while maintaining specificity. Methods: This study retrospectively analyzed 412 patients with 445 liver observations who underwent preoperative gadolinium ethoxybenzyl DTPA (GD-EOB-DTPA)-enhanced MRI followed by surgical procedures or biopsies. All observations were classified according to LI-RADS v2018, and the classifications were adjusted by modifying major features (MF)(substituting threshold growth with a more HCC-specific ancillary features (AF): presence of blood products within the mass, arterial phase hyperenhancement (APHE) was interpreted with hypointensity on precontrast imaging- isointensity in arterial phase (AP) and extending washout to transitional phase (TP)(2 min)). The specificity, sensitivity, and positive predictive value (PPV) were assessed to compare LR-5 (definitely HCC) diagnostic efficacy between LI-RADS version 2018 and modified LI-RADS. Results: Apart from nonenhancing "capsule", the interreader agreement of MFs and HCC-specific AFs between the two readers reached substantial or excellent ranges (κ values ranging from 0.631 to 0.911). According to LI-5 v2018, the specificity, sensitivity and PPV of HCC were 90.74%, 82.35%, and 98.17%, respectively. Based on a more HCC-specific AF, signal intensity in AP and TP (2 min), the sensitivity of the three modified strategies were 86.19%, 93.09%, 96.67% (P < .05)), while maintaining high specificity and PPV rates at 88.89% and 98.25% (P > .05) Conclusion: Further investigation into the efficacy of threshold growth as a MF is warranted. By utilizing GD-EOB-DTPA-enhanced MRI, enhancing the sensitivity of the modified LR-5 category may be achieved without compromising specificity and PPV in diagnosing HCC among high-risk patients.

Diagnostic performance of magnetic resonance imaging and contrast-enhanced ultrasound in differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma: a meta-analysis

PURPOSE

To compare the diagnostic ability between magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS) in distinguishing intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC).

METHODS

Original studies reporting the diagnostic accuracy of MRI and CEUS in differentiating ICC from HCC were identified in PubMed and EMBASE databases. Histopathological examination was used as the reference standard for tumor diagnosis. Study quality was assessed using QUADAS-2 scale. Data were extracted to calculate the pooled diagnostic sensitivity, specificity, and diagnostic odds ratio (DOR) using a bivariate random-effects model, as well as the area under the curve (AUC). Sensitivity analysis, subgroup analysis, meta-regression, and investigation of publication bias were also performed.

RESULTS

A total of 26 studies with 28 data subsets (18 on MRI, 10 on CEUS) were included, consisting of 4169 patients with 1422 ICC lesions and 2747 HCC lesions. Most MRI studies were performed at 3T with hepatobiliary agents, and most CEUS studies used SonoVue as the contrast agent. In MRI, the pooled sensitivity, specificity, DOR, and AUC in distinguishing ICC from HCC were 0.81 (0.79, 0.84), 0.90 (0.88, 0.91), 41.47 (24.07, 71.44), and 0.93 (0.90, 0.96), respectively. The pooled sensitivity, specificity, DOR, and AUC of CEUS were 0.88 (0.84, 0.90), 0.80 (0.78, 0.83), 42.06 (12.38, 133.23), and 0.93 (0.87, 0.99), respectively. Subgroup analysis and meta-regression analysis demonstrated significant heterogeneity among the studies associated with the type of contrast agent in MRI studies. No publication bias was found.

CONCLUSION

Both MRI and CEUS showed excellent diagnostic performance in differentiating ICC from HCC. CEUS showed higher pooled sensitivity and MRI showed higher pooled specificity.

Diagnostic Performance of the 2018 EASL vs. LI-RADS for Hepatocellular Carcinoma Using CT and MRI: A Systematic Review and Meta-Analysis of Comparative Studies

BACKGROUND

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.

PURPOSE

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.

STUDY TYPE

Systematic review and meta-analysis.

SUBJECTS

Eight studies with 2232 observations, including 1617 HCCs.

FIELD STRENGTH/SEQUENCE

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

ASSESSMENT

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).

STATISTICAL TESTS

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).

RESULTS

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).

DATA CONCLUSION

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.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 2.

Individual Participant Data Meta-Analysis of LR-5 in LI-RADS Version 2018 versus Revised LI-RADS for Hepatocellular Carcinoma Diagnosis

Background A simplification of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 (v2018), revised LI-RADS (rLI-RADS), has been proposed for imaging-based diagnosis of hepatocellular carcinoma (HCC). Single-site data suggest that rLI-RADS category 5 (rLR-5) improves sensitivity while maintaining positive predictive value (PPV) of the LI-RADS v2018 category 5 (LR-5), which indicates definite HCC. Purpose To compare the diagnostic performance of LI-RADS v2018 and rLI-RADS in a multicenter data set of patients at risk for HCC by performing an individual patient data meta-analysis. Materials and Methods Multiple databases were searched for studies published from January 2014 to January 2022 that evaluated the diagnostic performance of any version of LI-RADS at CT or MRI for diagnosing HCC. An individual patient data meta-analysis method was applied to observations from the identified studies. Quality Assessment of Diagnostic Accuracy Studies version 2 was applied to determine study risk of bias. Observations were categorized according to major features and either LI-RADS v2018 or rLI-RADS assignments. Diagnostic accuracies of category 5 for each system were calculated using generalized linear mixed models and compared using the likelihood ratio test for sensitivity and the Wald test for PPV. Results Twenty-four studies, including 3840 patients and 4727 observations, were analyzed. The median observation size was 19 mm (IQR, 11-30 mm). rLR-5 showed higher sensitivity compared with LR-5 (70.6% [95% CI: 60.7, 78.9] vs 61.3% [95% CI: 45.9, 74.7]; P < .001), with similar PPV (90.7% vs 92.3%; P = .55). In studies with low risk of bias (n = 4; 1031 observations), rLR-5 also achieved a higher sensitivity than LR-5 (72.3% [95% CI: 63.9, 80.1] vs 66.9% [95% CI: 58.2, 74.5]; P = .02), with similar PPV (83.1% vs 88.7%; P = .47). Conclusion rLR-5 achieved a higher sensitivity for identifying HCC than LR-5 while maintaining a comparable PPV at 90% or more, matching the results presented in the original rLI-RADS study. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sirlin and Chernyak in this issue.

Hepatocellular Carcinoma: Optimal Radiological Evaluation before Liver Transplantation

Liver transplantation (LT) is the recommended curative-intent treatment for patients with early or intermediate-stage hepatocellular carcinoma (HCC) who are ineligible for resection. Imaging plays a central role in staging and for selecting the best LT candidates. This review will discuss recent developments in pre-LT imaging assessment, in particular LT eligibility criteria on imaging, the technical requirements and the diagnostic performance of imaging for the pre-LT diagnosis of HCC including the recent Liver Imaging Reporting and Data System (LI-RADS) criteria, the evaluation of the response to locoregional therapy, as well as the non-invasive prediction of HCC aggressiveness and its impact on the outcome of LT. We will also briefly discuss the role of nuclear medicine in the pre-LT evaluation and the emerging role of artificial intelligence models in patients with HCC.

Differences between CEUS LI-RADS and CECT LI-RADS in the diagnosis of focal liver lesions in patients at risk for HCC

OBJECTIVES

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).

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

Nonalcoholic fatty liver disease and hepatocellular carcinoma:Insights in epidemiology, pathogenesis, imaging, prevention and therapy

Hepatocellular carcinoma (HCC) is estimated to be the third leading cause of cancer-related mortality and is characterized by low survival rates. Nonalcoholic fatty liver disease (NAFLD) is emerging as a leading cause of HCC, whose rates are increasing, owing to the increasing prevalence of NAFLD. The pathogenesis of NAFLD-associated HCC is multifactorial: insulin resistance, obesity, diabetes and the low-grade hepatic inflammation, which characterizes NAFLD, seem to play key roles in the development and progression of HCC. The diagnosis of NAFLD-associated HCC is based on imaging in the presence of liver cirrhosis, preferably computerized tomography or magnetic resonance imaging, but liver biopsy for histological confirmation is usually required in the absence of liver cirrhosis. Some preventive measures have been recommended for NAFLD-associated HCC, including weight loss, cessation of even moderate alcohol drinking and smoking, as well as the use of metformin, statins and aspirin. However, these preventive measures are mainly based on observational studies, thus they need validation in trials of different design before introducing in clinical practice. The treatment of NAFLD should be tailored on an individual basis and should be ideally determined by a multidisciplinary team. In the last two decades, new medications, including tyrosine kinase inhibitors and immune checkpoints inhibitors, have improved the survival of patients with advanced HCC, but trials specifically designed for patients with NAFLD-associated HCC are scarce. The aim of this review was to overview evidence on the epidemiology and pathophysiology of NAFLD-associated HCC, then to comment on imaging tools for its appropriate screening and diagnosis, and finally to critically summarize the currently available options for its prevention and treatment.

Standardizing liver imaging reporting and interpretation: LI-RADS and beyond

Imaging plays a crucial role in diagnosis and post-treatment monitoring of primary liver cancers. Clear, consistent, and actionable communication of imaging results is crucial to avoid miscommunication and potential detrimental impact on patient care. In this review, we discuss the importance, advantages, and potential impact of universal adoption of standardized terminology and interpretive criteria for liver imaging, from the point of view of radiologists and clinicians.

Review article: Available modalities for screening and imaging diagnosis of hepatocellular carcinoma-Current gaps and challenges

BACKGROUND

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.

AIM

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.

METHODS

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

RESULTS

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.

CONCLUSIONS

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.

LI-RADS: Looking Back, Looking Forward

Since its initial release in 2011, the Liver Imaging Reporting and Data System (LI-RADS) has evolved and expanded in scope. It started as a single algorithm for hepatocellular carcinoma (HCC) diagnosis with CT or MRI with extracellular contrast agents and has grown into a multialgorithm network covering all major liver imaging modalities and contexts of use. Furthermore, it has developed its own lexicon, report templates, and supplementary materials. This article highlights the major achievements of LI-RADS in the past 11 years, including adoption in clinical care and research across the globe, and complete unification of HCC diagnostic systems in the United States. Additionally, the authors discuss current gaps in knowledge, which include challenges in surveillance, diagnostic population definition, perceived complexity, limited sensitivity of LR-5 (definite HCC) category, management implications of indeterminate observations, challenges in reporting, and treatment response assessment following radiation-based therapies and systemic treatments. Finally, the authors discuss future directions, which will focus on mitigating the current challenges and incorporating advanced technologies. Tha authors envision that LI-RADS will ultimately transform into a probability-based system for diagnosis and prognostication of liver cancers that will integrate patient characteristics and quantitative imaging features, while accounting for imaging modality and contrast agent.

Can MRI features predict clinically relevant hepatocellular carcinoma genetic subtypes?

PURPOSE

Recent studies in cancer genomics have revealed core drivers for hepatocellular carcinoma (HCC) pathogenesis. We aim to study whether MRI features can serve as non-invasive markers for the prediction of common genetic subtypes of HCC.

METHODS

Sequencing of 447 cancer-implicated genes was performed on 43 pathology proven HCC from 42 patients, who underwent contrast-enhanced MRI followed by biopsy or resection. MRI features were retrospectively evaluated including tumor size, infiltrative tumor margin, diffusion restriction, arterial phase hyperenhancement, non-peripheral washout, enhancing capsule, peritumoral enhancement, tumor in vein, fat in mass, blood products in mass, cirrhosis and tumor heterogeneity. Fisher's exact test was used to correlate genetic subtypes with imaging features. Prediction performance using correlated MRI features for genetic subtype and inter-reader agreement were assessed.

RESULTS

The two most prevalent genetic mutations were TP53 (13/43, 30%) and CTNNB1 (17/43, 40%). Tumors with TP53 mutation more often demonstrated an infiltrative tumor margin on MRI (p = 0.01); inter-reader agreement was almost perfect (kappa = 0.95). The CTNNB1 mutation was associated with peritumoral enhancement on MRI (p = 0.04), inter-reader agreement was substantial (kappa = 0.74). The MRI feature of an infiltrative tumor margin correlated with the TP53 mutation with accuracy, sensitivity, and specificity of 74.4%, 61.5% and 80.0%, respectively. Peritumoral enhancement correlated with the CTNNB1 mutation with accuracy, sensitivity, and specificity of 69.8%, 47.0% and 84.6%, respectively.

CONCLUSION

An infiltrative tumor margin on MRI correlated with TP53 mutation and peritumoral enhancement correlated with CTNNB1 mutation in HCC. Absence of these MRI features are potential negative predictors of the respective HCC genetic subtypes that have implications for prognosis and treatment response.

Radiologic features of hepatocellular carcinoma related to prognosis

The cross-sectional imaging findings play a crucial role in the diagnosis of hepatocellular carcinoma (HCC). Recent studies have shown that imaging findings of HCC are not only relevant for the diagnosis of HCC, but also for identifying genetic and pathologic characteristics and determining prognosis. Imaging findings such as rim arterial phase hyperenhancement, arterial phase peritumoral hyperenhancement, hepatobiliary phase peritumoral hypointensity, non-smooth tumor margin, low apparent diffusion coefficient, and the LR-M category of the Liver Imaging-Reporting and Data System have been reported to be associated with poor prognosis. In contrast, imaging findings such as enhancing capsule appearance, hepatobiliary phase hyperintensity, and fat in mass have been reported to be associated with a favorable prognosis. Most of these imaging findings were examined in retrospective, single-center studies that were not adequately validated. However, the imaging findings can be applied for deciding the treatment strategy for HCC, if their significance can be confirmed by a large multicenter study. In this literature, we would like to review imaging findings related to the prognosis of HCC as well as their associated clinicopathological characteristics.

Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer metastases

Liver cancers are the fourth leading cause of cancer-related mortality worldwide. In the past decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of algorithms in the cancer setting. A growing body of recent studies have evaluated machine learning (ML) and deep learning (DL) algorithms for pre-screening, diagnosis and management of liver cancer patients through diagnostic image analysis, biomarker discovery and predicting personalized clinical outcomes. Despite the promise of these early AI tools, there is a significant need to explain the 'black box' of AI and work towards deployment to enable ultimate clinical translatability. Certain emerging fields such as RNA nanomedicine for targeted liver cancer therapy may also benefit from application of AI, specifically in nano-formulation research and development given that they are still largely reliant on lengthy trial-and-error experiments. In this paper, we put forward the current landscape of AI in liver cancers along with the challenges of AI in liver cancer diagnosis and management. Finally, we have discussed the future perspectives of AI application in liver cancer and how a multidisciplinary approach using AI in nanomedicine could accelerate the transition of personalized liver cancer medicine from bench side to the clinic.

The Organ Procurement and Transplantation Network hepatocellular carcinoma classification: Alignment with Liver Imaging Reporting and Data System, current gaps, and future direction

The Organ Procurement and Transplantation Network (OPTN) updated its allocation policy for liver transplantation to align with the Liver Imaging Reporting and Data System (LI-RADS) for the diagnosis of hepatocellular carcinoma (HCC). LI-RADS computed tomography/magnetic resonance imaging algorithm had achieved congruency with the American Association for the Study of Liver Diseases (AASLD) HCC Practice Guidance in 2018, and therefore, alignment of OPTN, LI-RADS, and AASLD unifies HCC diagnostic approaches. The two changes to the OPTN HCC classification are adoption of LI-RADS terminology or lexicon for HCC major imaging features as well as the modification of OPTN Class-5A through the adoption of LI-RADS-5 criteria. However, despite this significant milestone, the OPTN allocation policy may benefit from further refinements such as adoption of treatment response assessment criteria after locoregional therapy and categorization criteria for lesions with atypical imaging appearances that are not specific for HCC. In this review, we detail the changes to the OPTN HCC classification to achieve alignment with LI-RADS, discuss current limitations of the OPTN classification, and explore future directions.

Percentages of Hepatocellular Carcinoma in LI-RADS Categories with CT and MRI: A Systematic Review and Meta-Analysis

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

Universal Liver Imaging Lexicon: Imaging Atlas for Research and Clinical Practice

The use of standardized terms in assessing and reporting disease processes has well-established benefits, such as clear communication between radiologists and other health care providers, improved diagnostic accuracy and reproducibility, and the enhancement and facilitation of research. Recently, the Liver Imaging Reporting and Data System (LI-RADS) Steering Committee released a universal liver imaging lexicon. The current version of the lexicon includes 81 vetted and precisely defined terms that are relevant to acquisition of images using all major liver imaging modalities and contrast agents, as well as lesion- and organ-level features. Most terms in the lexicon are applicable to all patients undergoing imaging of the liver, and only a minority of the terms are strictly intended to be used for patients with high risk factors for hepatocellular carcinoma. This pictorial atlas familiarizes readers with the liver imaging lexicon and includes discussion of general concepts, providing sample definitions, schematics, and clinical examples for a subset of the terms in the liver imaging lexicon. The authors discuss general, technical, and imaging feature terms used commonly in liver imaging, with the goal of illustrating their use for clinical and research applications. Work of the U.S. Government published under an exclusive license with the RSNA. Online supplemental material is available for this article.

PIVKA-II or AFP has better diagnostic properties for hepatocellular carcinoma diagnosis in high-risk patients

Background

Hepatocellular carcinoma (HCC) is a lethal cancer. Two biomarkers were used for HCC diagnosis including alpha-fetoprotein (AFP) and protein induced by vitamin K absence-II or antagonist (PIVKA-II). However, data on biomarkers and HCC diagnosis are not consistent. This study aimed to evaluate if PIVKA-II, AFP, or a combination of both biomarkers had the best diagnostic properties for HCC.

Methods

This was a prospective study and enrolled patients 18 years or over with a high risk for HCC. AFP and PIVKA-II levels were calculated for HCC diagnosis. Diagnostic properties of both biomarkers were reported with sensitivity, specificity, and a receiver operating characteristic (ROC) curve.

Results

There were 260 patients with high risk for HCC in this cohort. Of those, 219 patients were diagnosed with HCC: confirmed by biopsy in 7 patients (2.69%) and by imaging in the others. Median values of AFP and PIVKA-II were 56 ng/mL and 348 mAU/mL, respectively. PIVKA-II level of 40 mAU/mL had sensitivity of 80.80%, while AFP of 10 ng/mL had sensitivity of 75.80%. A combination of PIVKA-II at 100 mAU/mL or over and AFP of 11 ng/mL gave sensitivity of 60.30%. The ROC curve of PIVKA-II plus AFP was significantly higher than the AFP alone (0.855 vs. 0.796; p = 0.027), but not significantly different from the PIVKA-II alone (0.855 vs. 0.832; p = 0.130).

Conclusion

PIVKA-II may have more diagnostic yield for HCC compared with AFP. It can be used alone without a combination with AFP.

[CT/MRI Liver Imaging Reporting and Data System (LI-RADS): Standardization, Evidence, and Future Direction]

The liver imaging reporting and data system (LI-RADS) has been developed with the support of the American College of Radiology to standardize the diagnosis and evaluation of treatment response of hepatocellular carcinoma (HCC). The CT/MRI LI-RADS version 2018 has been incorporated in the American Association for the Study of Liver Diseases guidance. This review examines the effect of CT/MRI LI-RADS on the standardized reporting of liver imaging, and the evidence in diagnosing HCC and evaluating treatment response after locoregional treatment using CT/MRI LI-RADS. The results are compared with other HCC diagnosis guidelines, and future directions are described.

Patient communication in radiology: Moving up the agenda

Optimised communication between patients and the imaging team is an essential component of providing patient-centred and value-based care. Communication with patients can be challenging in the setting of busy radiology departments where there is a focus on efficient and accurate diagnosis. Traditionally, most results are provided directly to the referring clinician. However, the importance of direct communication between the radiologist and patient is increasingly relevant, particularly in the context of face-to-face settings such as rapid assessment and ultrasound clinics, and interventional radiology, as well as in written form through electronic patient portals. Artificial intelligence tools may improve efficiency, allowing more time for radiologists to communicate directly with patients. There is a need for dedicated training in communication skills for imaging professionals. This review considers the topic of patient communication in the setting of imaging departments and discusses the ways that communication skills may be improved through training and through harnessing emerging digital technologies that may enhance the quality of communication.

Diagnostic performance of CT versus MRI Liver Imaging Reporting and Data System category 5 for hepatocellular carcinoma: a systematic review and meta-analysis of comparative studies

OBJECTIVE

To compare the performance of Liver Imaging Reporting and Data System category 5 (LR-5) for diagnosing HCC between CT and MRI using comparative studies.

METHODS

The MEDLINE and EMBASE databases were searched from inception to April 21, 2021, to identify studies that directly compare the diagnostic performance of LR-5 for HCC between CT and MRI. A bivariate random-effects model was fitted to calculate the pooled per-observation sensitivity and specificity of LR-5 of each modality, and compare the pooled estimates of paired data. Subgroup analysis was performed according to the MRI contrast agent.

RESULTS

Seven studies with 1145 observations (725 HCCs) were included in the final analysis. The pooled per-observation sensitivity of LR-5 for diagnosing HCC was higher using MRI (61%; 95% confidence interval [CI], 43-76%; I² = 95%) than CT (48%; 95% CI, 31-65%; I² = 97%) (p < 0.001). The pooled per-observation specificities of LR-5 did not show statistically significant difference between CT (96%; 95% CI, 92-98%; I² = 0%) and MRI (93%; 95% CI, 88-96%; I² = 16%) (p = 0.054). In the subgroup analysis, extracellular contrast agent-enhanced MRI showed significantly higher pooled per-observation sensitivity than gadoxetic acid-enhanced MRI for diagnosing HCC (73% [95% CI, 55-85%] vs. 55% [95% CI, 39-70%]; p = 0.007), without a significant difference in specificity (93% [95% CI, 80-98%] vs. 94% [95% CI, 87-97%]; p = 0.884).

CONCLUSIONS

The LR-5 of MRI showed significantly higher pooled per-observation sensitivity than CT for diagnosing HCC. The pooled per-observation specificities of LR-5 were comparable between the two modalities.

KEY POINTS

• The pooled sensitivity of LR-5 using MRI was higher than that using CT (61% versus 48%), but the pooled specificities of LR-5 were not significantly different between CT and MRI (96% versus 93%). • Subgroup analysis according to the MRI contrast media showed a significantly higher pooled per-observation sensitivity using ECA-enhanced MRI than with EOB-enhanced MRI (73% versus 55%), and comparable specificities (93% versus 94%). • Although LI-RADS provides a common diagnostic algorithm for CT or MRI, the per-observation performance of LR-5 can be affected by the imaging modality as well as the MRI contrast agent.

Performance of LI-RADS Version 2018 on CT for Determining Eligibility for Liver Transplant According to Milan Criteria in Patients at High Risk for Hepatocellular Carcinoma

BACKGROUND. LI-RADS has been investigated primarily in terms of detection of hepatocellular carcinoma (HCC), with less attention given to its performance, particularly on CT, in determining eligibility for liver transplant (LT). OBJECTIVE. The purpose of our study was to assess the performance of LI-RADS version 2018 (v2018) on CT for the diagnosis of HCC and determination of LT eligibility according to the Milan criteria (MC). METHODS. This retrospective study included 136 patients (110 men, 26 women; mean age, 53.9 ± 8.1 [SD] years) at high-risk for HCC who underwent liver protocol CT within 3 months before LT between January 2010 and December 2018. Two radiologists independently reviewed CT examinations using LI-RADS v2018; Organ Procurement and Transplantation Network (OPTN) classes were constructed from the LI-RADS interpretations. Histopathologic analysis of liver explants served as the reference standard for determining the presence of HCC and LT eligibility based on MC. Diagnostic performance was evaluated. Overall survival (OS) was assessed based on medical record review. RESULTS. Based on histopathologic evaluation of liver explants in the 136 patients, 27 patients had no malignancy, 77 were eligible for LT due to HCC within MC, and 32 were unsuitable for LT (i.e., HCC beyond MC in 16 patients, HCC with macrovascular invasion in 12, non-HCC malignancy in four). LR-5 exhibited per-lesion sensitivity and PPV for HCC of 55.9% and 92.8%, respectively, for reader 1 and 39.8% and 86.5% for reader 2. When considering LR-5 observations to represent HCC in assessing MC, LI-RADS had accuracy for determining LT eligibility of 92.7% for reader 1 and 85.3% for reader 2; OPTN criteria had accuracy for determining LT eligibility of 89.0% for reader 1 and 84.4% for reader 2. Five-year OS for patients within MC versus 5-year OS for patients unsuitable for LT was 92.2 months versus 56.0 months for LI-RADS, 92.6 months versus 47.6 months for OPTN criteria, and 93.3 months versus 55.1 months for histopathologic assessment of liver explants. CONCLUSION. LI-RADS v2018, as evaluated on CT in high-risk patients, shows high PPV for HCC detection and high accuracy for determining LT eligibility based on MC. LT eligibility based on preoperative LI-RADS evaluation is associated with post-LT survival. CLINICAL IMPACT. These findings support the use of LI-RADS on CT in assessing eligibility in patients who are candidates for LT.

Correlation of CT Perfusion Parameters and Vascular Endothelial Growth Factor (VEGF) and Basic Fibroblast Growth Factor (BFGF) in Patients with Primary Liver Cancer

Objective

To investigate the correlation of CT perfusion-related parameters with serum vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (BFGF) in patients with primary liver cancer.

Methods

A total of 100 patients with primary liver cancer who were treated in our hospital from June 2019 to June 2021 were selected as the observation group, and 90 patients with benign liver lesions during the same period were selected as the control group. The CT perfusion-related parameters (perfusion volume and perfusion index) and serum VEGF and BFGF levels were compared between the two groups. Pearson correlation was used to analyze the correlation between CT perfusion-related parameters and serum VEGF and BFGF levels.

Results

Compared to the control group, significantly higher HAP and lower HPP and TLP were observed in the observation group. The perfusion volume indexes of patients with different stages of liver cancer in the observation group were statistically different (P < 0.05). Compared to the control group, the observation group witnessed significantly higher HAPI and lower HPPI. There were statistically significant differences in the perfusion index of patients with different stages of primary liver cancer in the observation group (P < 0.05). The serum VEGF and BFGF levels in the observation group were significantly higher than those in the control group, and the serum VEGF and BFGF levels in patients with different stages of primary liver cancer in the observation group were statistically different (P < 0.05). Pearson correlation analysis showed that HAP and HAPI were positively correlated with VEGF and BFGF (r = 0.986, P ≤ 0.001; r = 0.983, P ≤ 0.001), and HPP, TLP, and HPPI were negatively correlated with VEGF and BFGF (r = −0.992, P ≤ 0.001; r = -0.993, P ≤ 0.001; r = −0.995, P ≤ 0.001).

Conclusion

CT perfusion-related parameters and serum VEGF and BFGF levels in patients with primary liver cancer are abnormally expressed, and there is a strong correlation between the two, which might aid clinical diagnosis and treatment.

Radiomics Analysis on Gadoxetate Disodium-Enhanced MRI Predicts Response to Transarterial Embolization in Patients with HCC

Objectives: To explore the potential of radiomics on gadoxetate disodium-enhanced MRI for predicting hepatocellular carcinoma (HCC) response after transarterial embolization (TAE). Methods: This retrospective study included cirrhotic patients treated with TAE for unifocal HCC naïve to treatments. Each patient underwent gadoxetate disodium-enhanced MRI. Radiomics analysis was performed by segmenting the lesions on portal venous (PVP), 3-min transitional, and 20-min hepatobiliary (HBP) phases. Clinical data, laboratory variables, and qualitative features based on LI-RADSv2018 were assessed. Reference standard was based on mRECIST response criteria. Two different radiomics models were constructed, a statistical model based on logistic regression with elastic net penalty (model 1) and a computational model based on a hybrid descriptive-inferential feature extraction method (model 2). Areas under the ROC curves (AUC) were calculated. Results: The final population included 51 patients with HCC (median size 20 mm). Complete and objective responses were obtained in 14 (27.4%) and 29 (56.9%) patients, respectively. Model 1 showed the highest performance on PVP for predicting objective response with an AUC of 0.733, sensitivity of 100%, and specificity of 40.0% in the test set. Model 2 demonstrated similar performances on PVP and HBP for predicting objective response, with an AUC of 0.791, sensitivity of 71.3%, specificity of 61.7% on PVP, and AUC of 0.790, sensitivity of 58.8%, and specificity of 90.1% on HBP. Conclusions: Radiomics models based on gadoxetate disodium-enhanced MRI can achieve good performance for predicting response of HCCs treated with TAE.

CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis

Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) (PROSPERO protocol: CRD42020164486). Results A total of 32 studies were included, with 1170 CT observations, 3341 MRI observations, and 853 CEUS observations. At multivariable analysis of CT/MRI LI-RADS, all major features were associated with HCC, except threshold growth (OR, 1.6; 95% CI: 0.7, 3.6; P = .07). Nonperipheral washout (OR, 13.2; 95% CI: 9.0, 19.2; P = .01) and nonrim arterial phase hyperenhancement (APHE) (OR, 10.3; 95% CI: 6.7, 15.6; P = .01) had stronger associations with HCC than enhancing capsule (OR, 2.4; 95% CI: 1.7, 3.5; P = .03). On CEUS images, APHE (OR, 7.3; 95% CI: 4.6, 11.5; P = .01), late and mild washout (OR, 4.1; 95% CI: 2.6, 6.6; P = .01), and size of at least 20 mm (OR, 1.6; 95% CI: 1.04, 2.5; P = .04) were associated with HCC. Twenty-five studies (78%) had high risk of bias due to reporting ambiguity or study design flaws. Conclusion Most Liver Imaging Reporting and Data System major features had different independent associations with hepatocellular carcinoma; for CT/MRI, arterial phase hyperenhancement and washout had the strongest associations, whereas threshold growth had no association. © RSNA, 2021 Online supplemental material is available for this article.

Second-line Sonazoid-enhanced ultrasonography for Liver Imaging Reporting and Data System category 3 and 4 on gadoxetate-enhanced magnetic resonance imaging

Purpose

This study investigated the utility of second-line contrast-enhanced ultrasonography (CEUS) using Sonazoid in Liver Imaging Reporting and Data System category 3 (LR-3) and 4 (LR-4) observations on gadoxetate-enhanced magnetic resonance imaging (MRI).

Methods

This retrospective study included LR-3 or LR-4 observations on gadoxetate-enhanced MRI subsequently evaluated with CEUS from 2013 to 2017. The presence of MRI features, CEUS-arterial phase hyperenhancement (CEUS-APHE), and Kupffer phase defect (KPD) was evaluated. Multivariable logistic regression analysis was performed to identify significant imaging features associated with the diagnosis of hepatocellular carcinoma (HCC). The optimal diagnostic criteria were investigated using the McNemar test.

Results

In total, 104 patients with 104 observations (63 HCCs) were included. The presence of both CEUS-APHE and KPD on CEUS enabled the additional detection of 42.3% (11/26) of LR-3 HCCs and 78.4% (29/37) of LR-4 HCCs. Transitional phase (TP) hypointensity (adjusted odds ratio [OR], 10.59; P<0.001), restricted diffusion (adjusted OR, 7.55; P=0.004), and KPD (adjusted OR, 7.16; P=0.003) were significant imaging features for HCC diagnosis. The presence of at least two significant imaging features was optimal for HCC diagnosis (sensitivity, specificity, and accuracy: 88.9%, 78.1%, and 84.6%, respectively), with significantly higher sensitivity than the presence of both CEUS-APHE and KPD (sensitivity, specificity, and accuracy: 63.5% [P=0.001], 92.7% [P=0.077], and 75.0% [P=0.089], respectively).

Conclusion

The combined interpretation of gadoxetate-enhanced MRI and second-line CEUS using Sonazoid, focusing on TP hypointensity, restricted diffusion, and KPD, may be optimal for further characterizing LR-3 and LR-4 observations.

The Course of LIRADS 3 and 4 Hepatic Abnormalities as Correlated With Explant Pathology: A Single Center Experience

BACKGROUND AND AIMS

The Liver Reporting and Data System (LI-RADS) is the standard classification of imaging findings of hepatic abnormalities for hepatocellular carcinoma (HCC) surveillance. We aimed to study the course of LI-RADS 3 and 4 (LR-3 and LR-4) abnormalities through correlations with explant pathology.

METHODS

A single center retrospective study of liver transplant recipients between January 2016 and September 2019 with HCC on explant pathology was conducted. Eligible patients were divided into three subgroups based on their LI-RADS classification: LR-3/4, LR-5 only, and combination of LR-3/4/5.

RESULTS

There were 116 eligible patients with 99 LR-3/4 observations (60 LR-3 and 39 LR-4); the rest had LR-5 lesions. LR-4 more often than LR-3 observations progressed to LR-5 (36% vs 12%) and with shorter duration during follow-up (median 175 days and 196 days). Mean size growth of LR-3 and LR-4 abnormalities were 2.6 and 3.8 mm; median growth rates were 0.2 and 0.4 mm/month, respectively. Numbers of HCC lesions per explant, largest HCC lesion size, and cumulative size were higher in LR-3/4/5 subgroup than LR-5 subgroup (P = 0.007, 0.007 and 0.006, respectively); 68% of LR-3 and 82% of LR-4 abnormalities were confirmed HCC on explant (P = 0.09).

CONCLUSION

Compared to LR-3, more LR-4 abnormalities progressed to LR-5 (12% and 36%, respectively) in a shorter time and with faster growth rate. A high proportion of LR-3 and LR-4 lesions (68% and 82%, respectively) were confirmed HCC on explant, raising the question of whether excluding HCC based on radiologic criteria alone is adequate in those with LR-3/4 abnormalities.

Accuracy of Various Forms of Contrast-Enhanced MRI for Diagnosing Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Background

Contrast-enhanced MRI can be used to identify patients with hepatocellular carcinoma (HCC). However, studies around the world have found differing diagnostic accuracies for the technique. Hence, we designed this meta-analysis to assess the accuracy of contrast-enhanced MRI for HCC diagnosis.

Methods

We conducted a systematic search for all studies reporting the diagnostic accuracy of contrast-enhanced MRI for HCC in the databases of MEDLINE, EMBASE, Cochrane Library, Web of Science, SCOPUS, ScienceDirect, and Google Scholar from inception until January 2021. We used the "Midas" package from the STATA software to perform the meta-analysis.

Results

Our study was based on 21 publications with 5,361 patients. The pooled HCC diagnosis sensitivity and specificity were 75% (95% CI, 70%-80%) and 90% (95% CI, 88%-92%), respectively, for gadoxetic acid-enhanced MRI; and they were 70% (95% CI, 57%-81%) and 94% (95% CI, 85%-97%), respectively, for MRI with extracellular contrast agents (ECA-MRI). We found significant heterogeneity with a significant chi-square test and an I ² statistic >75%. We also found significant publication bias as per Deeks' test results and funnel plot.

Conclusion

We found that both types of contrast-enhanced MRI are accurate diagnostic and surveillance tools for HCC and offer high sensitivity and specificity. Further studies on different ethnic populations are required to strengthen our findings.

What proportion of LI-RADS 5 observations reported in clinical practice do not meet LI-RADS 5 criteria?

OBJECTIVES

Liver Imaging Reporting and Data System (LI-RADS, LR) category 5 (definite hepatocellular carcinoma [HCC]) is assigned based on combinations of major imaging features (MFs): size, arterial-phase hyperenhancement (APHE), washout (WO), enhancing capsule, and threshold growth. The criteria were simplified in v2018 compared to v2017. The goal of this study is to assess the proportion of LR-5 observations reported in clinical practice with LI-RADS v2017 or v2018 that did not meet LR-5 criteria based on reported MFs.

METHODS

All MR and CT reports using a standardized LI-RADS template between April 2017 and September 2020 were identified retrospectively. For each reported LR-5 observation, size, MFs, and LI-RADS version (v2017 or v2018) were extracted. Reported MFs were used to determine whether LR-5 criteria were met using the applied version of LI-RADS. The data was summarized descriptively.

RESULTS

Three hundred eight observations in 234 patients (67.6% male, mean age 66.2 years) were reported as LR-5, including 136 (44.2%) with v2017 and 172 (55.8%) with v2018. 8/136 (6%) v2017 LR-5 observations and 6/172 (3%) v2018 LR-5 observations did not meet LR-5 criteria. Of 8 incorrectly categorized v2017 observations, 3 (43%) lacked APHE, 1 (14%) was a 16-mm new observation with APHE only, and 4 (43%) were 10-19 mm with APHE and WO. Of the 6 incorrectly categorized v2018 observations, 5 (83%) lacked APHE and 1 (17%) was < 10 mm.

CONCLUSIONS

Depending on the LI-RADS version, 3-6% of LR-5 observations reported in clinical practice do not meet LR-5 criteria based on reported MFs. Key Points • Depending on the LI-RADS version, 3-6% of LR-5 observations in clinical practice do not meet LR-5 criteria based on reported major imaging features. • Assigning LR-5 category to observations without nonrim arterial-phase hyperenhancement was the most common error.

Progression Rates of LR-2 and LR-3 Observations on MRI to Higher LI-RADS Categories in Patients at High Risk for Hepatocellular Carcinoma: A Retrospective Study

Background: Reported rates of hepatocellular carcinoma (HCC) for LR-2 and LR-3 observations are generally greater than what may be expected based on clinical experience, possibly reflecting some studies' requirement for pathologic reference. Objective: To determine progression rates to higher LI-RADS categories of LR-2 and LR-3 observations in patients at high risk for HCC. Methods: This retrospective study included 91 patients (mean age 62 years; 64 men, 27 women) at high risk for HCC with clinically reported LR-2 (n=55) or LR-3 (n=36) observations on MRI and who also underwent follow-up CT or MRI after at least 12 months. A study coordinator annotated the location of a single LR-2 or LR-3 observation per patient, based on the clinical reports. Using LI-RADS v2018 criteria, two radiologists independently assigned LI-RADS categories on the follow-up examinations. Progression rates from LR-2 or LR-3 to higher categories were determined. A post hoc consensus review was performed of observations that progressed to LR-4 or LR-5. Subgroup analyses were performed with respect to presence or prior HCC (n=34) or a separate baseline LR-5 observation (n=12). Results: For LR-2 observations, progression to LR-4 was 0.0% (95% CI 0.0%-6.7%) and LR-5 was 3.6% (95% CI 0.4%-13.1%) for both readers. For LR-3 observations, progression to LR-4 was 22.2% (95% CI 9.6%-43.8%) and LR-5 was 11.1% (95% CI 3.0%-28.4%) for both readers. Fourteen observations progressed to LR-4 or LR-5 for both readers (post hoc analysis: no LR-2 to LR-4; two LR-2 to LR-5; eight LR-3 to LR-4; four LR-3 to LR-5). Progression rate from LR-3 to LR-5 was higher (p<.001) among patients with versus without a separate baseline LR-5 observation (100.0% vs 3.0%, respectively) for both readers; progression rate from LR-2 to LR-5 was not associated with a separate baseline LR-5 observation for either reader (p=.30). Progression rates were not different (p>.99) between patients with versus without prior HCC. Conclusion: Based on progression to LR-4 or LR-5, LR-2 and LR-3 observations showed lower progression rates than reported in studies incorporating pathology in determining progression. Clinical Impact: The findings refine understanding of the clinical significance of LR-2 and LR-3 observations.

LI-RADS treatment response algorithm for detecting incomplete necrosis in hepatocellular carcinoma after locoregional treatment: a systematic review and meta-analysis using individual patient data

PURPOSE

To perform a systematic review and meta-analysis using individual patient data to investigate the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS) Treatment Response (TR) algorithm for detecting incomplete necrosis on pathology.

METHODS

PubMed and EMBASE were searched from Jan 1, 2017 until October 14, 2020. Studies reporting diagnostic accuracy of LI-RADS TR algorithm on CT or MRI for detecting incomplete necrosis on pathology as a reference standard were included. Sensitivity and specificity were pooled using random-effects model. Subgroup analyses were performed for locoregional treatment (LRT) type and imaging modality.

RESULTS

Six studies (393 patients, 534 lesions) were included. Pooled sensitivity was 0.56 (95% confidence interval [CI] 0.43-0.69) and specificity was 0.91 (95%CI 0.84-0.96). Pooled sensitivity was highest using arterial phase hyperenhancement (APHE) (0.67 [95%CI 0.51-0.81]), followed by washout (0.43 [95%CI 0.26-0.62]) and enhancement similar to pretreatment (0.24 [95%CI 0.15-0.36]). Among lesions with incomplete necrosis, 2% (95%CI 0.00-0.05) manifested as washout but no APHE; 0% (95% CI 0.00-0.02) as enhancement similar to pretreatment without both APHE and washout. Pooled sensitivity was lower after ablation than embolization (0.42 [95%CI, 0.28-0.57] vs. 0.65 [95%CI, 0.53-0.77], p = 0.033). MRI and CT were comparable (p = 0.783 and 0.290 for sensitivity and specificity).

CONCLUSIONS

LI-RADS TR algorithm shows moderate sensitivity and high specificity for detecting incomplete necrosis after LRT. APHE is the dominant criterion, a washout contributes to small but meaningful extent, while the contribution of enhancement similar to pretreatment may be negligible. LRT type may affect performance of the algorithm.

LI-RADS Major Features on MRI for Diagnosing Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

BACKGROUND

The reported diagnostic performance for hepatocellular carcinoma (HCC) of each major imaging feature on MRI using standardized definitions of the Liver Imaging Reporting and Data System (LI-RADS) is variable. It is important to know the actual performance of each LI-RADS major imaging feature for imaging diagnosis of HCC and determine the sources of heterogeneity between the reported results.

PURPOSE

To systematically determine the performance of each major imaging feature of LI-RADS for diagnosing HCC using either extracellular contrast agent-enhanced MRI (ECA-MRI) or gadoxetate disodium-enhanced MRI (EOB-MRI).

STUDY TYPE

Systematic review and meta-analysis.

SUBJECTS

Sixteen original articles with 3542 lesions.

FIELD STRENGTH

A 1.5 T and 3.0 T.

ASSESSMENT

Data extraction was independently performed by two reviewers who identified and reviewed original articles reporting the diagnostic performance of each LI-RADS major imaging feature-arterial phase hyperenhancement (APHE), observation size, washout appearance, enhancing "capsule," and threshold growth-using MRI. Study characteristics, study population characteristics, MRI characteristics, contrast agent, LI-RADS version, reference standards, and study outcomes were extracted from included studies. Risk of bias and concerns regarding applicability were evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

STATISTICAL TESTS

Bivariate random-effects models were used to obtain summary estimates of the diagnostic performance of each LI-RADS major imaging feature. Hierarchical summary receiver operating characteristic curves were plotted. Meta-regression analyses were performed to explore potential sources of heterogeneity.

RESULTS

The pooled per-observation sensitivities and specificities for diagnosing HCC were 85% (95% confidence interval [CI] = 78%-89%) and 57% (95% CI = 44%-70%) for arterial phase hyperenhancement (APHE), 77% (95% CI = 72%-82%), and 74% (95% CI = 63%-83%) for washout appearance, and 52% (95% CI = 41%-64%) and 90% (95% CI = 85%-94%) for enhancing "capsule," respectively.

DATA CONCLUSIONS

Among the LI-RADS major features, the sensitivity was the highest for APHE and the specificity was the highest for enhancing "capsule" in the diagnosis of HCC.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Optimized scan delay for late hepatic arterial or pancreatic parenchymal phase in dynamic contrast-enhanced computed tomography with bolus-tracking method

OBJECTIVES

To determine the optimal scan delay corresponding to individual hemodynamic status for pancreatic parenchymal phase in dynamic contrast-enhanced CT of the abdomen.

METHODS

One hundred and fourteen patients were included in this retrospective study (69 males and 45 females; mean age, 67.9 ± 12.1 years; range, 39-87 years). These patients underwent abdominal dynamic contrast-enhanced CT between November 2019 and May 2020. We calculated and recorded the time from contrast material injection to the bolus-tracking trigger of 100 Hounsfield unit (HU) at the abdominal aorta (s) (Time_TRIG) and scan delay from the bolus-tracking trigger to the initiation of pancreatic parenchymal phase scanning (s) (Time_SD). The scan delay ratio (SDR) was defined by dividing the Time_SD by Time_TRIG. Non-linear regression analysis was conducted to assess the association between CT number of the pancreas and SDR and to reveal the optimal SDR, which was ≥120 HU in pancreatic parenchyma.

RESULTS

The non-linear regression analysis showed a significant association between CT number of the pancreas and the SDR (p < 0.001). The mean Time_TRIG and Time_SD were 16.1 s and 16.8 s, respectively. The SDR to peak enhancement of the pancreas (123.5 HU) was 1.00. An SDR between 0.89 and 1.18 shows an appropriate enhancement of the pancreas (≥120 HU).

CONCLUSION

The CT number of the pancreas peaked at an SDR of 1.00, which means Time_SD should be approximately the same as Time_TRIG to obtain appropriate pancreatic parenchymal phase images in dynamic contrast-enhanced CT with bolus-tracking method.

ADVANCES IN KNOWLEDGE

The hemodynamic state is different in each patient; therefore, scan delay from the bolus-tracking trigger should also vary based on the time from contrast material injection to the bolus-tracking trigger. This is necessary to obtain appropriate late hepatic arterial or pancreatic parenchymal phase images in dynamic contrast-enhanced CT of the abdomen.

Diagnostic Performance of Liver Imaging Reporting and Data System Version 2017 Versus Version 2018 for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis of Comparative Studies

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing liver imaging in patients at risk for hepatocellular carcinoma (HCC).

PURPOSE

To systematically compare the performance of computed tomography (CT)/MRI LI-RADS category 5 (LR-5) for diagnosing HCC between versions 2017 and 2018.

STUDY TYPE

Systematic review and meta-analysis.

SUBJECTS

Six articles with 1181 lesions.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T.

ASSESSMENT

Data extraction was independently performed by two reviewers who identified and reviewed articles comparing the performance of LR-5 for diagnosing HCC between CT/MRI LI-RADS versions 2017 and 2018. Study and patient characteristics, index test characteristics, reference standards, and study outcomes were extracted from included studies. Risk of bias and concerns regarding applicability were evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

STATISTICAL TESTS

Bivariate random-effects models were used to calculate the pooled per-observation sensitivity and specificity of LR-5 using both versions. The summary receiver operating characteristic curves were plotted. Meta-regression analysis was performed to explore heterogeneity. A P-value <0.05 was considered to be statistically significant for all analyses other than heterogeneity, where the significance threshold was 0.1.

RESULTS

The pooled per-observation sensitivity of LR-5 for diagnosing HCC did not show statistically significant difference between versions 2017 (60%; 95% confidence interval [CI], 49%-70%) and 2018 (67%; 95% CI, 56%-76%; P = 0.381). The pooled per-observation specificities of LR-5 were not significantly different between versions 2017 (92%; 95% CI, 90%-95%) and 2018 (91%; 95% CI, 88%-93%; P = 0.332). Meta-regression analyses revealed that the most common underlying liver disease (hepatitis B or hepatitis C) was a significant factor contributing to the heterogeneity of sensitivities among studies for both versions.

DATA CONCLUSION

In this meta-analysis using intraindividual paired comparisons, the pooled sensitivity and pooled specificity of LR-5 were not significantly different between 2017 and 2018 LI-RADS versions.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Characteristics and Early Recurrence of Hepatocellular Carcinomas Categorized as LR-M: Comparison with Those Categorized as LR-4 or 5

BACKGROUND

According to the Liver Imaging Reporting and Data System (LI-RADS), the LI-RADS category M (LR-M), which are probably or definitely malignant but are not specific for hepatocellular carcinomas (HCCs), does not exclude HCCs. A gap in knowledge remains, including their characteristics and recurrence of HCCs categorized as LR-M.

PURPOSE

To compare the characteristics of HCCs categorized as LR-M with HCCs categorized as LR-4 or LR-5 (LR-4/5) using the LI-RADS version 2018 and evaluate the relationship of these categories with the risk of early recurrence after curative resections of single HCCs.

STUDY TYPE

Retrospective.

SUBJECTS

Two hundred and eighty-one patients (mean age, 57 years; 191 men and 90 women) who underwent curative resections for single HCCs and preoperative contrast-enhanced MRI between 2015 and 2017.

FIELD STRENGTH/SEQUENCE

3T Dual gradient-echo T₁ WI with in- and opposed-phase, turbo spin-echo T₂ WI, diffusion-weighted echo-planar images, and three-dimensional gradient-echo T₁ WI before and after administration of contrast agent.

ASSESSMENT

MRI features according to the LI-RADS version 2018 were evaluated and LI-RADS category were assigned for each observation. Clinical, imaging, and histopathological features were compared based on LI-RADS categorization. Early recurrence rates (<2 years) and associated factors were also evaluated.

STATISTICAL TESTS

Fisher's exact test, two-sample t test after satisfying assumption of normality through Shapiro-Wilk test, Fleiss κ coefficient, Cox proportional hazards regression analysis, Kaplan-Meier method, and log-rank test.

RESULTS

Forty-one HCCs (14.6%) were categorized as LR-M and 240 HCCs (85.4%) were categorized as LR-4/5. LR-M HCCs showed poorer differentiation than LR-4/5 HCCs. In the multivariate analysis, the LR-M category was an independent predictor for early recurrence (hazard ratio, 1.904; 95% confidence interval, 1.024-3.542; P < 0.05). Early recurrence rates were significantly higher in patients with LR-M HCCs than in patients with LR-4/5 HCCs (32.0% vs. 18.4%, respectively, P < 0 05).

DATA CONCLUSION

Compared to LR-4/5 HCCs, LR-M HCCs were associated with poorer tumor differentiation and higher early recurrence rates after curative resections of single HCCs.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage: 2.

The peritumoral hypointense rim around hepatocellular carcinoma on T2*-weighted magnetic resonance imaging: radiologic-pathologic correlation

BACKGROUND

A peritumoral hypointense rim (PTHR) is sometimes observed around hepatocellular carcinoma (HCC) on T2*-weighted images (T2*WIs). We aimed to investigate the association between the PTHR and histopathologic findings on T2*WIs.

METHODS

We assessed the presence of a PTHR on T2*WIs in 39 pathologically proven HCCs from April 2012 to December 2013. Prussian blue staining was performed, and iron deposition was evaluated by semiquantitative and quantitative methods. Optical density was used in the quantitative methods. The associations between a PTHR on T2*WI and histopathologic peritumoral or background liver iron deposition were analyzed.

RESULTS

A PTHR on T2*WI was observed in 23 of 39 (59%) HCCs. There was no significant difference in the histopathologic fibrous capsule findings (P = 0.394). In the semiquantitative methods, both peritumoral and background liver iron deposition grade were significantly higher in HCCs with a PTHR compared with HCCs without a PTHR (P < 0.001). The mean optical density in HCCs with a PTHR was significantly higher compared with HCCs without a PTHR, in the quantitative peritumoral (42,244.1 ± 20,854.9 vs. 18,739.1 ± 12,258.7, respectively; P < 0.001) and background liver iron deposition analyses (35,554.7 ± 19,854.8 vs. 17,292.4 ± 11,605.8, respectively; P < 0.001). Tumor size (P = 0.005), etiology (P = 0.001), and degree of fibrosis (P = 0.042) were significantly associated with the presence of a PTHR.

CONCLUSIONS

A PTHR in HCCs on T2*WIs was strongly associated with peritumoral iron deposition in the iron-deposited background liver but not with the fibrous capsule.