Diagnostic performance of MR for hepatocellular carcinoma based on LI-RADS v2018, compared with v2017

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.

Lessons learned: strategies for implementing and the ongoing use of LI-RADS in your practice

The establishment of the Liver Imaging Reporting and Data System (LI-RADS) in 2011 provided a comprehensive approach to standardized imaging, interpretation, and reporting of liver observations in patients diagnosed with or at risk for hepatocellular carcinoma (HCC). Each set of algorithms provides criteria pertinent to the various components of HCC management including surveillance, diagnosis, staging, and treatment response supported by a detailed lexicon of terms applicable to a wide range of liver imaging scenarios. Before its widespread adoption, the variability in the terminology of diagnostic criteria and definitions of imaging features led to significant challenges in patient management and made it difficult to replicate findings or apply them consistently. The integration of LI-RADS into the clinical setting has enhanced the efficiency and clarity of communication between radiologists, referring providers, and patients by employing a uniform language that averts miscommunications. LI-RADS has been strengthened with its integration into the American Association for Study of Liver Diseases practice guidelines. We will provide the background on the initial development of LI-RADS and reasons for development to serve as a starting point for conveying the system's benefits and evolution over the years. We will also suggest strategies for the implementation and maintenance of a LI-RADS program will be discussed.

Combining CEUS and CT/MRI LI-RADS major imaging features: diagnostic accuracy for classification of indeterminate liver observations in patients at risk for HCC

PURPOSE

To determine the diagnostic accuracy of combining CEUS and CT/MRI LI-RADS major imaging features for the improved categorization of liver observations indeterminate on both CT/MRI and CEUS.

MATERIALS AND METHODS

A retrospective analysis using a database from a prospective study conducted at 11 centers in North America and Europe from 2018 to 2022 included a total of 109 participants at risk for HCC who had liver observations with indeterminate characterization (LR3, LR-4, and LR-M) on both CEUS and CT/MRI. The individual CEUS and CT/MRI LI-RADS major features were extracted from the original study and analyzed in various combinations. Reference standards included biopsy, explant histology, and follow-up CT/MRI. The diagnostic performance of the combinations of LI-RADS major features for definitive diagnosis of HCC was calculated. A reverse, stepwise logistical regression sub-analysis was also performed.

RESULTS

This study included 114 observations indeterminate on both CT/MRI and CEUS. These observations were categorized as LR-3 (n = 37), LR-4 (n = 41), and LR-M (n = 36) on CT/MRI and LR-3 (n = 48), LR-4 (n = 36), LR-M (n = 29), and LR-TIV (n = 1) on CEUS. Of them, 43.0% (49/114) were confirmed as HCC, 37.3% (43/114) non-malignant, and 19.3% (22/114) non-hepatocellular malignancies. The highest diagnostic accuracy among the combinations of imaging features was achieved in CT/MRI LR-3 observations, where the combination of CEUS arterial phase hyper-enhancement (APHE) + CT/MRI APHE had 96.7% specificity, 75.0% positive predictive value (PPV), and 86.5% accuracy for HCC.

CONCLUSION

The combination of LI-RADS major features on CT/MRI and CEUS showed higher specificity, PPV, and accuracy compared to individual modalities' assessments, particularly for CT/MRI LR-3 observations.

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.

Evidence Supporting Diagnostic Value of Liver Imaging Reporting and Data System for CT- and MR Imaging-based Diagnosis of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis

Background

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

Objective

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

Material and Methods

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

Results

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

Conclusion

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

Up-to-Date Role of Liver Imaging Reporting and Data System in Hepatocellular Carcinoma

This article overviews Liver Imaging Reporting and Data System (LI-RADS), a system that standardizes techniques, interpretation and reporting of imaging studies done for hepatocellular carcinoma surveillance, diagnosis, and locoregional treatment response assessment. LI-RADS includes 4 algorithms, each of which defines ordinal categories reflecting probability of the assessed outcome. The categories, in turn, guide patient management. The LI-RADS diagnostic algorithms provide diagnostic criteria for the entire spectrum of lesions found in at-risk patients. In addition, the use of LI-RADS in clinical care improves clarity of communication between radiologists and clinicians and may improve the performance of inexperienced users to the levels of expert liver imagers.

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.

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.

Efficacy of LR-5 and LR-4/5 by Liver Imaging Reporting and Data System (MRI) for hepatocellular carcinoma: A meta-analysis

To comprehensive investigate the diagnostic efficacy of LR-5 and LR-4/5 by MRI LI-RADS of suspected liver nodules. A comprehensive search of authenticated international databases including PubMed/Medline, Ovid, Embase, Web of Science as well as a series of nation-level databases, including China National Knowledge Infrastructure was carried out to look for related studies with respect to the diagnostic performance of MRI LR-5 or LR-4/5 for HCC. Subsequently, main data including the basic information of the articles incorporated as well as main outcomes, including diagnostic sensitivity, specificity, accuracy, or original data like true positive, false positive, true negative and false negative values were extracted. Next, forest plots were generated to reveal the pooled diagnostic sensitivity, specificity. The diagnostic sensitivity, specificity of LR-5 and LR-4/5 by LI-RADS were comparatively satisfactory. The pooled diagnostic sensitivity and specificity of MRI LR-5 with respect to pathologically diagnosed HCC were 0.73 [95% CI 0.7-0.75] and 0.88 [95% CI 0.86-0.90] respectively. The pooled sensitivity and specificity of MRI LR-4/5 were 0.77 [95% CI 0.75-0.80] and 0.82 [95% CI 0.79-0.85] respectively. Through this systematic review and meta-analysis, we found a promisingly satisfactory diagnostic efficacy of LR-5 and LR-4/5 by MRI LI-RADS of suspected malignant liver nodules, manifested by optimal diagnostic sensitivity, specificity, and accuracy.

Identification of the origin of tumor in vein: comparison between CEUS LI-RADS v2017 and v2016 for patients at high risk

Objectives

To compare the diagnostic performance of the Contrast-Enhanced Ultrasound (CEUS) Liver Imaging Report and Data System (LI-RADS) v2016 and v2017 in identifying the origin of tumor in vein (TIV).

Methods

From April 2014 to December 2018, focal liver lesions (FLLs) accompanied by TIV formation in patients at high risk for hepatocellular carcinoma (HCC) were enrolled. Histologic evaluation or composite imaging reference standard were served as the reference standard. Each case was categorized according to the CEUS LI-RADS v2016 and v2017, respectively. Diagnostic performance of CEUS LI-RADS v2016 and v2017 in identifying the originated tumor of TIV was validated via sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value.

Results

A total of 273 FLLs with TIV were analyzed finally, including 266 HCCs and 7 non-HCCs. In v2016, when adopting all TIV as LR-5V, the accuracy and PPV in identifying the originated tumor were both 97.4%. In v2017, when assigning TIV according to contiguous FLLs CEUS LI-RADS category, the accuracy and PPV were 61.9% and 99.4% in subclass of LR-5 as the diagnostic criteria of HCC, and 64.1% and 99.4% in subclass of LR-4/5 as the criteria of HCC diagnosis. There were significant differences in diagnostic accuracy between CEUS LI-RADS v2016 and v2017 in identifying the originated tumor of TIV (p < 0.001).

Conclusions

CEUS LI-RADS v2016 could be better than v2017 in identifying the originated tumor of TIV.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00912-4.

A gadoxetic acid-enhanced MRI-based multivariable model using LI-RADS v2018 and other imaging features for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma

PURPOSE

To identify imaging features of macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) using LI-RADS v2018 and other imaging features and to develop a gadoxetic acid-enhanced MRI (EOB-MRI)-based model for pretreatment prediction of MTM-HCC.

MATERIALS AND METHODS

A total of 93 patients with pathologically proven HCC (39 MTM-HCC and 54 non-MTM-HCC) were retrospectively evaluated with EOB-MRI at 3 T. Imaging analysis according to LI-RADS v2018 was evaluated by two readers. Univariate and multivariate analyses were performed to determine independent predictors for MTM-HCC. Different logistic regression models were built based on MRI features, including model A (enhancing capsule, blood products in mass and ascites), model B (enhancing capsule and ascites), model C (blood products in mass and ascites), and model D (blood products in mass and enhancing capsule). Diagnostic performance was assessed by receiver operating characteristic (ROC) curves.

RESULTS

After multivariate analysis, absence of enhancing capsule (odds ratio = 0.102, p = 0.010), absence of blood products in mass (odds ratio = 0.073, p = 0.030), and with ascites (odds ratio = 55.677, p = 0.028) were identified as independent differential factors for the presence of MTM-HCC. Model A yielded a sensitivity, specificity, and AUC of 35.90% (21.20,52.80), 94.44% (84.60, 98.80), and 0.731 (0.629, 0.818). Model A achieved a comparable AUC than model D (0.731 vs. 0.699, p = 0.333), but a higher AUC than model B (0.731 vs. 0.644, p = 0.048) and model C (0.731 vs. 0.650, p = 0.005).

CONCLUSION

The EOB-MRI-based model is promising for noninvasively predicting MTM-HCC and may assist clinicians in pretreatment decisions.

Risk Stratification and Distribution of Hepatocellular Carcinomas in CEUS and CT/MRI LI-RADS: A Meta-Analysis

Background

CEUS LI-RADS and CT/MRI LI-RADS have been used in clinical practice for several years. However, there is a lack of evidence-based study to compare the proportion of hepatocellular carcinomas (HCCs) in each category and the distribution of HCCs of these two categorization systems.

Purpose

The purpose of this study was to compare the proportion of HCCs between corresponding CEUS LI-RADS and CT/MRI LI-RADS categories and the distribution of HCCs and non-HCC malignancies in each category.

Methods

We searched PubMed, Embase, and Cochrane Central databases from January 2014 to December 2021. The proportion of HCCs and non-HCC malignancies and the corresponding sensitivity, specificity, accuracy, diagnostic odds ratio (DOR), and area under the curve (AUC) of the LR-5 and LR-M categories were determined using a random-effect model.

Results

A total of 43 studies were included. The proportion of HCCs in CEUS LR-5 was 96%, and that in CECT/MRI LR-5 was 95% (p > 0.05). The proportion of non-HCC malignancy in CEUS LR-M was lower than that of CT/MRI LR-M (35% vs. 58%, p = 0.01). The sensitivity, specificity, and accuracy of CEUS LR-5 for HCCs were 73%, 92%, and 78%, respectively, and of CT/MRI LR-5 for HCCs, 69%, 92%, and 76%, respectively.

Conclusion

With the upshift of the LI-RADS category, the proportion of HCCs increased. CEUS LR-3 has a lower risk of HCCs than CT/MRI LR-3. CEUS LR-5 and CT/MRI LR-5 have a similar diagnostic performance for HCCs. CEUS LR-M has a higher proportion of HCCs and a lower proportion of non-HCC malignancies compared with CT/MRI LR-M.

MRI-diagnosis of category LR-M observations in the Liver Imaging Reporting and Data System v2018: a systematic review and meta-analysis

OBJECTIVES

We performed a meta-analysis to determine the probability of hepatocellular carcinoma (HCC) and non-HCC malignancies in Liver Imaging Reporting and Data System (LI-RADS) category M (LR-M) observations and the frequency of defined LR-M imaging features on MRI using LI-RADS v2018.

METHODS

We searched the MEDLINE and EMBASE databases to identify studies published from 1 January 2018 to 16 March 2021 reporting the probability of category LR-M in HCC and non-HCC malignancies on MRI. The pooled percentages of HCC and non-HCC malignancies in the LR-M observations were evaluated. Meta-regression analysis was performed to identify factors for study heterogeneity. The frequencies of defined LR-M imaging features were also calculated. Risk of bias and concerns regarding applicability were evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

RESULTS

We identified 18 studies reporting the diagnostic performance of the LR-M category (3,812 observations in 3,615 patients), with nine studies reporting the frequencies of LR-M imaging features. The pooled percentages of HCC and non-HCC malignancies in the LR-M observations were 29% (95% confidence interval [CI], 21-38%) and 67% (95%CI, 57-77%), respectively. The study type and inclusion of benign lesions were significant factors for study heterogeneity. Of the 10 LR-M imaging features, rim arterial phase hyperenhancement (APHE) showed the highest frequency in non-HCC malignancies (68%; 95%CI, 61-75%).

CONCLUSIONS

The LR-M category was commonly used to characterize non-HCC malignancies, but also included 29% of HCC. The frequencies of the different LR-M imaging features were variable, with rim APHE showing the highest frequency in non-HCC malignancies.

KEY POINTS

• In the LR-M category using LI-RADS v2018 for MRI, the pooled percentage of malignancies in general was 96%, with 29% HCC and 67% non-HCC malignancies, while the remaining 4% was benign entity. • The study type and inclusion of benign lesions were significant factors contributing to substantial heterogeneity among included studies. • The frequencies of the different LR-M imaging features were variable, with rim APHE showing the highest frequency in non-HCC malignancies.

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.

Tumor in vein (LR-TIV) and liver imaging reporting and data system (LI-RADS) v2018: diagnostic features, pitfalls, prognostic and management implications

Vascular invasion by hepatocellular carcinoma (HCC), also known as tumor in vein (TIV), indicates highly invasive tumor behavior and is also associated with poor outcome. Because a diagnosis of TIV precludes liver transplantation, knowledge of the imaging findings to differentiate between TIV and bland thrombus is key for proper patient management. Prior versions of liver imaging reporting and data system (LI-RADS) included presence of TIV as part of LR-5 criteria. However, even if HCC is the most common liver malignancy associated with TIV, other tumors can have vascular invasion and may occur in cirrhotic patients. For these reasons, in LI-RADS v2017 LR-TIV has been introduced as a new different diagnostic category. The aim of this article is to discuss the diagnostic criteria of LR-TIV according to LI-RADS v2018 and analyze potential pitfalls encountered on daily clinical practice. Indeterminate cases and how to manage them will also be discussed.

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.

Hepatobiliary phase signal intensity: A potential method of diagnosing HCC with atypical imaging features among LR-M observations

Herein, we assessed whether hepatobiliary phase (HBP) signal intensity (SI) can be used to differentiate HCC and non-HCC malignancies within LR-M observations. 106 LR-M patients based on LI-RADS v2018 who underwent gadoxetate-disodium magnetic resonance imaging and surgery from January 2009 to December 2018 were included. SI of LR-M observation on HBP was analyzed by two radiologists and categorized into dark, low and iso-to-high groups. Tumor was classified as dark when more than 50% of tumor showed hypointensity compared to spleen, as low when more than 50% of tumor showed hyperintensity compared to spleen but hypointensity compared to liver parenchyma, and as iso-to-high if there was even a focal iso-intensity or hyperintensity compared to liver parenchyma. Analysis of clinicopathological factors and association between imaging and histology was performed. Out of 106 LR-M, 42 (40%) were showed dark, 61 (58%) showed low, and 3 (3%) showed iso-to-high SI in HBP. Three iso-to-high SI LR-M were HCCs (P = 0.060) and their major histologic differentiation was Edmondson grade 1 (P = 0.001). 43 out of 61 (71%) low SI LR-M were iCCA or cHCC-CCA (P = 0.002). Inter-reader agreement of HBP SI classification was excellent, with a kappa coefficient of 0.872. LR-M with iso-to-high SI in HBP is prone to being HCC while LR-M with low SI in HBP is prone to being tumor with fibrous stroma such as iCCA and cHCC-CCA. Classification of LR-M based on HBP SI may be a helpful method of differentiating HCC from non-HCC malignancies.

Differentiation of hepatocellular carcinoma from intrahepatic cholangiocarcinoma and combined hepatocellular-cholangiocarcinoma in high-risk patients matched to MR field strength: diagnostic performance of LI-RADS version 2018

PURPOSE

To eliminate the effects of field strength in determining the diagnostic performance of the LI-RADS version 2018 (LI-RADS v2018) in differentiating hepatocellular carcinoma (HCC) from non-HCC primary liver malignancy in high-risk patients.

METHODS

Patients who were pathologically confirmed intrahepatic cholangiocarcinoma (iCCA) or combined hepatocellular-cholangiocarcinoma (cHCC-CCA) were retrospectively reviewed. Patients with HCC were matched to the iCCA or cHCC-CCA patients on age, tumor size, MR scanner, and number of tumors. Two readers independently evaluated the lesions according to LI-RADS v2018. Diagnostic performance of LI-RADS v2018 in differentiating HCC from non-HCC primary liver malignancy were analyzed.

RESULTS

A total of 198 patients with 204 lesions (102 HCCs, 78 iCCAs, and 24 cHCC-CCAs) were enrolled. The sensitivity and specificity of LR-5 or LR-TIV (definitely due to HCC) in diagnosing HCC were 68.63% and 85.29%, respectively. LR-M or LR-TIV (may be due to non-HCC malignancy) had a sensitivity of 72.55% and a specificity of 86.27% in diagnosing non-HCC malignancy. The sensitivity of LR-M or LR-TIV (may be due to non-HCC malignancy) for iCCA and cHCC-CCA was 82.05% and 41.67%, respectively. Nearly half (11/24, 45.83%) of cHCC-CCAs were categorized as LR-5. Three tesla MR showed higher sensitivity than 1.5 T in diagnosing HCC (80.00% vs 57.69%, P = 0.015).

CONCLUSION

When the effect of field strength was eliminated, LI-RADS v2018 demonstrated high specificity but suboptimal sensitivity in distinguishing HCC from non-HCC primary liver carcinomas. Most iCCAs were categorized as LR-M or LR-TIV (may be due to non-HCC malignancy). However, nearly half of cHCC-CCAs were assigned as LR-5.

Up-to-Date Role of CT/MRI LI-RADS in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of mortality worldwide and a major healthcare burden in most societies. Computed tomography (CT) and magnetic resonance imaging (MRI) play a pivotal role in the medical care of patients with or at risk for hepatocellular carcinoma (HCC). When stringent imaging criteria are fulfilled, CT and MRI allow for diagnosis, staging, and assessment of response to treatment, without the need for invasive workup, and can inform clinical decision making. Owing to the central role of these imaging modalities in HCC management, standardization is essential to facilitate proper imaging technique, accurate interpretation, and clear communication among all stakeholders in both the clinical practice and research settings. The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system that provides standardization across the continuum of HCC imaging, including ordinal probabilistic approach for reporting that directs individualized management. This review discusses the up-to-date role of CT and MRI in HCC imaging from the LI-RADS perspective. It also provides a glimpse into the future by discussing how advances in knowledge and technology are likely to enrich the LI-RADS approach.

Diagnosis and treatment of hepatocellular carcinoma. Update of the consensus document of the AEEH, AEC, SEOM, SERAM, SERVEI, and SETH

Hepatocellular carcinoma (HCC) is the most common primary liver neoplasm and one of the most common causes of death in patients with cirrhosis of the liver. In parallel, with recognition of the clinical relevance of this cancer, major new developments have recently appeared in its diagnosis, prognostic assessment and in particular, in its treatment. Therefore, the Spanish Association for the Study of the Liver (AEEH) has driven the need to update the clinical practice guidelines, once again inviting all the societies involved in the diagnosis and treatment of this disease to participate in the drafting and approval of the document: Spanish Society for Liver Transplantation (SETH), Spanish Society of Diagnostic Radiology (SERAM), Spanish Society of Vascular and Interventional Radiology (SERVEI), Spanish Association of Surgeons (AEC) and Spanish Society of Medical Oncology (SEOM). The clinical practice guidelines published in 2016 and accepted as National Health System Clinical Practice Guidelines were taken as the reference documents, incorporating the most important recent advances. The scientific evidence and the strength of the recommendation is based on the GRADE system.

Assessment of SE-MRE-derived shear stiffness at 3.0 Tesla for solid liver tumors characterization

OBJECTIVES

To evaluate the feasibility and diagnostic value of using a 2D spin-echo MR elastography (SE-MRE) sequence at 3.0 Tesla for solid focal liver lesions (FLL) characterization.

METHODS

This prospective study included 55 patients with solid FLL (size > 20 mm), who underwent liver SE-MRE at 3 Tesla between 2016 and 2019. Stiffness measurements were performed by two independent readers blinded to the complete MRI exam or patient information. Histological confirmation or typical behavior on the complete MRI exam evaluated in consensus by expert abdominal radiologists was used as reference standard. FLLs were grouped and compared (malignant vs. benign) using the Mann-Whitney and Kruskal-Wallis tests. MRE diagnostic performance was assessed, and stiffness cutoffs were obtained by analysis of ROC curves from accuracy maximization. A linear regression plot was used to evaluate inter-rater agreement for FLLs stiffness measurements. p values < 0.05 were considered statistically significant.

RESULTS

The final study group comprised 57 FLLs (34 malignant, 23 benign). Stiffness measurements were technically successful in 91.23% of lesions. To both readers, the median stiffness of the lesions categorized as benign was 4.5 ± 1.5 kPa and in the malignant group 6.8 ± 1.7 and 7.5 ± 1.5 kPa depending on the reader. A cutoff of 5.8 kPa distinguished malignant and benign lesions with 88% specificity and 75-85% accuracy depending on the reader. The inter-rater agreement was 0.90 ± 0.04 with a correlation coefficient of 0.94.

CONCLUSION

2D-SE-MRE at 3.0 T provides high specificity and PPV to differentiate benign from malignant liver lesions. Trial registration 18FFUA-A02.

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.

Multi-arterial phase MRI depicts inconsistent arterial phase hyperenhancement (APHE) subtypes in liver observations of patients at risk for hepatocellular carcinoma

OBJECTIVES

According to LI-RADS, a major discriminating feature between hepatocellular carcinoma (HCC) and non-HCC malignancies is the subtype of arterial phase hyperenhancement (APHE). The aim of this study was to investigate whether APHE subtypes are consistent across multi-arterial phase (mHAP) MRI acquisitions while evaluating reader agreement. Secondarily, we investigated factors that may affect reader agreement for APHE subtype.

METHODS

In this retrospective study, consecutive patients with liver cirrhosis and focal observations who underwent mHAP were included. Five radiologists reviewed MR images in 2 reading sessions. In reading session 1, individual AP series were reviewed and scored for presence of APHE and subtype. In reading session 2, readers scored observations' major and ancillary features and LI-RADS category in the complete MRI examination. Reader agreement was calculated using Fleiss' kappa for binary outcomes and Kendall's coefficient of concordance for LI-RADS categories. Univariate mixed effects logistic regressions were performed to investigate factors affecting agreement.

RESULTS

In total, 61 patients with 77 focal observations were analyzed. Of observations unanimously scored as having APHE, 27.7% showed both rim and nonrim subtypes on mHAP. Inter-reader agreement for APHE subtype ranged from 0.49 (95% CI: 0.33, 0.64) to 0.57 (95% CI: 0.40, 0.74) between reading sessions. Observation size had a trend level effect on rim APHE agreement (p = 0.052).

CONCLUSION

Approximately 1/3 of observations demonstrated inconsistent APHE subtype during mHAP acquisition. Small lesions were particularly challenging. Further guidance on APHE subtype classification, especially when applied to mHAP, could be a focus of LI-RADS refinement.

KEY POINTS

• In a cohort of patients at risk for HCC, 28% of the observations showed inconsistent arterial phase hyperenhancement (APHE) subtypes (rim and nonrim) on multi-arterial phase imaging according to the majority score of 5 independent readers. • Inconsistent APHE subtypes may challenge reliable imaging diagnosis, i.e., LI-RADS categorization, of focal liver observations in patients at risk for HCC.

Increasing the sensitivity of LI-RADS v2018 for diagnosis of small (10-19 mm) HCC on extracellular contrast-enhanced MRI

PURPOSE

To evaluate whether the LI-RADS v2018 LR-5 criteria can be modified to increase sensitivity without reducing specificity for diagnosing small (10-19 mm) HCC.

METHODS

167 consecutive high-risk patients with 174 small observations reported clinically on extracellular contrast-enhanced MRI from 2014 to 2018 were retrospectively studied. The best available reference standard was applied for each observation. Blinded to the reference standard, two radiologists scored LI-RADS imaging features retrospectively and assigned each observation a LI-RADS category using LI-RADS v2018 and each of four modified LI-RADS versions (mLI-RADS I to IV) with successively more expansive LR-5 criteria. Per-observation sensitivity and specificity of LR-5 for small HCC using each version were assessed. Each modified version was compared to v2018 (McNemar test).

RESULTS

The 174 observations included 135 HCC, 8 non-HCC malignancies, and 31 benign entities. Using LI-RADS v2018, LR-5 provided 70% (both readers) sensitivity and 95% (both readers) specificity for small HCC. Expanding the LR-5 criteria to include nonrim APHE plus at least one additional major feature (mLI-RADS I) or no APHE plus at least two additional major features (mLI-RADS II) significantly increased sensitivity (reader 1/reader 2: 75%/75% vs. 70%, p = 0.016/0.031; 78%/79% vs. 70%, p = 0.001/0.001) without significantly reducing specificity (reader 1/reader 2: 90%/92% vs. 95%, p = 0.500/1.000 for both). mLI-RADS III and IV further increased sensitivity (reader 1/reader 2: 80%/81% vs. 70%, p < 0.001/< 0.001; 94%/92% vs. 70, p < 0.001/< 0.001) but with trend-level (reader 1/reader 2: 85%/80% vs. 95%, p = 0.125/0.063) or significant (reader 1/reader 2: 64%/62% vs. 95%, p < 0.001/< 0.001) specificity reductions.

CONCLUSIONS

Expanding the v2018 LR-5 criteria to include nonrim APHE plus at least one additional major feature or no APHE plus at least two additional major features significantly increases sensitivity without significantly reducing specificity for small HCC. Confirmation is warranted in multi-center prospective studies.

Clinical Application of Liver Imaging Reporting and Data System for Characterizing Liver Neoplasms: A Meta-Analysis

The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing liver imaging in patients at risk of developing hepatocellular carcinoma (HCC). We aimed to determine the diagnostic performance of LI-RADS category 5 (LR5) for diagnosing HCC and LI-RADS category M (LRM) for characterizing other non-HCC malignancies (OM) using contrast-enhanced ultrasound (CEUS) and computed tomography (CT)/magnetic resonance imaging (MRI). Multiple databases were searched for articles evaluating the diagnostic accuracy of CEUS LI-RADS and/or CT/MRI LI-RADS. A random-effects model was adopted to synthesize the summary estimates of the diagnostic accuracy of LR5 for diagnosing HCC and LRM for characterizing OM using CEUS and CT/MRI. The pooled sensitivity and specificity of CEUS LR5 for the diagnosis of HCC were 69% and 93%, respectively. The pooled sensitivity was 67% and the specificity, 93% of CT/MRI LR5 for HCC diagnosis. There was no significant difference between the overall diagnostic accuracy for HCC diagnosis of CEUS LR5 and that of CT/MRI LR5 in terms of diagnostic odds ratio (DOR) (p = 0.55). The sensitivity was 84% with a specificity of 90% in the CEUS LRM for characterizing OM, while the sensitivity and specificity of CT/MRI LRM for characterizing OM was 63% and 95%. The DOR of CEUS LRM for characterizing OM was higher than that of CT/MRI LRM without significant difference (50.59 vs. 36.06, p = 0.34). This meta-analysis indicated that CEUS LI-RADS is qualified to characterize HCC and OM and may provide complementary information on liver nodules to CT/MRI LI-RADS.

MRI LI-RADS Version 2018: Impact of and Reduction in Ancillary Features

OBJECTIVE. The purpose of this study is to determine the impact of LI-RADS ancillary features on MRI and to ascertain whether the number of ancillary features can be reduced without compromising LI-RADS accuracy. MATERIALS AND METHODS. A total of 222 liver observations in 81 consecutive patients were identified on MRI between August 2013 and December 2018. The presence or absence of major and ancillary features was used to determine the LI-RADS category for LR-1 to LR-5 observations. Final diagnosis was established on the basis of pathologic findings or one of several composite clinical reference standards. Diagnostic accuracy was compared with and without ancillary features by use of the z test of proportions. Decision tree analysis and machine learning-based feature pruning were used to identify noncontributory ancillary features for LI-RADS categorization. Interobserver agreement with and without ancillary features was measured using the Krippendorff alpha coefficient, and comparisons were made using bootstrapping. A p < .05 was considered statistically significant. RESULTS. Application of ancillary features resulted in a change in the LI-RADS category of seven hepatocellular carcinomas (HCCs), with the category of six of seven (86%) HCCs upgraded; 51 benign observations also had a change in LI-RADS category, with the category of 33 (65%) of these observations downgraded. When ancillary features were applied, the percentage of HCCs in each LI-RADS category did not differ significantly compared with major features alone (p = .06-.49). Decision tree analysis and the machine learning model identified five ancillary features as noncontributory: corona enhancement, nodule-in-nodule, mosaic architecture, blood products in mass, and fat in a mass, more than in adjacent liver. Interobserver agreement was high with and without application of ancillary features; however, it was significantly higher without ancillary features (p < .001). CONCLUSION. Although ancillary features are an important component of LI-RADS, their impact may be small. Several ancillary features likely can be removed from LI-RADS without compromising diagnostic performance.

LI-RADS and transplantation: challenges and controversies

Patients with early stage hepatocellular carcinoma (HCC) can be cured by liver transplantation. HCC imaging features on CT or MRI are specific enough to allow for definitive diagnosis and treatment without the need of confirmatory biopsy. When applied to the appropriate at-risk population the Liver Imaging Reporting and Data System (LI-RADS) imaging criteria achieve high specificity and positive predictive value for the diagnosis of HCC. The Organ Procurement and Transplantation Network (OPTN) is the United States organization that aims to assure the adequate and fair distribution of livers across candidates. Given the importance of fair organ allocation, OPTN also provides stringent imaging criteria for the diagnosis of HCC aiming to avoid false positive diagnosis. Although most imaging criteria are identical for both systems, discrepancies between LI-RADS and the current OPTN classification system for HCC diagnosis exists. Main differences include, but are not limited to, the binary approach of OPTN to classify lesions as HCC or not, versus the probabilistic algorithmic approach of LI-RADS, technical and interpretation considerations, and the approach towards treated lesions. The purpose of this article is to highlight the similarities and discrepancies between LI-RADS and the current OPTN criteria for HCC diagnosis and the implications that these differences may have on the management of patients who are transplant candidates.

Diagnostic performance of the LR-M criteria and spectrum of LI-RADS imaging features among primary hepatic carcinomas

PURPOSE

To evaluate the diagnostic performance of LR-M criteria for differentiating hepatocellular carcinoma, intrahepatic mass-forming cholangiocarcinoma, and combined hepatocellular-cholangiocarcinoma and to compare the imaging features of each type.

METHODS

In this retrospective study, 110 patients were surgically diagnosed with cholangiocarcinoma (n = 67) and combined hepatocellular-cholangiocarcinoma (n = 43) at a single tertiary hospital between 2013 and 2018. Among them, those with risk factors were enrolled (16 cholangiocarcinomas and 33 combined hepatocellular-cholangiocarcinomas). Forty-nine other patients with size-matched hepatocellular carcinoma were selected as a control group. Two independent readers evaluated the imaging findings of the preoperative MRIs based on LI-RADS version 2018 and assigned an LI-RADS category. The diagnostic performance of the LR-M criteria for diagnosing cholangiocarcinoma or combined hepatocellular-cholangiocarcinoma was evaluated, and the imaging features were compared. The imaging findings of the tumors in patients without risk factors (51 cholangiocarcinomas and 10 combined hepatocellular-cholangiocarcinomas) were evaluated for subgroup analysis.

RESULTS

In the non-hepatocellular carcinoma group, 33 patients were categorized into LR-M and 14 patients into LR-5 (67.3% and 28.6%, respectively), while 5 patients with hepatocellular carcinoma were categorized into LR-M and 38 patients into LR-5 (10.2% and 77.6%, respectively). Sensitivity and specificity of the LR-M criteria were 67.3% and 89.8%, respectively. When more than two LR-M features were present, cholangiocarcinoma or combined hepatocellular-cholangiocarcinoma were suggested with a specificity of 95.9%.

CONCLUSION

The diagnostic performance of the LR-M criteria is acceptable with moderate sensitivity and high specificity for both cholangiocarcinoma and combined hepatocellular-cholangiocarcinoma. Imaging findings of primary hepatic carcinomas should be understood as a spectrum.

Imaging Diagnosis of Hepatocellular Carcinoma: The Liver Imaging Reporting and Data System, Why and How?

The Liver Imaging Reporting and Data System (LI-RADS) provides standardized lexicon, technique, interpretation, and reporting of liver imaging in patients at risk for hepatocellular carcinoma (HCC). When applied to at-risk populations, LI-RADS achieves higher than 95% positive predictive value for the noninvasive diagnosis of HCC on computed tomography (CT), MRI and contrast-enhanced ultrasound (CEUS). This article focuses on similarities and differences between the CT/MRI diagnostic algorithm (CT/MRI LI-RADS) and the CEUS diagnostic algorithm (CEUS LI-RADS) to inform health care professionals for efficient and appropriate clinical decisions through the management of patients at risk.

Diagnostic performance of Liver Imaging Reporting and Data System in patients at risk of both hepatocellular carcinoma and metastasis

OBJECTIVE

The purpose of this study was to evaluate the diagnostic performance of the Liver Imaging Reporting and Data System (LI-RADS) in patients with both chronic liver disease and a history of extrahepatic malignancy.

MATERIALS AND METHODS

This retrospective study included 59 hepatocellular carcinomas (HCCs) and 45 metastases pathologically confirmed between 2008 and 2017 in 104 patients with chronic liver disease (cirrhosis or chronic hepatitis B) and a history of extrahepatic malignancy. Two radiologists blinded to the final diagnosis independently reviewed MRI (95 patients) or CT (9 patients) images, and their consensus data were used to calculate the diagnostic performance of LI-RADS categories. Serum tumor markers, tumor multiplicity, and suspected metastatic lymph nodes were also evaluated.

RESULTS

The sensitivity, specificity, and accuracy of LR-5 for diagnosing HCC were 69% (95% confidence intervals [CI] 56-81), 98% (95% CI 88-99), and 82% (95% CI 73-89), respectively, and those of LR-M for diagnosing metastasis were 89% (95% CI 76-96), 88% (95% CI 77-95), and 88% (95% CI 81-94), respectively. Elevation of serum carcinoembryonic antigen (P = 0.01) or carbohydrate antigen 19-9 levels (P = 0.02) and tumor multiplicity (P = 0.004) were more frequently observed in metastasis than in HCC. Three of four metastases categorized as LR-4 or LR-5 were smaller than 2 cm.

CONCLUSIONS

The LI-RADS provides high specificity (98%) for differentiating HCC from metastases in patients with both chronic liver disease and a history of extrahepatic malignancy.

The Liver Imaging Reporting and Data System tumor-in-vein category: a systematic review and meta-analysis

OBJECTIVES

We aimed to systematically determine the etiology of the Liver Imaging Reporting and Data System (LI-RADS) tumor-in-vein category (LR-TIV) on contrast-enhanced CT or MRI and to determine the sources of heterogeneity between reported results.

METHODS

Original studies reporting the etiology of LR-TIV were identified in MEDLINE and EMBASE up until July 7, 2020. The meta-analytic pooled percentages of HCC and non-HCC in LR-TIV were calculated. Subgroup analyses were performed according to the type of reference standard and the most common underlying liver disease. Meta-regression analysis was performed to explore study heterogeneity.

RESULTS

Sixteen studies reported the etiology of a total of 150 LR-TIV, of which 98 (65%) were HCC and 52 (35%) were non-HCC. The meta-analytic pooled percentages of HCC and non-HCC in LR-TIV were 70.9% (95% confidence interval [CI], 55.7-82.5%; I² = 59%) and 29.2% (95% CI, 17.5-44.4%; I² = 59%), respectively. The meta-analytic pooled percentage of HCC was lower in studies using only pathology as a reference standard (67.1%; 95% CI, 49.3-81.1%), but higher in studies in which hepatitis C was the most common underlying liver disease (81.9%; 95% CI, 11.3-99.4%) than that in the total 16 studies. Study type (cohort study versus case-control study) was significantly associated with study heterogeneity (p = 0.04).

CONCLUSION

The most common etiology of LR-TIV was HCC. It might be important to understand the percentage of HCC and non-HCC in LR-TIV in consideration of the type of reference standard, geographic differences, and study design.

KEY POINTS

• The most common etiology of Liver Imaging Reporting and Data System (LI-RADS) tumor-in-vein category (LR-TIV) was hepatocellular carcinoma (HCC). • The percentage of HCC in LR-TIV was relatively low in studies using only pathology as a reference standard, but high in studies in which hepatitis C was the most common underlying liver disease. • Study type was a factor significantly influencing study heterogeneity.

Diagnostic Performance of LI-RADS Version 2018, LI-RADS Version 2017, and OPTN Criteria for Hepatocellular Carcinoma

OBJECTIVE. Liver Imaging Reporting and Data System (LI-RADS) was updated in 2018 (LI-RADS version 2018 [LI-RADSv2018]) to facilitate integration into the American Association for the Study of Liver Diseases 2018 clinical practice guidelines and involved changes in LR-5 categorization and threshold growth definitions. There are also differences between the criteria for LI-RADSv2018 LR-5 category and the criteria for Organ Procurement and Transplantation Network (OPTN) class 5. The objective of our study was to compare the diagnostic performances of LI-RADSv2018, LI-RADS version 2017 (LI-RADSv2017), and OPTN criteria for diagnosing hepatocellular carcinoma (HCC) on MRI. MATERIALS AND METHODS. In this retrospective study, 122 patients with 159 observations were included who met LI-RADS criteria for at risk for HCC and had at least one hepatic observation on MRI performed between January 1, 2015, and January 1, 2018 and who had histopathology results (n = 104) or follow-up imaging (n = 55) as reference standards. Three abdominal radiologists assigned categories independently and in consensus using LI-RADSv2017, LI-RADSv2018, and OPTN criteria. Diagnostic performance was compared among the guidelines with a generalized estimating equation. RESULTS. Fourteen of 159 (8.8%) observations were assigned a different category according to LI-RADSv2018 compared with LI-RADSv2017. Eight of 31 (25.8%) LR-4 observations using v2017 were recategorized as LR-5 using v2018, and all eight were HCC. Six of 31 (19.4%) LR-4 observations based on v2017 were recategorized as LR-3 using v2018, and all six were non-HCCs. Seven of 114 (6.1%) observations not meeting OPTN class 5 criteria were LR-5 using v2018, and all seven were HCC. Sensitivity for HCC of LR-5 and LR-TIV+5 (i.e., LR-TIV [tumor in vein] definitely due to HCC) categories based on v2018 was significantly higher than that based on v2017 (63.9% vs 55.2%, respectively; p = 0.008) without a difference in specificity (97.3% vs 97.3%; p = 1.00). Sensitivity of LR-5 and LR-TIV+5 in LI-RADSv2018 was significantly higher than the sensitivity of class 5 in OPTN criteria (63.9% vs 53.6%; p = 0.004) without a difference in specificity (97.3% vs 97.3%; p = 1.00). Reader agreement was moderate for overall LIRADSv2017 and LI-RADSv2018 categories (κ = 0.504 and 0.561, respectively); substantial for LR-5 and LR-TIV+5 categories as diagnostic of HCC versus other categories for both v2017 and v2018 (κ = 0.758 and 0.802, respectively); and substantial for OPTN class 5 criteria (κ = 0.756). CONCLUSION. The diagnostic performance of LI-RADSv2018 is higher, with higher sensitivity and similar specificity, than the diagnostic performance of LI-RADSv2017 and OPTN criteria for HCC.

Intra-individual comparison of dual portal venous phases for non-invasive diagnosis of hepatocellular carcinoma at gadoxetic acid-enhanced liver MRI

OBJECTIVES

To compare the diagnostic performances of first and second portal venous phases (PVP1 and PVP2) in revealing washout and capsule appearance for non-invasive HCC diagnoses in gadoxetic acid-enhanced MRI (Gd-EOB-MRI).

METHODS

This retrospective study included 123 at-risk patients with 160 hepatic observations (HCCs, n = 116; non-HCC malignancies, n = 18; benign, n = 26) showing arterial phase hyper-enhancement (APHE) ≥ 1 cm at Gd-EOB-MRI. The mean time intervals from gadoxetic acid injection to PVP1 and PVP2 acquisitions were 53 ± 2 s and 73 ± 3 s, respectively. After evaluating image findings independently, imaging findings and diagnoses were finalized by a consensus of two radiologists using either PVP1 or PVP2 image sets according to the LI-RADS v2018 or EASL criteria. Sensitivity, specificity, and accuracy were compared.

RESULTS

Among HCCs, more washout and enhancing capsule were observed in PVP2 (83.6% and 27.6%) than in PVP1 (50.9% and 19.8%) (p < 0.001, both). The PVP2 set presented significantly higher sensitivity (83.6% vs. 53.5%, LI-RADS; 82.8% vs. 50.0%, EASL; p < 0.001, both) and accuracy (0.88 vs. 0.73, LI-RADS; 0.88 vs. 0.72, EASL; p < 0.001, both) than the PVP1 set without significant specificity loss (93.2% vs. 93.2%, by LI-RADS or EASL; p = 0.32, both). None of the non-HCC malignancy was non-invasively diagnosed as HCC in both PVP image sets.

CONCLUSION

Late acquisition of PVP detected washout and enhancing capsule of HCC more sensitively than early acquisition, enabling accurate diagnoses of HCC, according to LI-RADS or EASL criteria.

KEY POINTS

• Among HCCs, more washout and enhancing capsules were observed in PVP2 than PVP1, quantitatively and qualitatively. • The portal venous phase acquired at around 70 s after contrast media administration (PVP2) provided significantly higher sensitivity and AUC value than PVP1 by using LI-RADS v2018 or EASL criteria. • More HCCs were categorized as LR-5 in PVP2 than in PVP1 images, and the specificity of PVP2 (93.5%) was comparable with PVP1 (93.5%).

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

PURPOSE

The aim of this study was to determine the diagnostic performance of the LR-5 category for hepatocellular carcinoma (HCC) and the pooled proportion of HCC in each Liver Imaging Reporting and Data System (LI-RADS) category with CT and MRI, using LI-RADS version 2018.

METHODS

The MEDLINE, Embase, and Scopus databases were searched from inception to December 7, 2019, for studies reporting the diagnostic accuracy of LI-RADS version 2018 for HCC. Risk for bias and concerns regarding applicability were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Random-effects models were used to determine the summary estimates of the diagnostic performance of LR-5 and the pooled proportion of HCC for each LI-RADS category.

RESULTS

Fourteen studies were included in the final analysis, consisting of 2,708 observations with 1,841 HCCs. The pooled per-observation sensitivity and specificity of the LR-5 category for diagnosing HCC were 70% (95% confidence interval [CI], 61%-78%) and 91% (95% CI, 89%-93%), respectively. No HCCs were reported for LR-1 and LR-2. The pooled proportions of HCC were 31% (95% CI, 12%-50%) for LR-3, 64% (95% CI, 47%-80%) for LR-4, 95% (95% CI, 93%-96%) for LR-5, 54% (95% CI, 30%-77%) for LR-TIV, and 33% (95% CI, 21%-46%) for LR-M. The proportions of HCC were significantly different among the LI-RADS categories (P = .022).

CONCLUSIONS

The LR-5 category of LI-RADS version 2018 provided moderate sensitivity and high specificity for diagnosing HCC. Higher LI-RADS categories from LR-3 to LR-5 included greater proportions of HCC.

Diagnostic Performance of CT/MRI Liver Imaging Reporting and Data System v2017 for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

BACKGROUND & AIMS

The liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing liver imaging in patients at high risk for hepatocellular carcinoma (HCC). We performed a meta-analysis to determine the diagnostic performance of the LR-5 category for HCC and the pooled proportions of HCCs in each LI-RADS category using CT/MRI LI-RADS v2017.

METHODS

We searched multiple databases for original studies reporting on the diagnostic accuracy of CT/MRI LI-RADS v2017. Random-effects models were used to determine the summary estimates of the diagnostic performance of the LR-5 category and the pooled proportions of HCCs for each LI-RADS category. Risk of bias and concerns regarding applicability were evaluated with the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

RESULTS

Fourteen studies (3 prospective studies and 11 retrospective studies) were included in the final analysis, consisting of 2056 patients, 2589 observations, and 1693 HCCs. The pooled per-observation sensitivity was 67% (95% confidence interval [CI], 62%-72%) with specificity of 92% (95% CI, 88%-95%) in the LR-5 category of CT/MRI LI-RADS v2017 for diagnosing HCC. The pooled proportions of HCCs were 0% (95% CI, 0%-0%) for LR-1, 4% (95% CI, 0%-8%) for LR-2, 34% (95% CI, 23%-44%) for LR-3, 67% (95% CI, 53%-81%) for LR-4, and 92% (95% CI, 87%-96%) for LR-5. The proportions of HCCs were significantly different among LI-RADS categories 1-5 (P = .034).

CONCLUSIONS

The LR-5 category of CT/MRI LI-RADS v2017 shows moderate sensitivity and high specificity for diagnosing HCC. Higher LI-RADS categories contained higher proportions of HCCs.

New Arterial Phase Enhancing Nodules on MRI of Cirrhotic Liver: Risk of Progression to Hepatocellular Carcinoma and Implications for LI-RADS Classification

OBJECTIVE. The purposes of this study were to evaluate the outcome of new arterial phase enhancing nodules at MRI of cirrhotic livers, including clinical and imaging factors that affect progression to hepatocellular carcinoma (HCC), and to assess the diagnostic performance of Liver Imaging Reporting and Data System version 2018 (LI-RADSv2018) versus version 2017 (LI-RADSv2017) in categorizing these nodules. MATERIALS AND METHODS. A database search identified 129 new arterial phase enhancing, round, solid, space-occupying nodules in 79 patients with cirrhosis who underwent surveillance MRI. Three readers assessed the nodules for LI-RADS findings and made assessments based on the 2017 and 2018 criteria. Clinical information and laboratory values were collected. Outcome data were assessed on the basis of follow-up imaging and pathology results. Interreader agreement was assessed. Logistic regression and ROC curve analyses were used to assess the utility of the features for prediction of progression to HCC. RESULTS. Of the 129 nodules, 71 (55%) progressed to HCC. LI-RADSv2017 score, LIRADSv2018 score, and mild-to-moderate T2 hyperintensity were significant independent predictors of progression to HCC in univariate analyses. Serum α-fetoprotein level, hepatitis B or C virus infection as the cause of liver disease, and presence of other HCCs were significant predictors of progression to HCC in multivariate analyses. The rates of progression of LI-RADS category 3 and 4 observations were 38.1% and 57.6%, respectively, for LI-RADSv2017 and 44.4% and 69.9%, respectively, for LI-RADSv2018. CONCLUSION. New arterial phase enhancing nodules in patients with cirrhosis frequently progress to HCC. Factors such as serum α-fetoprotein level and presence of other HCCs are strong predictors of progression to HCC.

Comparison of guidelines for diagnosis of hepatocellular carcinoma using gadoxetic acid-enhanced MRI in transplantation candidates

OBJECTIVES

To compare diagnostic performances of current guidelines for the diagnosis of HCC in LT candidates using gadoxetic acid-enhanced liver MRI (Gd-EOB-MRI).

METHODS

Eighty-one patients (119 HCCs and 35 non-HCCs) who underwent preoperative Gd-EOB-MRI and subsequent LT were included. Per-lesion imaging diagnoses of HCCs were made using four different guidelines (American Association for the Study of Liver Disease (AASLD), European Association for the Study of the Liver (EASL), Asian Pacific Association for the Study of the Liver (APASL), and Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) guidelines, and patient allocation was determined according to Milan criteria (MC). Comparisons of per-lesion sensitivity, specificity, and accuracy of patient allocation between guidelines were performed using logistic regression with generalized estimating equations.

RESULTS

For diagnosis of HCC, AASLD guideline showed highest specificity (97.4%), followed by EASL and KLCA-NCC guidelines (92.1% and 92.1%, p > 0.99 and = 0.15, respectively, in comparison to AASLD), while the specificity of APASL guideline was significantly lower than that of AASLD guideline (78.9% vs. 97.4%, p = 0.006). APASL and KLCA-NCC guidelines (75.9% and 65.6%) showed significantly higher sensitivities than AASLD/EASL guidelines (34.5% and 38.8%, respectively; all ps < 0.001). For organ allocation, KLCA-NCC guideline showed higher accuracy in selecting unsuitable candidates (with non-HCC malignancies or beyond MC HCCs) than EASL guideline (68.4% vs. 31.8%; p = 0.001).

CONCLUSION

For the diagnosis of HCCs using Gd-EOB-MRI, AASLD guideline provided the highest specificity, followed by EASL, KLCA-NCC, and APASL guidelines with statistically significant difference with only APASL guideline. KLCA-NCC guideline provided the most accurate selection of unsuitable LT candidates.

KEY POINTS

• AASLD/LI-RADS showed the highest specificity, followed by EASL and KLCA-NCC guidelines. • APASL and KLCA-NCC guidelines allowed more sensitive diagnoses of HCCs. • KLCA-NCC more accurately classified patients not appropriate transplantation candidates than EASL.

Liver Imaging Reporting and Data System Version 2018: What Radiologists Need to Know

In this article, we aim to review Liver Imaging Reporting and Data System version 18 (LI-RADS v2018). Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. Liver Imaging Reporting and Data System developed for standardizing interpreting, reporting, and data collection of HCC describes 5 major features for accurate HCC diagnosis and several ancillary features, some favoring HCC in particular or malignancy in general and others favoring benignity. Untreated hepatic lesions LI-RADS affords 8 unique categories based on imaging appearance on computed tomography and magnetic resonance imaging, which indicate the possibility of HCC or malignancy with or without tumor in vein. Furthermore, LI-RADS defines 4 treatment response categories for treated HCCs after different locoregional therapy. These continuous recent updates on LI-RADS improve the communication between the radiologists and the clinicians for better management and patient outcome.

Liver Imaging Reporting and Data System (LI-RADS) v2018: Review of the CT/MRI Diagnostic Categories

Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system that provides standardization in the interpretation and reporting of observations in patients at risk of developing hepatocellular carcinoma (HCC). Computed tomography/magnetic resonance imaging (CT/MRI) LI-RADS v2018 includes 8 diagnostic categories, which reflect the probability of benignity, malignancy in general, or HCC specifically. This article reviews the diagnostic categories of CT/MRI LI-RADS v2018, highlighting the key imaging features, diagnostic criteria, and management implications.

Expanding the Liver Imaging Reporting and Data System (LI-RADS) v2018 diagnostic population: performance and reliability of LI-RADS for distinguishing hepatocellular carcinoma (HCC) from non-HCC primary liver carcinoma in patients who do not meet strict LI-RADS high-risk criteria

BACKGROUND

Hepatocellular carcinoma (HCC) can be diagnosed using imaging criteria in patients at high-risk for HCC, according to Liver Imaging Reporting and Data System (LI-RADS) guidelines. The aim of this study was to determine the diagnostic performance and inter-rater reliability (IRR) of LI-RADS v2018 for differentiating HCC from non-HCC primary liver carcinoma (PLC), in patients who are at increased risk for HCC but not included in the LI-RADS 'high-risk' population.

METHODS

This retrospective HIPAA-compliant study included a 10-year experience of pathologically-proven PLC at two liver transplant centers, and included patients with non-cirrhotic hepatitis C infection, non-cirrhotic non-alcoholic fatty liver disease, and fibrosis. Two readers evaluated each lesion and assigned an overall LI-RADS diagnostic category, additionally scoring all major, LR-M, and ancillary features.

RESULTS

The final study cohort consisted of 27 HCCs and 104 non-HCC PLC in 131 patients. The specificity of a 'definite HCC' designation was 97% for reader 1 and 100% for reader 2. The IRR was fair for overall LI-RADS category and substantial for most major features.

CONCLUSION

In a population at increased risk for HCC but not currently included in the LI-RADS 'high-risk' population, LI-RADS v2018 demonstrated very high specificity for distinguishing pathologically-proven HCC from non-HCC PLC.

Characterization of liver nodules in patients with chronic liver disease by MRI: performance of the Liver Imaging Reporting and Data System (LI-RADS v.2018) scale and its comparison with the Likert scale

OBJECTIVES

To evaluate the performance of the LI-RADS v.2018 scale by comparing it with the Likert scale, in the characterization of liver lesions.

METHODS

A total of 39 patients with chronic liver disease underwent MR examination for characterization of 44 liver lesions. Images were independently analyzed by two radiologists using the LI-RADS scale and by another two radiologists using the Likert scale. The reference standard used was either histopathological evaluation or a 4-year MRI follow-up. Receiver operating characteristic analysis was performed.

RESULTS

The LI-RADS scale obtained an accuracy of 80%, a sensitivity of 72%, a specificity of 93%, a positive predictive value (PPV) of 93% and a negative predictive value (NPV) of 70%, while the Likert scale achieved an accuracy of 79%, a sensitivity of 73%, a specificity of 87%, a PPV of 89% and a NPV of 70%. The area under the curve (AUC) was 85% for the LI-RADS scale and 83% for the Likert scale. The inter-observer agreement was strong (k = 0.89) between the LI-RADS evaluators and moderate (k = 0.69) between the Likert evaluators.

CONCLUSIONS

There was no statistically significant difference between the performances of the two scales; nevertheless, we suggest that the LI-RADS scale be used, as it appeared more objective and consistent.

Liver Imaging Reporting and Data System Version 2018: Impact on Categorization and Hepatocellular Carcinoma Staging

The purpose of this study was to assess the concordance in categorization and radiologic T staging using Liver Imaging Reporting and Data System (LI-RADS, LR) version 2017 (v2017), version 2018 (v2018), and the Organ Procurement and Transplantation Network (OPTN) criteria. All magnetic resonance imaging and computed tomography reports using a standardized LI-RADS macro between April 2015 and March 2018 were identified retrospectively. The major features (size, arterial phase hyperenhancement, washout, enhancing capsule, or threshold growth) were extracted from the report for each LR-3, LR-4, and LR-5 observation. Each observation was assigned a new category based on LI-RADS v2017, v2018, and OPTN criteria. Radiologic T stage was calculated based on the size and number of LR-5 or OPTN class 5 observations. Categories and T stages assigned by each system were compared descriptively. There were 398 patients (66.6% male; mean age, 63.4 years) with 641 observations (median size, 14 mm) who were included. A total of 73/182 (40.1%) observations categorized LR-4 by LI-RADS v2017 were up-categorized to LR-5 by LI-RADS v2018 due to changes in the LR-5 criteria, and 4/196 (2.0%) observations categorized as LR-5 by LI-RADS v2017 were down-categorized to LR-4 by LI-RADS v2018 due to changes in the threshold growth definition. The T stage was higher by LI-RADS v2018 than LI-RADS v2017 in 49/398 (12.3%) patients. Compared with the OPTN stage, 12/398 (3.0%) patients were upstaged by LI-RADS v2017 and 60/398 (15.1%) by LI-RADS v2018. Of 101 patients, 5 (5.0%) patients with T2 stage based on LI-RADS v2017 and 10/102 (9.8%) patients with T2 stage based on LI-RADS v2018 did not meet the T2 criteria based on the OPTN criteria. Of the 98 patients with a T2 stage based on OPTN criteria, 2 (2.0%) had a T stage ≥3 based on LI-RADS v2017 and 6 (6.1%) had a T stage ≥3 based on LI-RADS v2018.

User and system pitfalls in liver imaging with LI-RADS

The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver imaging, created specifically for patients at risk for hepatocellular carcinoma. Over the past years, LI-RADS has been progressively implemented into clinical practice, but pitfalls remain related to user error and inherent limitations of the system. User pitfalls include the inappropriate application of LI-RADS to a low-risk patient population, incorrect measurement techniques, inaccurate assumptions about LI-RADS requirements, and improper usage of LI-RADS terminology and categories. System pitfalls include areas of discordance with the Organ Procurement and Transplantation Network (OPTN) as well as pitfalls related to rare ancillary features. This article reviews common user pitfalls in applying LI-RADS v2018 and how to avoid preventable errors and also highlights deficiencies of the current version of LI-RADS and how it might be improved in the future. Level of Evidence:3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2019;50:1673-1686.

A scientometric analysis on hepatocellular carcinoma magnetic resonance imaging research from 2008 to 2017

Background

With the development of new magnetic resonance imaging (MRI) techniques, an increasing number of articles have been published regarding hepatocellular carcinoma magnetic resonance imaging (HCCMRI) in the past decade. However, few studies have statistically analyzed these published articles. In this study, we aim to systematically evaluate the scientific outcomes of HCCMRI research and explore the research hotspots from 2008 to 2017.

Methods

The included articles regarding HCCMRI research from 2008 to 2017 were downloaded from the Web of Science Core Collection and verified by two experienced radiologists. Excel 2016 was used to analyze the literature data, including the publication years and journals. CiteSpace V was used to perform co-occurrence analyses for authors, countries/regions and institutions and to generate the related collaboration network maps. Reference co-citation analysis (RCA) and burst keyword detection were also performed using CiteSpace V to explore the research hotspots in the past decade.

Results

A total of 835 HCCMRI articles published from 2008 to 2017 were identified. Journal of Magnetic Resonance Imaging published the most articles (79 publications, 9.46%). Extensive cooperating relationship were observed among countries/regions and among authors. South Korea had the most publications (199 publications, 21.82%), followed by the United States of America (USA) (190 publications, 20.83%), Japan (162 publications, 17.76%), and the People's Republic of China (148 publications, 16.23%). Among the top 10 co-cited authors, Bruix J (398 citations) was ranked first, followed by Llovet JM (235 citations), Kim YK (170 citations) and Forner A (152 citations). According to the RCA, ten major clusters were explored over the last decade; "LI-RADS data system" and "microvascular invasion" (MVI) were the two most recent clusters. Forty-seven burst keywords with the highest citation strength were detected over time. Of these keywords, "microvascular invasion" had the highest strength in the last 3 years. The LI-RADS has been constantly updated with the latest edition released in July 2018. However, the LI-RADS still has limitations in identifying certain categories of lesions by conceptual and non-quantitative probabilistic methods. Plenty of questions still need to be further answered such as the difference of diagnostic efficiency of each major/ancillary imaging features. Preoperative prediction of MVI of HCC is very important to therapeutic decision-making. Some parameters of Gd-EOB-DTPA-enhanced MRI were found to be useful in prediction of MVI, however, with a high specificity but a very low sensitivity. Comprehensive predictive model incorporating both imaging and clinical variables may be the more preferable in prediction of MVI of HCC.

Conclusions

HCCMRI-related publications displayed a gradually increasing trend from 2008 to 2017. The USA has a central position in collaboration with other countries/regions, while South Korea contributed the most in the number of publications. Of the ten major clusters identified in the RCA, the two most recent clusters were "LI-RADS data system" and "microvascular invasion", indicative of the current HCCMRI research hotspots.