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

Risk of Bias in Liver Imaging Reporting and Data System Studies Using QUADAS-2

Purpose: Use a tailored version of the Quality Assessment of Diagnostic Accuracy Studies tool to evaluate risk of bias and applicability across LIRADS related publications. Method: A tailored QUADAS-2 tool was created through consensus approach to assess risk of bias and applicability across 37 LI-RADS related publications. Studies were selected from 2017 to 2022 using the assistance of experienced hospital librarians to search for studies evaluating the diagnostic accuracy of CT, MRI, or contrast-enhanced ultrasound for HCC using LI-RADS through multiple different databases. QUADAS-2 assessments were performed in duplicate and independently by 2 authors with experience using the QUADAS-2 tool. Disagreements were resolved with a third expert reviewer. Consensus QUADAS-2 assessments were tabulated for each domain. Results: Using the tailored QUADAS-2 tool, 31 of the 37 included LI-RADS studies were assessed as high risk of bias, and 9 out of 37 studies demonstrated concerns for applicability. Patient selection (21 out of 37 studies) and flow/timing (24 out of 37 studies) domains demonstrated the highest risk of bias. 6 out of 37 studies in the index domain demonstrated high risk of bias. 2 out of 37 studies showed high risk of bias in the reference standard domain. Conclusion: A significant proportion of LI-RADS research is at risk of bias with concerns for applicability. Identifying risk of bias in such research is essential to recognize limitations of a study that may affect the validity of the results. Areas for improvement in LI-RADS research include reducing selection bias, avoiding inappropriate exclusions, and decreasing verification bias.

Is concurrent LR-5 associated with a higher rate of hepatocellular carcinoma in LR-3 or LR-4 observations? An individual participant data meta-analysis

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations.

PURPOSE

To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis.

METHODS

Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x . Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).

RESULTS

Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis.

CONCLUSION

The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.

Modified LR-5 criteria based on gadoxetic acid can improve the sensitivity in the diagnosis of hepatocellular carcinoma

BACKGROUND

Currently, only tumors classified as LR-5 are considered definitive hepatocellular carcinoma (HCC), and no further pathologic confirmation is required to initiate therapy. Previous studies have shown that the sensitivity of LR-5 is modest, and lesions enhanced by gadoxetic acid (Gd-EOB-DTPA) may exhibit lower sensitivity than those enhanced by Gd-DTPA.

AIM

To identify malignant ancillary features (AFs) that can independently and significantly predict HCC in Liver Imaging Reporting and Data System version 2018, and to develop modified LR-5 criteria to improve diagnostic performance on Gd-EOB-DTPA - enhanced magnetic resonance imaging.

METHODS

Imaging data from patients with HCC risk factors who underwent abdominal Gd-EOB-DTPA - enhanced magnetic resonance imaging were collected. Univariate and multivariate logistic regression analyses were performed to determine AFs that could independently and significantly predict HCC. The modified LR-5 criteria involved reclassifying LR-4/LR-3 lesions based on major features combined with independently significant AFs for HCC, or by substituting threshold growth with significant AFs. McNemar's test was used to compare the diagnostic performance of the modified LR-5 criteria.

RESULTS

A total of 244 lesions from 216 patients were included. Transitional phase hypointensity, mild - moderate T2 hyperintensity, and fat in mass (more than adjacent liver) were identified as significant independent predictors of HCC. Using the modified LR-5 criteria (e.g., LR-5-M1: LR-4 + transitional phase hypointensity; LR-5-M4: LR-5 by transitional phase hypointensity instead of threshold growth; LR-5-M5: LR-5 by mild - moderate T2 hyperintensity instead of threshold growth; LR-5-M8: LR-3/LR-4 + any two features of transitional phase hypointensity/mild - moderate T2 hyperintensity/fat in mass), sensitivities were significantly increased (88.5%-89.1%) compared to the standard LR-5 (60.6%; all P values < 0.05), while specificities (84.8%-89.9%) remained largely unchanged (93.7%; all P values > 0.05). The LR-5-M8 criterion achieved the highest sensitivity.

CONCLUSION

Mild - moderate T2 hyperintensity, transitional phase hypointensity, and fat in mass are independent and significant predictors of HCC malignant AFs. The modified LR-5 criteria can improve sensitivity without significantly reducing specificity.

Current State of Evidence for Use of MRI in LI-RADS

The American College of Radiology Liver Imaging Reporting and Data System (LI-RADS) is the preeminent framework for classification and risk stratification of liver observations on imaging in patients at high risk for hepatocellular carcinoma. In this review, the pathogenesis of hepatocellular carcinoma and the use of MRI in LI-RADS is discussed, including specifically the LI-RADS diagnostic algorithm, its components, and its reproducibility with reference to the latest supporting evidence. The LI-RADS treatment response algorithms are reviewed, including the more recent radiation treatment response algorithm. The application of artificial intelligence, points of controversy, LI-RADS relative to other liver imaging systems, and possible future directions are explored. After reading this article, the reader will have an understanding of the foundation and application of LI-RADS as well as possible future directions.

LI-RADS Nonradiation Treatment Response Algorithm Version 2024: Diagnostic Performance and Impact of Ancillary Features

BACKGROUND. LI-RADS Treatment Response Algorithm (TRA) version 2024 (v2024) introduced separate algorithms for detecting hepatocellular carcinoma (HCC) viability after radiation and nonradiation locoregional therapies (LRTs). The nonradiation algorithm incorporated MRI-based ancillary features to optionally upgrade lesions from LR-TR Equivocal to LR-TR Viable. OBJECTIVE. The purpose of this study was to compare the diagnostic performance of LI-RADS Nonradiation TRA v2024 with that of LI-RADS TRA version 2017 (v2017) and modified RECIST (mRECIST) for evaluating HCC response to LRT on MRI, with attention given to the impact of ancillary features. METHODS. This retrospective study included 231 patients (198 men and 33 women; median age, 56 years) who underwent LRT for HCC followed by liver resection or transplant between January 2017 and December 2022. Two radiologists (reader 1 and reader 2) independently evaluated treated lesions (n = 306) using LI-RADS Nonradiation TRA v2024, LI-RADS TRA v2017, and mRECIST. Lesions were classified as showing pathologic viability (n = 249) or complete pathologic necrosis (n = 57) based on curative surgery pathology. The diagnostic performance for pathologic viability was compared using Bonferroni-adjusted McNemar tests, with LR-TR Equivocal assessments classified as test negative. RESULTS. The sensitivity, specificity, and accuracy for LI-RADS Nonradiation TRA v2024 with ancillary features were 85.5%, 75.4%, and 83.7%, respectively, for reader 1 and 87.2%, 63.2%, and 82.7%, respectively, for reader 2; for LI-RADS Nonradiation TRA v2024 without ancillary features, they were 81.1%, 78.9%, and 80.7%, respectively, for reader 1 and 80.3%, 78.9%, and 80.1%, respectively, for reader 2; for LI-RADS TRA v2017, they were 79.9%, 82.5%, and 80.4%, respectively, for reader 1 and 79.1%, 79.0%, and 79.1%, respectively, for reader 2; and for mRECIST, they were 83.9%, 54.4%, and 78.4%, respectively, for reader 1 and 87.2%, 40.4%, and 78.4%, respectively, for reader 2. LI-RADS Nonradiation TRA v2024 with ancillary features showed higher sensitivity and accuracy than LI-RADS Nonradiation v2024 without ancillary features (both readers), higher sensitivity than LI-RADS TRA v2017 (both readers), higher specificity than mRECIST (both readers), and higher accuracy than LI-RADS TRA v2017 (reader 2) (p < .008); remaining comparisons between LI-RADS Nonradiation TRA v2024 with ancillary features and other systems were not significant (p > .008). CONCLUSION. LI-RADS Nonradiation TRA v2024 showed good diagnostic performance in detecting pathologic viability. Ancillary features yielded improved sensitivity and accuracy without a significant change in specificity. CLINICAL IMPACT. Use of LI-RADS Nonradiation TRA v2024 with ancillary features is recommended for guiding prognostic assessments and treatment decisions after LRT.

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.

Best Practice for MRI Diagnostic Accuracy Research With Lessons and Examples from the LI-RADS Individual Participant Data Group

Medical imaging diagnostic test accuracy research is strengthened by adhering to best practices for study design, data collection, data documentation, and study reporting. In this review, key elements of such research are discussed, and specific recommendations provided for optimizing diagnostic accuracy study execution to improve uniformity, minimize common sources of bias and avoid potential pitfalls. Examples are provided regarding study methodology and data collection practices based on insights gained by the liver imaging reporting and data system (LI-RADS) individual participant data group, who have evaluated raw data from numerous MRI diagnostic accuracy studies for risk of bias and data integrity. The goal of this review is to outline strategies for investigators to improve research practices, and to help reviewers and readers better contextualize a study's findings while understanding its limitations. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Intra-patient and inter-observer image quality analysis in liver MRI study with gadoxetic acid using two different multi-arterial phase techniques

PURPOSE

To evaluate intra-patient and interobserver agreement in patients who underwent liver MRI with gadoxetic acid using two different multi-arterial phase (AP) techniques.

METHODS

A total of 154 prospectively enrolled patients underwent clinical gadoxetic acid-enhanced liver MRI twice within 12 months, using two different multi-arterial algorithms: CAIPIRINHA-VIBE and TWIST-VIBE. For every patient, breath-holding time, body mass index, sex, age were recorded. The phase without contrast media and the APs were independently evaluated by two radiologists who quantified Gibbs artefacts, noise, respiratory motion artefacts, and general image quality. Presence or absence of Gibbs artefacts and noise was compared by the McNemar's test. Respiratory motion artefacts and image quality scores were compared using Wilcoxon signed rank test. Interobserver agreement was assessed by Cohen kappa statistics.

RESULTS

Compared with TWIST-VIBE, CAIPIRINHA-VIBE images had better scores for every parameter except higher noise score. Triple APs were always acquired with TWIST-VIBE but failed in 37% using CAIPIRINHA-VIBE: 11% have only one AP, 26% have two. Breath-holding time was the only parameter that influenced the success of multi-arterial techniques. TWIST-VIBE images had worst score for Gibbs and respiratory motion artefacts but lower noise score.

CONCLUSION

CAIPIRINHA-VIBE images were always diagnostic, but with a failure of triple-AP in 37%. TWIST-VIBE was successful in obtaining three APs in all patients. Breath-holding time is the only parameter which can influence the preliminary choice between CAIPIRINHA-VIBE and TWIST-VIBE algorithm.

ADVANCES IN KNOWLEDGE

If the patient is expected to perform good breath-holds, TWIST-VIBE is preferable; otherwise, CAIPIRINHA-VIBE is more appropriate.

Optimizing LI-RADS: ancillary features screened from LR-3/4 categories can improve the diagnosis of HCC on MRI

OBJECTIVE

To determine the high-efficiency ancillary features (AFs) screened from LR-3/4 lesions and the HCC/non-HCC group and the diagnostic performance of LR3/4 observations.

MATERIALS AND METHODS

We retrospectively analyzed a total of 460 patients (with 473 nodules) classified into LR-3-LR-5 categories, including 311 cases of hepatocellular carcinoma (HCC), 6 cases of non-HCC malignant tumors, and 156 cases of benign lesions. Two faculty abdominal radiologists with experience in hepatic imaging reviewed and recorded the major features (MFs) and AFs of the Liver Imaging Reporting and Data System (LI-RADS). The frequency of the features and diagnostic performance were calculated with a logistic regression model. After applying the above AFs to LR-3/LR-4 observations, the sensitivity and specificity for HCC were compared.

RESULTS

The average age of all patients was 54.24 ± 11.32 years, and the biochemical indicators ALT (P = 0.044), TBIL (P = 0.000), PLT (P = 0.004), AFP (P = 0.000) and Child‒Pugh class were significantly higher in the HCC group. MFs, mild-moderate T2 hyperintensity, restricted diffusion and AFs favoring HCC in addition to nodule-in-nodule appearance were common in the HCC group and LR-5 category. AFs screened from the HCC/non-HCC group (AF-HCC) were mild-moderate T2 hyperintensity, restricted diffusion, TP hypointensity, marked T2 hyperintensity and HBP isointensity (P = 0.005, < 0.001, = 0. 032, p < 0.001, = 0.013), and the AFs screened from LR-3/4 lesions (AF-LR) were restricted diffusion, mosaic architecture, fat in mass, marked T2 hyperintensity and HBP isointensity (P < 0.001, = 0.020, = 0.036, < 0.001, = 0.016), which were not exactly the same. After applying AF-HCC and AF-LR to LR-3 and LR-4 observations in HCC group and Non-HCC group, After the above grades changed, the diagnostic sensitivity for HCC were 84.96% using AF-HCC and 85.71% using AF-LR, the specificity were 89.26% using AF-HCC and 90.60% using AF-LR, which made a significant difference (P = 0.000). And the kappa value for the two methods of AF-HCC and AF-LR were 0.695, reaching a substantial agreement.

CONCLUSION

When adjusting for LR-3/LR-4 lesions, the screened AFs with high diagnostic ability can be used to optimize LI-RADS v2018; among them, AF-LR is recommended for better diagnostic capabilities.

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.

LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis

Background The independent contribution of each Liver Imaging Reporting and Data System (LI-RADS) CT or MRI ancillary feature (AF) has not been established. Purpose To evaluate the association of LI-RADS AFs with hepatocellular carcinoma (HCC) and malignancy while adjusting for LI-RADS major features through an individual participant data (IPD) meta-analysis. Materials and Methods Medline, Embase, Cochrane Central Register of Controlled Trials, and Scopus were searched from January 2014 to January 2022 for studies evaluating the diagnostic accuracy of CT and MRI for HCC using LI-RADS version 2014, 2017, or 2018. Using a one-step approach, IPD across studies were pooled. Adjusted odds ratios (ORs) and 95% CIs were derived from multivariable logistic regression models of each AF combined with major features except threshold growth (excluded because of infrequent reporting). Liver observation clustering was addressed at the study and participant levels through random intercepts. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2. Results Twenty studies comprising 3091 observations (2456 adult participants; mean age, 59 years ± 11 [SD]; 1849 [75.3%] men) were included. In total, 89% (eight of nine) of AFs favoring malignancy were associated with malignancy and/or HCC, 80% (four of five) of AFs favoring HCC were associated with HCC, and 57% (four of seven) of AFs favoring benignity were negatively associated with HCC and/or malignancy. Nonenhancing capsule (OR = 3.50 [95% CI: 1.53, 8.01]) had the strongest association with HCC. Diffusion restriction (OR = 14.45 [95% CI: 9.82, 21.27]) and mild-moderate T2 hyperintensity (OR = 10.18 [95% CI: 7.17, 14.44]) had the strongest association with malignancy. The strongest negative associations with HCC were parallels blood pool enhancement (OR = 0.07 [95% CI: 0.01, 0.49]) and marked T2 hyperintensity (OR = 0.18 [95% CI: 0.07, 0.45]). Seventeen studies (85%) had a high risk of bias. Conclusion Most LI-RADS AFs were independently associated with HCC, malignancy, or benignity as intended when adjusting for major features. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Crivellaro in this issue.

Diagnostic Value of CT Delayed Phase Images Added to Gd-EOB-DTPA MRI for HCC Diagnosis in LR-3/4 Lesions

Objective

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

Methods

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

Results

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

Conclusion

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

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.

Liver Imaging Reporting and Data System criteria for the diagnosis of hepatocellular carcinoma in clinical practice: A pictorial minireview

Hepatocellular carcinoma (HCC) is the sixth most common cancer. The main risk factors associated with HCC development include hepatitis B virus, hepatitis C virus, alcohol consumption, aflatoxin B1, and nonalcoholic fatty liver disease. However, hepatocarcinogenesis is a complex multistep process. Various factors lead to hepatocyte malignant transformation and HCC development. Diagnosis and surveillance of HCC can be made with the use of liver ultrasound (US) every 6 mo. However, the sensitivity of this imaging method to detect HCC in a cirrhotic liver is limited, due to the abnormal liver parenchyma. Computed tomography (CT) and magnetic resonance imaging (MRI) are considered to be most useful tools for at-risk patients or patients with inadequate US. Liver biopsy is still used for diagnosis and prognosis of HCC in specific nodules that cannot be definitely characterized as HCC by imaging. Recently the American College of Radiology designed the Liver Imaging Reporting and Data System (LI-RADS), which is a comprehensive system for standardized interpretation of CT and MRI liver examinations that was first proposed in 2011. In 2018, it was integrated into the American Association for the Study of Liver Diseases guidance statement for HCC. LI-RADS is designed to ensure high sensitivity, precise categorization, and high positive predictive value for the diagnosis of HCC and is applied to “high-risk populations” according to specific criteria. Most importantly LI-RADS criteria achieved international collaboration and consensus among liver experts around the world on the best practices for caring for patients with or at risk for HCC.

The added value of artificial intelligence to LI-RADS categorization: A systematic review

PURPOSE

The objective of this systematic review was to critically assess the available literature on deep learning (DL) and radiomics applied to the Liver Imaging Reporting and Data System (LI-RADS) in terms of 1) automatic LI-RADS classification of liver nodules; 2) the contribution of DL and radiomics to human evaluation in the classification of liver nodules following LI-RADS protocol.

MATERIALS AND METHODS

A literature search was conducted to identify original research studies published up to April 2021. The inclusion criteria were: English language, focus on computed tomography (CT) and/or magnetic resonance (MR) with specified number of patients and lesions, adoption of LI-RADS classification for the detected hepatic lesions, and application of AI in the classification of liver nodules. Review articles, conference papers, editorials and commentaries, animal studies or studies with absence of AI and/or LI-RADS were excluded. After screening 221 articles, 11 studies were included in this review.

RESULTS

All the included studies proved that DL and radiomics have high performances in liver nodules classification, sometimes similar or better than human evaluation. The best performances of DL was an AUC of 0.95 on MR and the best performance of radiomics was AUC of 0.98 either on CT and MR, while the lower ones were respectively AUC of 0.63 either on CT and MR for DL and AUC of 0.70 on CT for radiomics.

CONCLUSION

DL and radiomics could be a useful tool in assisting radiologists in the diagnosis and classification of liver nodules according to LI-RADS.

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.

LI-RADS ancillary features favoring benignity: is there a role in LR-5 observations?

OBJECTIVES

The Liver Imaging Reporting and Data System algorithm allows category downgrade in the presence of ancillary features (AFs) favoring benignity, even in observations categorized as LR-5. This study aims to assess the role of AFs favoring benignity in LR-5 observations and their impact on category downgrade.

METHODS

This study included high-risk patients with at least one LR-5 observation imaged with gadoxetate disodium MRI. Three readers with different experience levels independently evaluated the presence of AFs favoring malignancy (not hepatocellular carcinoma (HCC) in particular and HCC in particular) and AFs favoring benignity. Category downgrade was considered possible in the presence of ≥ 1 AF favoring benignity and no AF favoring malignancy. Correlation between observations size and number of AFs was assessed using Spearman's rank correlation coefficient. Cohen's kappa (k) test was used to assess inter-reader agreement.

RESULTS

The final study cohort included 162 LR-5 (mean size: 23 ± 16 mm) in 119 patients. AFs favoring benignity were reported in 9 (5.6%), 20 (12.3%), and 10 (6.2%) LR-5 observations by reader 1, reader 2, and reader 3, respectively. Hepatobiliary phase isointensity was observed in 6 (3.7%), 2 (1.2%), and 7 (4.3%) observations, respectively. Category downgrade was considered possible in only one (0.6%) observation by reader 1 and reader 3. There was a significant correlation between observation size and number of AFs favoring malignancy (p < 0.001), not HCC in particular (p ≤ 0.010), and favoring HCC in particular (p < 0.001). Inter-reader agreement of AFs favoring benignity was poor to moderate (k range: - 0.01, 0.43).

CONCLUSIONS

AFs favoring benignity are not uncommon in LR-5 observations, but category downgrade is exceptional.

KEY POINTS

• Ancillary features favoring benignity are encountered in 5.6-12.3% of observations categorized as LR-5. • Category downgrade of LR-5 observations is very rare (0.6% of observations) in the presence of AFs favoring benignity due to the high prevalence (98-99%) of ancillary features favoring malignancy in LR-5 observations. • The inter-reader agreement of ancillary features favoring benignity is poor to moderate (k range: - 0.01, 0.43) in readers with different levels of experience.