Can modified LI-RADS increase the sensitivity of LI-RADS v2018 for the diagnosis of 10-19 mm hepatocellular carcinoma on gadoxetic acid-enhanced MRI?

Mean ADC values and arterial phase hyperintensity discriminate small (≤ 3 cm) well-differentiated hepatocellular carcinoma from dysplastic nodule

BACKGROUND/AIM

This research endeavor sought to distinguish small (≤ 3 cm) well-differentiated hepatocellular carcinoma (WD-HCC) from dysplastic nodules (DN) by employing traditional imaging features and mean apparent diffusion coefficient (mADC) values derived from diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

In this retrospective analysis, we assessed a cohort of ninety patients with confirmed dysplastic nodules (DNs) (n = 71) or well-differentiated hepatocellular carcinoma (WD-HCC) (n = 41) who had undergone dynamic contrast-enhanced magnetic resonance imaging between March 2018 and June 2021. Multivariable logistic regression analyses were executed to pinpoint characteristics that can effectively differentiate histologic grades. A region-of-interest (ROI) encompassing all lesion voxels was delineated on each slice containing the mass in the ADC map. Subsequently, the whole-lesion mean ADC (mADC) were computed from these delineations. A receiver operating characteristic (ROC) curve was generated to assess the discriminatory efficacy of the mADC values in distinguishing between WD-HCC and DN.

RESULTS

Among the histopathological types from benign to malignant, mADC showed a significant decrease (P < 0.001). The mADCs were effective in distinguishing WD-HCC from DN [AUC, 0.903 (95% CI 0.849-0.958)]. The best cutoffs for the Youden index were 0.0012 mm2/s for mADC, with moderate sensitivity (70.7%) and high specificity (94.4%). MRI features including hyperintensity at arterial phase (odds ratio, 21.2; P = 0.009), mADC < 0.0012 mm2/s (odds ratio, 52.2; P < 0.001) were independent predictors for WD-HCC at multivariable analysis. The AUC value of hyperintensity at arterial phase was 0.857 (95% CI 0.786-0.928). The composite diagnostic criterion of arterial hyperintensity + mADC < 0.0012 mm2/s showed good performance [AUC, 0.926 (95% CI 0.878-0.975)], displaying increased sensitivity compared to individual assessments involving arterial hyperintensity (P = 0.013), mADC < 0.0012 mm2/s (P = 0.004), or LR-5 (P < 0.001), with similar specificity compared to LR-5 (P = 0.193).

CONCLUSION

DN and WD-HCC displayed contrasting diffusion characteristics, attainable to distinguish with satisfactory accuracy. The utilization of arterial phase hyperintensity and mADC < 0.0012 on MRI facilitated the differentiation of WD-HCC from DN.

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.

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

BACKGROUND

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

PURPOSE

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

STUDY TYPE

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

POPULATION

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

FIELD STRENGTH/SEQUENCE

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

ASSESSMENT

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

STATISTICAL TESTS

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

RESULTS

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

DATA CONCLUSION

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

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

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

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

LI-RADS version 2018 for hepatocellular carcinoma < 1.0 cm on gadoxetate disodium-enhanced magnetic resonance imaging

OBJECTIVES

We aimed to develop and evaluate a modified Liver Imaging Reporting and Data System (LI-RADS) version 2018 using significant ancillary features for diagnosing hepatocellular carcinoma (HCC) < 1.0 cm on gadoxetate disodium-enhanced magnetic resonance imaging (MRI).

METHODS

Patients who underwent preoperative gadoxetate disodium-enhanced MRI for focal solid nodules < 2.0 cm within 1 month of MRI between January 2016 and December 2020 were retrospectively analyzed. Major and ancillary features were compared between HCCs of < 1.0 cm and 1.0-1.9 cm using the chi-square test. Significant ancillary features associated with HCC < 1.0 cm were determined by univariable and multivariable logistic regression analysis. The sensitivity and specificity of LR-5 were compared between LI-RADS v2018 and our modified LI-RADS (applying the significant ancillary feature) using generalized estimating equations.

RESULTS

Of 796 included nodules, 248 were < 1.0 cm and 548 were 1.0-1.9 cm. HCC < 1.0 cm less frequently showed an enhancing capsule (7.1% vs. 31.1%, p < .001) and threshold growth (0% vs. 8.3%, p = .007) than HCC of 1.0-1.9 cm. Restricted diffusion was the only ancillary feature significant for diagnosing HCC < 1.0 cm (adjusted odds ratio = 11.50, p < .001). In the diagnosis of HCC, our modified LI-RADS using restricted diffusion had significantly higher sensitivity than LI-RADS v2018 (61.8% vs. 53.5%, p < .001), with similar specificity (97.3% vs. 97.8%, p = .157).

CONCLUSION

Restricted diffusion was the only significant independent ancillary feature for diagnosing HCC < 1.0 cm. Our modified LI-RADS using restricted diffusion can improve the sensitivity for HCC < 1.0 cm.

KEY POINTS

• The imaging features of hepatocellular carcinoma (HCC) < 1.0 cm differed from those of HCC of 1.0-1.9 cm. • Restricted diffusion was the only significant independent ancillary feature for HCC < 1.0 cm. • Modified Liver Imaging Reporting and Data System (LI-RADS) with the addition of restricted diffusion can improve the sensitivity for HCC < 1.0 cm.

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.

LI-RADS v2018: utilizing ancillary features on gadoxetic acid-enhanced MRI to improve the diagnostic performance of small hapatocellular carcinoma (≤ 20 mm)

PURPOSE

To evaluate the role of ancillary features (AFs) of Liver Imaging Reporting and Data System (LI-RADS) in the diagnostic performance of small HCC (≤ 20 mm) on gadoxetic acid-enhanced MRI.

METHODS

A total of 154 patients with 183 hepatic observations were analysed in this retrospective study. Observations were categorized using only major features (MFs) and combined MFs and AFs. Independently significant AFs were identified through logistic regression analysis, and upgraded LR-5 criteria were developed using these as new MFs. The diagnostic performance of the modified LI-RADS (mLI-RADS) was calculated and compared with that of LI-RADS v2018 using McNemar's test.

RESULTS

Restricted diffusion, transitional and hepatobiliary phase hypointensity were independently significant AFs. The mLI-RADS a, c, e, g, h and i (upgraded LR-4 lesions that were categorized using only MFs to LR-5 using a certain or any one, two, three of the above AFs as new MFs) yielded a significantly greater sensitivity than that of the LI-RADS v2018 (68.0%, 69.1%, 69.1%, 69.1%, 69.1%, 68.0% vs. 61.9%, all p < 0.05), whereas the specificities were not significantly different (84.9%, 86.0%, 84.9%, 83.7%, 84.9%, 87.2% vs. 88.4% all p > 0.05). When independently significant AFs were used to upgrade the LR-4 nodules categorized by combined MFs and AFs (mLI-RADS b, d and f), the sensitivities were improved, but the specificities were decreased (all p < 0.05).

CONCLUSIONS

Independently significant AFs may be used to upgrade an observation from LR-4 (categorized only using MFs) to LR-5, which can improve diagnostic performance for small HCC.

A Narrative Review on LI-RADS Algorithm in Liver Tumors: Prospects and Pitfalls

Liver cancer is the sixth most detected tumor and the third leading cause of tumor death worldwide. Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with specific risk factors and a targeted population. Imaging plays a major role in the management of HCC from screening to post-therapy follow-up. In order to optimize the diagnostic-therapeutic management and using a universal report, which allows more effective communication among the multidisciplinary team, several classification systems have been proposed over time, and LI-RADS is the most utilized. Currently, LI-RADS comprises four algorithms addressing screening and surveillance, diagnosis on computed tomography (CT)/magnetic resonance imaging (MRI), diagnosis on contrast-enhanced ultrasound (CEUS) and treatment response on CT/MRI. The algorithm allows guiding the radiologist through a stepwise process of assigning a category to a liver observation, recognizing both major and ancillary features. This process allows for characterizing liver lesions and assessing treatment. In this review, we highlighted both major and ancillary features that could define HCC. The distinctive dynamic vascular pattern of arterial hyperenhancement followed by washout in the portal-venous phase is the key hallmark of HCC, with a specificity value close to 100%. However, the sensitivity value of these combined criteria is inadequate. Recent evidence has proven that liver-specific contrast could be an important tool not only in increasing sensitivity but also in diagnosis as a major criterion. Although LI-RADS emerges as an essential instrument to support the management of liver tumors, still many improvements are needed to overcome the current limitations. In particular, features that may clearly distinguish HCC from cholangiocarcinoma (CCA) and combined HCC-CCA lesions and the assessment after locoregional radiation-based therapy are still fields of research.

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.

Stability of Liver Radiomics across Different 3D ROI Sizes-An MRI In Vivo Study

We aimed to evaluate the stability of radiomic features in the liver of healthy individuals across different three-dimensional regions of interest (3D ROI) sizes in T1-weighted (T1w) and T2-weighted (T2w) images from different MR scanners. We retrospectively included 66 examinations of patients without known diseases or pathological imaging findings acquired on three MRI scanners (3 Tesla I: 25 patients, 3 Tesla II: 19 patients, 1.5 Tesla: 22 patients). 3D ROIs of different diameters (10, 20, 30 mm) were drawn on T1w GRE and T2w TSE images into the liver parenchyma (segment V–VIII). We extracted 93 radiomic features from the different ROIs and tested features for significant differences with the Mann–Whitney-U (MWU)-test. The MWU-test revealed significant differences for most second- and higher-order features, indicating a systematic difference dependent on the ROI size. The features mean, median, root mean squared (RMS), 10th percentile, and 90th percentile were not significantly different. We also assessed feature robustness to ROI size variation with overall concordance correlation coefficients (OCCCs). OCCCs across the different ROI-sizes for mean, median, and RMS were excellent (>0.90) in both sequences on all three scanners. These features, therefore, seem robust to ROI-size variation and suitable for radiomic studies of liver MRI.