Diagnostic Performance of LI-RADS Version 2018 for Primary Liver Cancer in Patients With Liver Cirrhosis on Enhanced MRI

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.

Imaging and prognostic characterization of fat-containing hepatocellular carcinoma subtypes

PURPOSE

Steatohepatitic hepatocellular carcinoma (SH-HCC) is characterized by intratumoral fat with > 50% inflammatory changes. However, intratumoral fat (with or without inflammation) can also be found in not-otherwise specified HCC (NOS-HCC). We compared the imaging features and outcome of resected HCC containing fat on pathology including SH-HCC (> 50% steatohepatitic component), NOS-HCC with < 50% steatohepatitic component (SH-NOS-HCC), and fatty NOS-HCC (no steatohepatitic component).

MATERIAL AND METHODS

From September 2012 to June 2021, 94 patients underwent hepatic resection for fat-containing HCC on pathology. Imaging features and categories were assessed using LIRADS v2018. Fat quantification was performed on chemical-shift MRI. Recurrence-free and overall survival were estimated.

RESULTS

Twenty-one patients (26%) had nonalcoholic steatohepatitis (NASH). The median intra-tumoral fat fraction was 8%, with differences between SH-HCC and SH-NOS-HCC (9.5% vs. 5% p = 0.03). There was no difference in major LI-RADS features between all groups; most tumors were classified as LR-4/5. A mosaic architecture on MRI was rare (7%) in SH-HCC, a fat in mass on CT was more frequently depicted (48%) in SH-HCC. A combination of NASH with no mosaic architecture on MRI or NASH with fat in mass on CT yielded excellent specificity for diagnosing SH-HCC (97.6% and 97.7%, respectively). The median recurrence-free and overall survival were 58 and 87 months, with no difference between groups (p = 0.18 and p = 0.69).

CONCLUSION

In patients with NASH, an SH-HCC may be suspected in L4/LR-5 observations with no mosaic architecture at MRI or with fat in mass on CT. Oncological outcomes appear similar between fat-containing HCC subtypes.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Differentiation of Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma through MRI Radiomics

The purpose of this study was to investigate the efficacy of magnetic resonance imaging (MRI) radiomics in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). The clinical and MRI data of 129 pathologically confirmed HCC patients and 48 ICC patients treated at the Affiliated Hospital of North Sichuan Medical College between April 2016 and December 2021 were retrospectively analyzed. The patients were randomly divided at a ratio of 7:3 into a training group of 124 patients (90 with HCC and 34 with ICC) and a validation group of 53 patients (39 with HCC and 14 with ICC). Radiomic features were extracted from axial fat suppression T2-weighted imaging (FS-T2WI) and axial arterial-phase (AP) and portal-venous-phase (PVP) dynamic-contrast-enhanced MRI (DCE-MRI) sequences, and the corresponding datasets were generated. The least absolute shrinkage and selection operator (LASSO) method was used to select the best radiomic features. Logistic regression was used to establish radiomic models for each sequence (FS-T2WI, AP and PVP models), a clinical model for optimal clinical variables (C model) and a joint radiomics model (JR model) integrating the radiomics features of all the sequences as well as a radiomics-clinical model combining optimal radiomic features and clinical risk factors (RC model). The performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC). The AUCs of the FS-T2WI, AP, PVP, JR, C and RC models for distinguishing HCC from ICC were 0.693, 0.863, 0.818, 0.914, 0.936 and 0.977 in the training group and 0.690, 0.784, 0.727, 0.802, 0.860 and 0.877 in the validation group, respectively. The results of this study suggest that MRI-based radiomics may help noninvasively differentiate HCC from ICC. The model integrating the radiomics features and clinical risk factors showed a further improvement in performance.

Extracellular volume fraction using contrast-enhanced CT is useful in differentiating intrahepatic cholangiocellular carcinoma from hepatocellular carcinoma

Objectives

To evaluate whether tumor extracellular volume fraction (fECV) on contrast-enhanced computed tomography (CT) aids in the differentiation between intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC).

Methods

In this retrospective study, 113 patients with pathologically confirmed ICC (n = 39) or HCC (n = 74) who had undergone preoperative contrast-enhanced CT were enrolled. Enhancement values of the tumor (Etumor) and aorta (Eaorta) were obtained in the precontrast and equilibrium phase CT images. fECV was calculated using the following equation: fECV [%] = Etumor/Eaorta × (100 - hematocrit [%]). fECV values were compared between the ICC and HCC groups using Welch's t-test. The diagnostic performance of fECV for differentiating ICC and HCC was assessed using receiver-operating characteristic (ROC) analysis. fECV and the CT imaging features of tumors were evaluated by two radiologists. Multivariate logistic regression analysis was performed to identify factors predicting a diagnosis of ICC.

Results

Mean fECV was significantly higher in ICCs (43.8% ± 13.2%) than that in HCCs (31.6% ± 9.0%, p < 0.001). The area under the curve for differentiating ICC from HCC was 0.763 when the cutoff value of fECV was 41.5%. The multivariate analysis identified fECV (unit OR: 1.10; 95% CI: 1.01-1.21; p < 0.05), peripheral rim enhancement during the arterial phase (OR: 17.0; 95% CI: 1.29-225; p < 0.05), and absence of washout pattern (OR: 235; 95% CI: 14.03-3933; p < 0.001) as independent CT features for differentiating between the two tumor types.

Conclusions

A high value of fECV, peripheral rim enhancement during the arterial phase, and absence of washout pattern were independent factors in the differentiation of ICC from HCC.

The Diagnostic Approach towards Combined Hepatocellular-Cholangiocarcinoma-State of the Art and Future Perspectives

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer which displays clinicopathologic features of both hepatocellular (HCC) and cholangiocellular carcinoma (CCA). The similarity to HCC and CCA makes the diagnostic workup particularly challenging. Alpha-fetoprotein (AFP) and carbohydrate antigen 19-9 (CA 19-9) are blood tumour markers related with HCC and CCA, respectively. They can be used as diagnostic markers in cHCC-CCA as well, albeit with low sensitivity. The imaging features of cHCC-CCA overlap with those of HCC and CCA, dependent on the predominant histopathological component. Using the Liver Imaging and Reporting Data System (LI-RADS), as many as half of cHCC-CCAs may be falsely categorised as HCC. This is especially relevant since the diagnosis of HCC may be made without histopathological confirmation in certain cases. Thus, in instances of diagnostic uncertainty (e.g., simultaneous radiological HCC and CCA features, elevation of CA 19-9 and AFP, HCC imaging features and elevated CA 19-9, and vice versa) multiple image-guided core needle biopsies should be performed and analysed by an experienced pathologist. Recent advances in the molecular characterisation of cHCC-CCA, innovative diagnostic approaches (e.g., liquid biopsies) and methods to analyse multiple data points (e.g., clinical, radiological, laboratory, molecular, histopathological features) in an all-encompassing way (e.g., by using artificial intelligence) might help to address some of the existing diagnostic challenges.