Meta-analysis of the accuracy of Liver Imaging Reporting and Data System category 4 or 5 for diagnosing hepatocellular carcinoma

Simplified liver imaging reporting and data system for the diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced magnetic resonance imaging

BACKGROUND

The liver imaging reporting and data system (LI-RADS) diagnostic table has 15 cells and is too complex. The diagnostic performance of LI-RADS for hepatocellular carcinoma (HCC) is not satisfactory on gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI).

AIM

To evaluate the ability of the simplified LI-RADS (sLI-RADS) to diagnose HCC on EOB-MRI.

METHODS

A total of 331 patients with 356 hepatic observations were retrospectively analysed. The diagnostic performance of sLI-RADS A-D using a single threshold was evaluated and compared with LI-RADS v2018 to determine the optimal sLI-RADS. The algorithms of sLI-RADS A-D are as follows: The single threshold for sLI-RADS A and B was 10 mm, that is, classified observations ≥ 10mm using an algorithm of 10-19 mm observations (sLI-RADS A) and ≥ 20 mm observations (sLI-RADS B) in the diagnosis table of LI-RADS v2018, respectively, while the classification algorithm remained unchanged for observations < 10 mm; the single threshold for sLI-RADS C and D was 20 mm, that is, for < 20 mm observations, the algorithms for < 10 mm observations (sLI-RADS C)and 10-19 mm observations (sLI-RADS D) were used, respectively, while the algorithm remained unchanged for observations ≥ 20 mm. With hepatobiliary phase (HBP) hypointensity as a major feature (MF), the final sLI-RADS (F-sLI-RADS) was formed according to the optimal sLI-RADS, and its diagnostic performance was evaluated. The times needed to classify the observations according to F-sLI-RADS and LI-RADS v2018 were compared.

RESULTS

The optimal sLI-RADS was sLI-RADS D (with a single threshold of 20 mm), because its sensitivity was greater than that of LI-RADS v2018 (89.8% vs 87.0%, P = 0.031), and its specificity was not lower (89.4% vs 90.1%, P > 0.999). With HBP hypointensity as an MF, the sensitivity of F-sLI-RADS was greater than that of LI-RADS v2018 (93.0% vs 87.0%, P < 0.001) and sLI-RADS D (93.0% vs 89.8%, P = 0.016), without a lower specificity (86.5% vs 90.1%, P = 0.062; 86.5% vs 89.4%, P = 0.125). Compared with that of LI-RADS v2018, the time to classify lesions according to F-sLI-RADS was shorter (51 ± 21 s vs 73 ± 24 s, P < 0.001).

CONCLUSION

The use of sLI-RADS with HBP hypointensity as an MF may improve the sensitivity of HCC diagnosis and reduce lesion classification time.

Simplified liver imaging reporting and data system for the diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced magnetic resonance imaging

BACKGROUND

The liver imaging reporting and data system (LI-RADS) diagnostic table has 15 cells and is too complex. The diagnostic performance of LI-RADS for hepatocellular carcinoma (HCC) is not satisfactory on gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI).

AIM

To evaluate the ability of the simplified LI-RADS (sLI-RADS) to diagnose HCC on EOB-MRI.

METHODS

A total of 331 patients with 356 hepatic observations were retrospectively analysed. The diagnostic performance of sLI-RADS A-D using a single threshold was evaluated and compared with LI-RADS v2018 to determine the optimal sLI-RADS. The algorithms of sLI-RADS A-D are as follows: The single threshold for sLI-RADS A and B was 10 mm, that is, classified observations ≥ 10mm using an algorithm of 10-19 mm observations (sLI-RADS A) and ≥ 20 mm observations (sLI-RADS B) in the diagnosis table of LI-RADS v2018, respectively, while the classification algorithm remained unchanged for observations < 10 mm; the single threshold for sLI-RADS C and D was 20 mm, that is, for < 20 mm observations, the algorithms for < 10 mm observations (sLI-RADS C)and 10-19 mm observations (sLI-RADS D) were used, respectively, while the algorithm remained unchanged for observations ≥ 20 mm. With hepatobiliary phase (HBP) hypointensity as a major feature (MF), the final sLI-RADS (F-sLI-RADS) was formed according to the optimal sLI-RADS, and its diagnostic performance was evaluated. The times needed to classify the observations according to F-sLI-RADS and LI-RADS v2018 were compared.

RESULTS

The optimal sLI-RADS was sLI-RADS D (with a single threshold of 20 mm), because its sensitivity was greater than that of LI-RADS v2018 (89.8% vs 87.0%, P = 0.031), and its specificity was not lower (89.4% vs 90.1%, P > 0.999). With HBP hypointensity as an MF, the sensitivity of F-sLI-RADS was greater than that of LI-RADS v2018 (93.0% vs 87.0%, P < 0.001) and sLI-RADS D (93.0% vs 89.8%, P = 0.016), without a lower specificity (86.5% vs 90.1%, P = 0.062; 86.5% vs 89.4%, P = 0.125). Compared with that of LI-RADS v2018, the time to classify lesions according to F-sLI-RADS was shorter (51 ± 21 s vs 73 ± 24 s, P < 0.001).

CONCLUSION

The use of sLI-RADS with HBP hypointensity as an MF may improve the sensitivity of HCC diagnosis and reduce lesion classification time.

Hepatic Steatosis Has No Effect in Diagnosis Accuracy of LI-RADS v2018 Categorization of Hepatocellular Carcinoma in MR Imaging

BACKGROUND

In clinical practice, hepatocellular carcinoma (HCC) is widely diagnosed by using MRI, however, whether the imaging features are affected by hepatic steatosis (HS) is still unknown.

PURPOSE

To investigate and compare the differences in HCC related imaging features between with- and without-HS groups, and to further determine whether HS affects the diagnosis accuracy of Liver Imaging Reporting and Data System (LI-RADS) v2018 of HCC in MRI.

STUDY TYPE

Prospective.

SUBJECTS

One hundred and seventy-one patients (mean age, 52 ± 11 years; range, 26-83 years) including 137 men and 34 women.

FIELD STRENGTH/SEQUENCE

3.0 T, gradient echo (GRE).

ASSESSMENT

Subjects were classified as HS and non-HS groups according to MRI-proton density fat-fraction (PDFF). HS was defined as MRI-PDFF >5.6%. Three radiologists accessed HCC features and assigned LI-RADS categories in MRI independently based on LI-RADS v2018. Frequencies of HCC major features and LR categorization assignment between the two groups as well as interobserver agreement between the two radiologists were assessed.

STATISTICAL TESTS

Unpaired t-test, Chi-square test, Fisher's exact test, kappa statistic, intraclass correlation coefficient (ICC). A two-sided P value <0.05 was considered as statistically significant.

RESULTS

Major features including arterial hyperenhancement (APHE), enhancing "capsule" and nonperipheral "washout" observed between HS and non-HS groups were not significantly different (78.95% vs.78.62%, P = 0.866; 57.89% vs.52.98%, P = 0.483; and 75% vs.81.46%, P = 0.257, respectively), and the assessment of observation size showed a borderline difference (P = 0.059). No significant difference in LR-5 assignment between the two groups (69.74% vs. 72.85% for reader 1, P = 0.641; 71.05% vs. 72.19% for reader 2, P = 0.877). Interobserver agreement between the two radiologists showed almost perfect in LR-5 assignment (κ = 0.869) and size observation (ICC = 0.997).

DATA CONCLUSION

The diagnosis of HCC based on LI-RADS v2018 in MRI is of comparable performance regardless of HS, in which there is no significant difference in either the major imaging features or LR categorization.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 2.

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.

LI-RADS threshold growth based on tumor growth rate can improve the diagnosis of hepatocellular carcinoma ≤ 3.0 cm

OBJECTIVE

Despite the revision of threshold growth (TG) in the Liver Imaging Reporting and Data System (LI-RADS) version 2018, the appropriate time period between the two examinations for TG has not been determined. We compared the accuracy of LI-RADS with TG based on tumor growth rate for the diagnosis of hepatocellular carcinoma (HCC) with that of LI-RADS v2018 based on the original TG.

METHODS

Patients who underwent preoperative MRI for focal solid lesions (≤ 3.0 cm) were retrospectively evaluated. Three readers measured the size of each lesion on prior CT/MRI and index MRI, with tumor growth rate defined as the percent change in lesion size per month. In addition to the original TG (≥ 50% size increase within ≤ 6 months), the modified TG based on tumor growth rates ≥ 10%/month (TG-10%), ≥ 20%/month (TG-20%), and ≥ 30%/month (TG-30%) were evaluated. The accuracies of these evaluation methods for LI-RADS category 5 HCC were compared using generalized estimation equations.

RESULTS

A total of 508 lesions from 370 patients were evaluated. Compared with LI-RADS v2018 with the original TG, the accuracy of LI-RADS with TG-10% was significantly higher (85.0% vs. 80.7%, p < .001), whereas the accuracies of LI-RADS with TG-20% (81.3% vs. 80.7%, p = .404) and TG-30% (79.3% vs. 80.7%, p = .052) were not significant. The sensitivity of LI-RADS with TG-10% was higher than that of LI-RADS v2018 (79.0% vs. 72.5%, p < .001), whereas their specificities were not significantly different (96.6% vs. 96.6%, p > .999).

CONCLUSION

TG-10% improved the sensitivity of LI-RADS by detecting additional hepatocellular carcinomas underestimated due to short-term follow-up.

CLINICAL RELEVANCE STATEMENT

Threshold growth based on tumor growth rate can be clinically useful in the diagnosis of hepatocellular carcinoma, by improving the sensitivity of LI-RADS.

KEY POINTS

• The diagnostic accuracy of Liver Imaging Reporting and Data System (LI-RADS) v2018 was not significantly affected by the time interval between prior and index assessments of threshold growth. • In the 334 hepatocellular carcinomas, the frequency of threshold growth was significantly higher using tumor growth rate ≥ 10%/month (TG-10%) than original threshold growth (53.3% vs. 18.0%, p < .001). • Compared with LI-RADS v2018 with the original threshold growth, LI-RADS with TG-10% had significantly higher accuracy (85.0% vs. 80.7%, p < .001) and sensitivity (79.0% vs. 72.5%, p < .001) but a similar specificity (96.6% vs. 96.6%, p > .999).

A gadoxetic acid-enhanced MRI-based model using LI-RADS v2018 features for preoperatively predicting Ki-67 expression in hepatocellular carcinoma

PURPOSE

To construct a gadoxetic acid-enhanced MRI (EOB-MRI) -based multivariable model to predict Ki-67 expression levels in hepatocellular carcinoma (HCC) using LI-RADS v2018 imaging features.

METHODS

A total of 121 patients with HCC who underwent EOB-MRI were enrolled in this study. The patients were divided into three groups according to Ki-67 cut-offs: Ki-67 ≥ 20% (n = 86) vs. Ki-67 < 20% (n = 35); Ki-67 ≥ 30% (n = 73) vs. Ki-67 < 30% (n = 48); Ki-67 ≥ 50% (n = 45) vs. Ki-67 < 50% (n = 76). MRI features were analyzed to be associated with high Ki-67 expression using logistic regression to construct multivariable models. The performance characteristic of the models for the prediction of high Ki-67 expression was assessed using receiver operating characteristic curves.

RESULTS

The presence of mosaic architecture (p = 0.045), the presence of infiltrative appearance (p = 0.039), and the absence of targetoid hepatobiliary phase (HBP, p = 0.035) were independent differential factors for the prediction of high Ki-67 status (≥ 50% vs. < 50%) in HCC patients, while no features could predict high Ki-67 status with thresholds of 20% (≥ 20% vs. < 20%) and 30% (≥ 30% vs. < 30%) (p > 0.05). Four models were constructed including model A (mosaic architecture and infiltrated appearance), model B (mosaic architecture and targetoid HBP), model C (infiltrated appearance and targetoid HBP), and model D (mosaic architecture, infiltrated appearance and targetoid HBP). The model D yielded better diagnostic performance than the model C (0.776 vs. 0.669, p = 0.002), but a comparable AUC than model A (0.776 vs. 0.781, p = 0.855) and model B (0.776 vs. 0.746, p = 0.076).

CONCLUSIONS

Mosaic architecture, infiltrated appearance and targetoid HBP were sensitive imaging features for predicting Ki-67 index ≥ 50% and EOB-MRI model based on LI-RADS v2018 features may be an effective imaging approach for the risk stratification of patients with HCC before surgery.

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.

Value of threshold growth as a major diagnostic feature of hepatocellular carcinoma in LI-RADS

BACKGROUND & AIMS

The Liver Reporting and Data System (LI-RADS) version 2018 simplified the definition of threshold growth to '≥50% size increase in a mass in ≤6 months'. However, the diagnostic value of threshold growth for hepatocellular carcinoma (HCC) remained unclear. We evaluated the value of threshold growth, as defined by LI-RADS v2018, in diagnosing HCCs.

METHODS

Patients who underwent preoperative gadoxetate disodium-enhanced MRI because of the presence of LI-RADS category 2, 3, or 4 rather than category 5 on prior CT/MRI between January 2017 and December 2020 were retrospectively evaluated. Pathologic or clinical diagnoses were used as reference standards. Imaging features were evaluated by three readers according to LI-RADS v2018. The frequency and diagnostic odds ratio of threshold growth were calculated. The diagnostic performance of LI-RADS category 5 was separately evaluated when threshold growth was and was not considered a major feature, and results were compared using generalized estimation equations. Subgroups of patients who underwent CT/MRI during the previous 3-6 months were analyzed.

RESULTS

Analysis of 340 observations in 243 patients found that the frequency of threshold growth was 18.8% and it gradually increased over time. Threshold growth was significantly associated with HCC (diagnostic odds ratio 5.2; 95% CI 2.1-12.7; p <0.001). Use of threshold growth as a major feature significantly increased sensitivity in both the overall (66.4% vs. 57.3%, p <0.001) and subgroup (73.4% vs. 58.2%, p <0.001) cohorts, but had no effect on specificity in either the overall (97.5% vs. 98.3%, p = 0.319) or subgroup (95.9% vs. 98.0%, p = 0.323) cohorts.

CONCLUSION

The revised threshold growth of LI-RADS v2018 was significantly associated with HCC. Use of threshold growth as a major diagnostic feature of HCC can improve the sensitivity of LI-RADS v2018.

IMPACT AND IMPLICATIONS

We found that the revised threshold growth in the Liver Imaging Reporting and Data System version 2018 (LI-RADS v2018) was a significant predictor of hepatocellular carcinoma (HCC). The use of threshold growth as a major imaging feature of HCC significantly increased the sensitivity of LI-RADS v2018, especially small HCCs (≤3.0 cm), compared with its non-use. Because these small HCCs are eligible for curative treatments, the additional detection of small HCCs is clinically meaningful.

Simplified LI-RADS for Hepatocellular Carcinoma Diagnosis at Gadoxetic Acid-enhanced MRI

Background Although various modifications to the Liver Imaging Reporting and Data System (LI-RADS) at gadoxetic acid-enhanced MRI have been suggested, LI-RADS shows suboptimal sensitivity for hepatocellular carcinoma (HCC) and is perceived to be too complex. Purpose To evaluate clinical usefulness of a simplified LI-RADS for diagnosing HCCs of 30 mm or smaller at gadoxetic acid-enhanced MRI. Materials and Methods Patients who underwent gadoxetic acid-enhanced MRI examination and subsequent resection, transplantation, or biopsy for focal solid nodules of 30 mm or smaller between January 2019 and December 2020 at a single tertiary referral institution were retrospectively analyzed. Two strategies for simplified LI-RADS using one size criterion (≥10 mm) were evaluated (strategy A, using classifications for nodules of 10-19 mm for nodules both 10-19 mm and ≥20 mm; strategy B, using classifications for nodules ≥20 mm for nodules both 10-19 mm and ≥20 mm). Multivariable analysis was performed to determine significant ancillary features for HCC. Generalized estimating equations were used to compare diagnostic performance for LR-5 (definite HCC) between LI-RADS version 2018 and simplified LI-RADS. The time required for LI-RADS category assignment was compared between the two systems with use of a paired t test. Results A total of 645 nodules from 510 patients (mean age ± SD, 60 years ± 10; 393 men) were evaluated. Compared with strategy A, strategy B had a higher sensitivity of 74% (347 of 470 nodules [95% CI: 70, 78]) vs 73% (342 of 470 nodules [95% CI: 69, 77]) (P = .02) with the same specificity of 96% (168 of 175 nodules [95% CI: 92, 98]) vs 96% (168 of 175 nodules [95% CI: 92, 98]) (P > .99). In strategy B, transitional phase hypointensity was an independent ancillary feature for HCC (P = .04) in LR-4 of at least 10 mm with arterial phase hyperenhancement and no other major features. In all 645 nodules, simplified LI-RADS with use of both strategy B and transitional phase hypointensity had a higher sensitivity of 82% (387 of 470 nodules [95% CI: 79, 86]) vs 73% (343 of 470 nodules [95% CI: 69, 77]) (P < .001) than LI-RADS version 2018, without lower specificity (94%, 165 of 175 nodules [95% CI: 90, 97] vs 96%, 168 of 175 nodules [95% CI: 92, 98], P = .08). Compared with LI-RADS version 2018, simplified LI-RADS reduced the time for LI-RADS category assignment (44 seconds ± 23 vs 74 seconds ± 22, P < .001). Conclusion A simplified Liver Imaging Reporting and Data System was found to be clinically useful for diagnosing hepatocellular carcinomas of 30 mm or smaller at gadoxetic acid-enhanced MRI. © RSNA, 2022 Online supplemental material is available for this article.

Modifying LI-RADS on Gadoxetate Disodium-Enhanced MRI: A Secondary Analysis of a Prospective Observational Study

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS) is widely used for diagnosing hepatocellular carcinoma (HCC), however, with unsatisfactory sensitivity, complex ancillary features, and inadequate integration with gadoxetate disodium (EOB)-enhanced MRI.

PURPOSE

To modify LI-RADS (mLI-RADS) on EOB-MRI.

STUDY TYPE

Secondary analysis of a prospective observational study.

POPULATION

Between July 2015 and September 2018, 224 consecutive high-risk patients (median age, 51 years; range, 26-83; 180 men; training/testing sets: 169/55 patients) with 742 (median size, 13 mm; interquartile range, 7-27; 498 HCCs) LR-3/4/5 observations.

FIELD STRENGTH/SEQUENCE

3.0 T T₂ -weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar, and 3D T₁ -weighted gradient echo sequences.

ASSESSMENT

Three radiologists (with 5, 5, and 10 years of experience in liver MR imaging, respectively) blinded to the reference standard (histopathology or imaging follow-up) reviewed all MR images independently. In the training set, the optimal LI-RADS version 2018 (v2018) features selected by Random Forest analysis were used to develop mLI-RADS via decision tree analysis.

STATISTICAL TESTS

In an independent testing set, diagnostic performances of mLI-RADS, LI-RADS v2018, and the Korean Liver Cancer Association (KLCA) guidelines were computed using a generalized estimating equation model and compared with McNemar's test. A two-tailed P < 0.05 was statistically significant.

RESULTS

Five features (nonperipheral "washout," restricted diffusion, nonrim arterial phase hyperenhancement [APHE], mild-moderate T2 hyperintensity, and transitional phase hypointensity) constituted mLI-RADS, and mLR-5 was nonperipheral washout coupled with either nonrim APHE or restricted diffusion. In the testing set, mLI-RADS was significantly more sensitive (72%) and accurate (80%) than LI-RADS v2018 (sensitivity, 61%; accuracy 74%; both P < 0.001) and the KLCA guidelines (sensitivity, 64%; accuracy 74%; both P < 0.001), without sacrificing positive predictive value (mLI-RADS, 94%; LI-RADS v2018, 94%; KLCA guidelines, 92%).

DATA CONCLUSION

In high-risk patients, the EOB-MRI-based mLI-RADS was simpler and more sensitive for HCC than LI-RADS v2018 while maintaining high positive predictive value.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

New strategy for Liver Imaging Reporting and Data System category M to improve diagnostic performance of MRI for hepatocellular carcinoma ≤ 3.0 cm

PURPOSE

We aimed to determine a new strategy for Liver Imaging Reporting and Data System category M (LR-M) criteria to improve the diagnosis of HCC ≤ 3.0 cm on magnetic resonance imaging (MRI).

METHODS

A total of 463 pathologically confirmed hepatic observations ≤ 3.0 cm (375 HCCs, 32 other malignancies, 56 benignities) in 384 patients at risk of HCC who underwent gadoxetate-enhanced MRI were retrospectively analyzed. Two radiologists evaluated the presence of major, ancillary, and LR-M features according to LI-RADS v2018. Of the ten LR-M features, those significantly associated with non-HCC malignancy were identified using multivariable logistic regression analysis, and new LR-M criteria for improving the diagnosis of HCC were investigated. Generalized estimating equations were used to compare sensitivity and specificity of LR-5 for diagnosing HCC using the new LR-M criteria with values calculated using the original LR-M criteria. p < 0.05 was considered to indicate a significant difference.

RESULTS

Of ten LR-M features, rim arterial-phase hyperenhancement, delayed central enhancement, targetoid restriction, and targetoid transitional-phase/hepatobiliary-phase appearance were independently significantly associated with non-HCC malignancy (adjusted odds ratio ≥ 6.2; p ≤ 0.02). Using the new LR-M criteria (two or more of these significant features), the sensitivity of LR-5 for diagnosing HCC was higher than that with the original LR-M criteria (69% [95% confidence interval 64-73%] vs. 65% [61-70%], p = 0.002), whereas the specificity was similar (90% [82-95%] vs. 92% [83-96%], p = 0.28).

CONCLUSION

The new LR-M criteria (two or more significant features) can improve the sensitivity of LR-5 for diagnosing HCC ≤ 3.0 cm, without compromising specificity.

Data-Driven Modification of the LI-RADS Major Feature System on Gadoxetate Disodium-Enhanced MRI: Toward Better Sensitivity and Simplicity

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS) is widely accepted as a reliable diagnostic scheme for hepatocellular carcinoma (HCC) in at-risk patients. However, its application is hampered by substantial complexity and suboptimal diagnostic sensitivity.

PURPOSE

To propose data-driven modifications to the LI-RADS version 2018 (v2018) major feature system (rLI-RADS) on gadoxetate disodium (EOB)-enhanced magnetic resonance imaging (MRI) to improve sensitivity and simplicity while maintaining high positive predictive value (PPV) for detecting HCC.

STUDY TYPE

Retrospective.

POPULATION

Two hundred and twenty-four consecutive at-risk patients (training dataset: 169, independent testing dataset: 55) with 742 LR-3 to LR-5 liver observations (HCC: N = 498 [67%]) were analyzed from a prospective observational registry collected between July 2015 and September 2018.

FIELD STRENGTH/SEQUENCE

3.0 T/T2-weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar and three-dimensional (3D) T1-weighted gradient echo sequences.

ASSESSMENT

All images were evaluated by three independent abdominal radiologists who were blinded to all clinical, pathological, and follow-up information. Composite reference standards of either histopathology or imaging follow-up were used.

STATISTICAL TESTS

In the training dataset, LI-RADS v2018 major features were used to develop rLI-RADS based on their associated PPV for HCC. In an independent testing set, diagnostic performances of LI-RADS v2018 and rLI-RADS were computed using a generalized estimating equation model and compared with McNemar's test. A P value <0.05 was considered statistically significant.

RESULTS

The median (interquartile range) size of liver observations was 13 mm (7-27 mm). The diagnostic table for rLI-RADS encompassed 9 cells, as opposed to 16 cells for LI-RADS v2018. In the testing set, compared to LI-RADS v2018, rLI-RADS category 5 demonstrated a significantly superior sensitivity (76% vs. 61%) while maintaining comparably high PPV (92.5% vs. 94.1%, P = 0.126).

DATA CONCLUSION

Compared with LI-RADS v2018, rLI-RADS demonstrated improved simplicity and significantly superior diagnostic sensitivity for HCC in at-risk patients.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Impact of the Liver Imaging Reporting and Data System on Research Studies of Diagnosing Hepatocellular Carcinoma Using MRI

Objective

Since its introduction in 2011, the CT/MRI diagnostic Liver Imaging Reporting and Data System (LI-RADS) has been updated in 2014, 2017, and 2018. We evaluated the impact of CT/MRI diagnostic LI-RADS on liver MRI research methodology for the diagnosis of hepatocellular carcinoma (HCC).

Materials and Methods

The MEDLINE, EMBASE, and Cochrane databases were searched for original articles reporting the diagnostic performance of liver MRI for HCC between 2011 and 2019. The MRI techniques, image analysis methods, and diagnostic criteria for HCC used in each study were investigated. The studies were classified into three groups according to the year of publication (2011–2013, 2014–2016, and 2017–2019). We compared the percentage of studies adopting MRI techniques recommended by LI-RADS, image analysis methods in accordance with the lexicon defined in LI-RADS, and diagnostic criteria endorsed by LI-RADS. We compared the pooled sensitivity and specificity between studies that used the LI-RADS and those that did not.

Results

This systematic review included 179 studies. The percentages of studies using imaging techniques recommended by LI-RADS were 77.8% for 2011–2013, 85.7% for 2014–2016, and 84.2% for 2017–2019, with no significant difference (p = 0.951). After the introduction of LI-RADS, the percentages of studies following the LI-RADS lexicon were 0.0%, 18.4%, and 56.6% in the respective periods (p < 0.001), while the percentages of studies using the LI-RADS diagnostic imaging criteria were 0.0%, 22.9%, and 60.7%, respectively (p < 0.001). Studies that did not use the LI-RADS and those that used the LI-RADS version 2018 showed no significant difference in sensitivity and specificity (86.3% vs. 77.7%, p = 0.102 and 91.4% vs. 89.9%, p = 0.770, respectively), with some difference in heterogeneity (I² = 94.3% vs. 86.7% in sensitivity and I² = 86.6% vs. 53.2% in specificity).

Conclusion

LI-RADS imparted significant changes in the image analysis methods and diagnostic criteria used in liver MRI research for the diagnosis of HCC.

Diagnostic Performance of KLCA-NCC 2018 Criteria for Hepatocellular Carcinoma Using Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

Several imaging-based systems have been proposed for the diagnosis of hepatocellular carcinoma (HCC) using magnetic resonance imaging (MRI), reflecting geographical differences in the clinical environment for HCC. We conducted a systematic review and meta-analysis to determine the performance of the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) 2018 criteria for the MRI diagnosis of HCC. Original studies reporting the performance of the KLCA-NCC 2018 criteria for the diagnosis of HCC using MRI were identified in MEDLINE and EMBASE until 29 March 2021. The meta-analytic pooled sensitivity and specificity of the KLCA-NCC 2018 criteria for diagnosing HCC were calculated using a bivariate random-effects model. A meta-regression analysis was performed to explore study heterogeneity further. Eight studies involving 1690 HCCs reported the accuracy of the KLCA-NCC 2018 imaging criteria. The pooled sensitivity and specificity of the definite HCC criteria for diagnosing HCC were 81% (95% confidence interval, 76-85%; I2 = 86%) and 90% (86-93%; I2 = 23%), respectively. For five available studies, the pooled sensitivity and specificity of the definite HCC criteria for diagnosing HCCs smaller than 20 mm were 80% (72-86%; I2 = 76%) and 91% (86-94%; I2 = 0%), respectively. A considerable threshold effect with a correlation coefficient of 0.667 was observed. The results of the meta-regression analysis revealed that the accuracy of the definite HCC criteria differed significantly depending on the type of MRI contrast agent (p = 0.01). In conclusion, the KLCA-NCC 2018 criteria had good overall diagnostic performance in diagnosing HCC. Substantial study heterogeneity was observed for sensitivity, which was significantly influenced by the type of contrast agent and by a threshold effect.

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.

Combined computed tomography and magnetic resonance imaging improves diagnosis of hepatocellular carcinoma ≤ 3.0 cm

BACKGROUND/PURPOSE

Imaging diagnosis of hepatocellular carcinoma (HCC) is important, but the diagnostic performance of combined computed tomography (CT) and magnetic resonance imaging (MRI) using the Liver Imaging Reporting and Data System (LI-RADS) v2018 is not fully understood. We evaluated the clinical usefulness of combined CT and MRI for diagnosing HCC ≤ 3.0 cm using LI-RADS.

METHODS

In 222 patients at risk of HCC who underwent both contrast-enhanced dynamic CT and gadoxetate disodium-enhanced MRI in 2017, 291 hepatic nodules ≤ 3.0 cm were retrospectively analyzed. Two radiologists performed image analysis and assigned a LI-RADS category to each nodule. The diagnostic performance for HCC was evaluated for CT, ordinary-MRI (washout confined to portal venous-phase), and modified-MRI (washout extended to hepatobiliary phase), and sensitivity and specificity were calculated for each modality. Generalized estimating equations were used to compare the diagnostic performance for HCC between combined CT and ordinary-MRI, combined CT and modified-MRI, and CT or MRI alone. p < 0.0062 (0.05/8) was considered statistically significant following Bonferroni correction for multiple comparisons.

RESULTS

In 291 nodules, the sensitivity and specificity of CT, ordinary-MRI, and modified-MRI were 70.2% and 92.8%, 72.6% and 96.4%, and 84.6% and 88.0%, respectively. Compared with CT or MRI alone, both combined CT and ordinary-MRI (sensitivity, 83.7%; specificity, 95.2%) and combined CT and modified-MRI (sensitivity, 88.9%; specificity, 89.2%) showed significantly higher sensitivity (p ≤ 0.006), without a significant decrease in specificity (p ≥ 0.314).

CONCLUSIONS

Compared with CT or MRI alone, combined CT and MRI can increase sensitivity for diagnosing HCC ≤ 3.0 cm, without a significant decrease in specificity.

LI-RADS category 5 hepatocellular carcinoma: preoperative gadoxetic acid-enhanced MRI for early recurrence risk stratification after curative resection

OBJECTIVES

To explore the role of preoperative gadoxetic acid-enhanced MRI in stratifying the risk of early recurrence in patients with LR-5 hepatocellular carcinoma (HCC) by LI-RADS v2018 after curative resection.

METHODS

Between July 2015 and August 2018, this study evaluated consecutive treatment-naïve at-risk LR-5 HCC patients who underwent gadoxetic acid-enhanced MRI examination within 2 weeks before curative resection. The Cox regression analysis was performed to identify potential predictors of early recurrence. Disease-free survival (DFS) rates were analyzed and compared by using the Kaplan-Meier method and log-rank tests.

RESULTS

Fifty-three of 103 (51.5%) patients experienced early recurrence. Three MRI findings were significantly associated with early recurrence: corona enhancement (hazard ratio [HR]: 2.116; p = 0.013), peritumoral hypointensity on hepatobiliary phase (HBP) (HR: 2.262; p = 0.007), and satellite nodule (HR: 2.777; p = 0.005). An additional risk factor was AFP level > 400 ng/mL (HR: 1.975; p = 0.016). Based on the number of MRI predictors, LR-5 HCC patients were stratified into three subgroups: LR-5a (60/103; no predictor), LR-5b (26/103; one predictor), and LR-5c (17/103; two or three predictors), with low, medium, and high risk of early recurrence, respectively. The 2-year DFS rate of LR-5a, LR-5b, and LR-5c patients was 65.0%, 38.5%, and 5.9%, respectively, while the corresponding median DFS was undefined, 17.1 months, and 5.1 months, respectively (p < 0.001).

CONCLUSIONS

In at-risk LR-5 HCC patients, corona enhancement, peritumoral hypointensity on HBP, and satellite nodule could be used to preoperatively stratify the risk of early recurrence after hepatectomy.

KEY POINTS

• Corona enhancement, peritumoral hypointensity on HBP, satellite nodule, and serum AFP level > 400 ng/mL were significant predictors of early recurrence in patients with LR-5 HCC after hepatectomy. • Based on the number of predictive MRI findings, LR-5 HCC patients could be preoperatively stratified into three subgroups: LR-5a, LR-5b, and LR-5c, with significantly different risk of early recurrence and disease-free survival. • Preoperative risk stratification is essential for the identification of patients at increased risk of postoperative early recurrence, which may contribute to risk-based personalized management for LR-5 HCC patients.

Inter-reader reliability of CT Liver Imaging Reporting and Data System according to imaging analysis methodology: a systematic review and meta-analysis

OBJECTIVES

To establish inter-reader reliability of CT Liver Imaging Reporting and Data System (LI-RADS) and explore factors that affect it.

METHODS

MEDLINE and EMBASE databases were searched from January 2014 to March 2020 to identify original articles reporting the inter-reader reliability of CT LI-RADS. The imaging analysis methodology of each study was identified, and pooled intraclass correlation coefficient (ICC) or kappa values (κ) were calculated for lesion size, major features (arterial-phase hyperenhancement [APHE], nonperipheral washout [WO], and enhancing capsule [EC]), and LI-RADS categorization (LR) using random-effects models. Subgroup analyses of pooled κ were performed for the number of readers, average reader experience, differences in reader experience, and LI-RADS version.

RESULTS

In the 12 included studies, the pooled ICC or κ of lesion size, APHE, WO, EC, and LR were 0.99 (0.96-1.00), 0.69 (0.58-0.81), 0.67 (0.53-0.82), 0.65 (0.54-0.76), and 0.70 (0.59-0.82), respectively. The experience and number of readers varied: studies using readers with ≥ 10 years of experience showed significantly higher κ for LR (0.82 vs. 0.45, p = 0.01) than those with < 10 years of reader experience. Studies with multiple readers including inexperienced readers showed significantly lower κ for APHE (0.55 vs. 0.76, p = 0.04) and LR (0.45 vs. 0.79, p = 0.02) than those with all experienced readers.

CONCLUSIONS

CT LI-RADS showed substantial inter-reader reliability for major features and LR. Inter-reader reliability differed significantly according to average reader experience and differences in reader experience. Reported results for inter-reader reliability of CT LI-RADS should be understood with consideration of the imaging analysis methodology.

KEY POINTS

• The CT Liver Imaging Reporting and Data System (LI-RADS) provides substantial inter-reader reliability for three major features and category assignment. • The imaging analysis methodology varied across studies. • The inter-reader reliability of CT LI-RADS differed significantly according to the average reader experience and the difference in reader experience.

Accuracy of contrast-enhanced ultrasound liver imaging reporting and data system: a systematic review and meta-analysis

BACKGROUND AND AIM

After the introduction of the contrast-enhanced ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS), several studies have reported on its performance, but the reported data vary considerably. Therefore, we performed a systematic review and meta-analysis to determine the diagnostic performance of CEUS LI-RADS in patients at risk for hepatocellular carcinoma (HCC) and investigate the causes of study heterogeneity.

METHODS

Original studies published until May 30, 2020, investigating the diagnostic performance of CEUS LI-RADS were identified in the MEDLINE, EMBASE, and Cochrane library databases. Study quality was assessed using the QUADAS-2 tool. Meta-analytic summary sensitivity and specificity for the diagnosis of HCC were calculated using a bivariate random-effects model. Meta-regression analysis was performed to explore the causes of study heterogeneity.

RESULTS

Of the 105 articles screened, eight studies were finally analyzed (5428 hepatic observations). The summary sensitivity and specificity of CEUS LI-RADS category 5 (LR-5) for diagnosing HCC were 73% [95% confidence interval (CI) 65-79%; I² = 93%] and 95% (95% CI 91-97%; I² = 89%), respectively. Substantial study heterogeneity was noted in both sensitivity and specificity. Study heterogeneity was significantly associated with the proportion of cases of HCC and the type of reference standard (p ≤ 0.05).

CONCLUSION

CEUS LI-RADS had high pooled specificity for diagnosing HCC but suboptimal pooled sensitivity. Substantial study heterogeneity was found, which was significantly associated with the proportion of cases of HCC and the type of reference standard.

Diagnostic performance of ultrasonography-guided core-needle biopsy according to MRI LI-RADS diagnostic categories

Purpose

According to the American Association for the Study of Liver Diseases (AASLD) guidelines, biopsy is a diagnostic option for focal hepatic lesions depending on the Liver Imaging Reporting and Data System (LI-RADS) category. We evaluated the diagnostic performance of ultrasonography-guided core-needle biopsy (CNB) according to LI-RADS categories.

Methods

A total of 145 High-risk patients for hepatocellular carcinoma (HCC) who underwent magnetic resonance imaging (MRI) followed by CNB for a focal hepatic lesion preoperatively were retrospectively enrolled. Focal hepatic lesions on MRI were evaluated according to LI-RADS version 2018. Pathologic results were categorized into HCC, non-HCC malignancies, and benignity. The categorization was defined as correct when the CNB pathology and surgical pathology reports were identical. Nondiagnostic results were defined as inadequate CNB pathology findings for a specific diagnosis. The proportion of correct categorizations was calculated for each LI-RADS category, excluding nondiagnostic results.

Results

After excluding 16 nondiagnostic results, 131 lesions were analyzed (45 LR-5, 24 LR-4, 4 LR-3, and 58 LR-M). All LR-5 lesions were HCC, and CNB correctly categorized 97.8% (44/45) of LR-5 lesions. CNB correctly categorized all 24 LR-4 lesions, 16.7% (4/24) of which were non-HCC malignancies. All LR-M lesions were malignant, and 62.1% (36/58) were non-HCC malignancies. CNB correctly categorized 93.1% (54/58) of LR-M lesions, and 12.5% (3/24) of lesions with CNB results of HCC were confirmed as non-HCC malignancies.

Conclusion

In agreement with AASLD guidelines, CNB could be helpful for LR-4 lesions, but is unnecessary for LR-5 lesions. In LR-M lesions, CNB results of HCC did not exclude non-HCC malignancy.

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.

Comparison of LI-RADS 2018 and KLCA-NCC 2018 for noninvasive diagnosis of hepatocellular carcinoma using magnetic resonance imaging

Background/Aims

This study aimed to compare the diagnostic performances of Liver Imaging Reporting and Data System (LI-RADS) 2018 and Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) 2018 criteria on magnetic resonance imaging (MRI) for the noninvasive diagnosis of hepatocellular carcinoma (HCC) in high-risk patients.

Methods

This retrospective study included 273 treatment-naïve patients (71 patients with extracellular contrast agent [ECA]-MRI and 202 patients with hepatobiliary agent [HBA]-MRI; 352 lesions including 263 HCCs) with high risk of HCC who underwent contrast-enhanced MRI between 2016 and 2017. Two readers evaluated all lesions according to the criteria of LI-RADS 2018 and KLCA-NCC 2018. The per-lesion diagnostic performances were compared using the generalized estimating equation method.

Results

On ECA-MRI, the sensitivity and specificity of LI-RADS 2018 and KLCA-NCC 2018 were not significantly different (LR-5 vs. definite HCC: 75.8% vs. 69.4%, P=0.095 and 95.8% vs. 95.8%, P>0.999; LR-5/4 vs. definite/probable HCC: 87.1% vs.83.9%, P=0.313 and 87.5% vs. 91.7%, P=0.307). On HBA-MRI, definite HCC of KLCA-NCC 2018 showed significantly higher sensitivity (79.1% vs. 68.2%, P<0.001) than LR-5 of LI-RADS 2018 without a significant difference in specificity (93.9% vs. 95.4%, P=0.314). Definite/probable HCC of KLCA-NCC 2018 had higher specificity (92.3% vs. 80.0%, P=0.003) than LR-5/4 of LI-RADS 2018. The sensitivity was lower for definite/probable HCC than for LR-5/4 without statistical significance (85.6% vs. 88.1%, P=0.057).

Conclusions

On ECA-MRI, LI-RADS 2018 and KLCA-NCC 2018 showed comparable diagnostic performances. On HBA-MRI, definite HCC of KLCA-NCC 2018 provided better sensitivity than LR-5 category of LI-RADS 2018 without compromising the specificity, while definite/probable HCC of KLCA-NCC 2018 revealed higher specificity than LR-5/4 of LI-RADS 2018 for diagnosing 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.

Comparison of the diagnostic performance of imaging criteria for HCCs ≤ 3.0 cm on gadoxetate disodium-enhanced MRI

BACKGROUND AND PURPOSE

Imaging-based diagnostic systems play important roles in hepatocellular carcinoma (HCC). We aimed to compare the diagnostic performance of recently updated imaging criteria for HCCs ≤ 3.0 cm on gadoxetate disodium-enhanced magnetic resonance imaging (MRI).

METHODS

493 nodules (399 HCCs, 24 other malignancies, 70 benign) 1.0-3.0 cm from 400 patients, including 322 male (mean age 59.3 ± 9.4 years) and 78 female (mean age 61.2 ± 9.0 years), at risk for HCC who underwent gadoxetate disodium-enhanced MRI between July 2015 and December 2016 were retrospectively evaluated. Final diagnosis was determined histopathologically or clinically. The sensitivity and specificity in diagnosing HCC of the latest versions of four imaging criteria [Liver Imaging Reporting and Data System (LI-RADS), European Association for the Study of the Liver (EASL), Asian Pacific Association for the Study of the Liver (APASL), Korean Liver Cancer Association-National Cancer Center (KLCA-NCC)] were compared using generalized estimating equations.

RESULTS

In 331 only pathologically diagnosed nodules, the sensitivities of both the APASL (86.8%) and KLCA-NCC criteria (85.4%) were significantly higher than the sensitivities of the EASL (71.8%) and LR-5 (71.1%) criteria (p < 0.001 for each pairwise comparison). However, the specificity of LR-5 was significantly higher than that of APASL (92.2% vs. 70.6%, respectively; p = 0.011) but did not differ significantly from the specificities of EASL (84.3%; p = 0.634) and KLCA-NCC (78.4%; p = 0.107).

CONCLUSION

Of the four international imaging criteria, LI-RADS and EASL showed high specificity but suboptimal sensitivity for diagnosing HCCs ≤ 3 cm. However, APASL and KLCA-NCC had a higher sensitivity but a lower specificity than LI-RADS and EASL.