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

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.

Re-assessing the diagnostic value of the enhancing capsule in hepatocellular carcinoma imaging

BACKGROUNDS/AIMS

The enhancing capsule (EC) in hepatocellular carcinoma (HCC) diagnosis has received varying degrees of recognition across major guidelines. This study aimed to assess the diagnostic utility of EC in HCC detection.

METHODS

We retrospectively analyzed patients who underwent pre-surgical computed tomography (CT) and hepatobiliary agent-enhanced magnetic resonance imaging (HBA-MRI) between January 2016 and December 2019. A single hepatic tumor was confirmed based on the pathology of each patient. Three radiologists independently reviewed the images according to the Liver Imaging Reporting and Data System (LI-RADS) v2018 criteria and reached a consensus. Interobserver agreement for EC before reaching a consensus was quantified using Fleiss κ statistics. The impact of EC on the LI-RADS classification was assessed by comparing the positive predictive values for HCC detection in the presence and absence of EC.

RESULTS

In total, 237 patients (median age, 60 years; 184 men) with 237 observations were included. The interobserver agreement for EC detection was notably low for CT (κ=0.169) and HBA-MRI (κ=0.138). The presence of EC did not significantly alter the positive predictive value for HCC detection in LI-RADS category 5 observations on CT (94.1% [80/85] vs. 94.6% [88/93], P=0.886) or HBAMRI (95.7% [88/92] vs. 90.6% [77/85], P=0.178).

CONCLUSIONS

The diagnostic value of EC in HCC diagnosis remains questionable, given its poor interobserver agreement and negligible impact on positive predictive values for HCC detection. This study challenges the emphasis on EC in certain diagnostic guidelines and suggests the need to re-evaluate its role in HCC imaging.

Systematic training of LI-RADS CT v2018 improves interobserver agreements and performances in LR categorization for focal liver lesions

AIM

To retrospectively explored whether systematic training in the use of Liver Imaging Reporting and Data System (LI-RADS) v2018 on computed tomography (CT) can improve the interobserver agreements and performances in LR categorization for focal liver lesions (FLLs) among different radiologists.

MATERIALS AND METHODS

A total of 18 visiting radiologists and the liver multiphase CT images of 70 hepatic observations in 63 patients at high risk of HCC were included in this study. The LI-RADS v2018 training procedure included three thematic lectures, with an interval of 1 month. After each seminar, the radiologists had 1 month to adopt the algorithm into their daily work. The interobserver agreements and performances in LR categorization for FLLs among the radiologists before and after training were compared.

RESULTS

After training, the interobserver agreements in classifying the LR categories for all radiologists were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.053). After systematic training, the areas under the curve (AUCs) for LR categorization performance for all participants were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.062).

CONCLUSION

Systematic training in the use of the LI-RADS can improve the interobserver agreements and performances in LR categorization for FLLs among radiologists with different levels of experience.

Can absolute arterial phase hyperenhancement improve sensitivity of detection of hepatocellular carcinoma in indeterminate nodules on CT?

OBJECTIVES

To determine if quantitative assessment of relative (R) and absolute (A) arterial phase hyperenhancement (APHE) and washout (WO) applied to indeterminate nodules on CT would improve the overall sensitivity of detection of hepatocellular carcinoma (HCC).

METHODS

One-hundred and fourteen patients (90 male; mean age, 65 years) with 210 treatment-naïve HCC nodules (190 HCCs, 20 benign) who underwent 4-phase CT were included in this retrospective study. Four radiologists independently assigned a qualitative LR (LI-RADS) category per nodule. LR-3/4 nodules were then quantitatively analyzed by the 4 readers, placing ROIs within nodules and adjacent liver parenchyma. A/R-APHE and WO were calculated, and per-reader sensitivity and specificity updated. Interobserver agreement and AUCs were calculated per reader.

RESULTS

Qualitative readers 1-4 categorized 57, 69, 57, and 63 nodules as LR-3/4 respectively with moderate to substantial agreement in LR category (kappa 0.56-0.69, p < 0.0001); their diagnostic performances in the detection of HCC were 80%, 73.2%, 77.4%, and 77.4% sensitivity, and 100%, 95%, 70%, and 100% specificity, respectively. A threshold of ≥ 20 HU for A-APHE increased overall sensitivity of HCC detection by 0.5-3.1% without changing specificity for the subset of nodules APHE - /WO + on qualitative read, with 2, 6, 6, and 1 additional HCC detected by readers 1-4. Relative and various A-WO formulae and thresholds all increased sensitivity, but with a drop in specificity for some/all readers.

CONCLUSION

Quantitatively assessed A-APHE showed potential to increase sensitivity and maintain specificity of HCC diagnosis when selectively applied to indeterminate nodules demonstrating WO without subjective APHE. Quantitatively assessed R and A-WO increased sensitivity, however reduced specificity.

CLINICAL RELEVANCE STATEMENT

A workflow using selective quantification of absolute arterial enhancement is routinely employed in the CT assessment of renal and adrenal nodules. Quantitatively assessed absolute arterial enhancement is a simple tool which may be used as an adjunct to help increase sensitivity and maintain specificity of HCC diagnosis in indeterminate nodules demonstrating WO without subjective APHE.

KEY POINTS

• In indeterminate nodules categorized as LI-RADS 3/4 due to absent subjective arterial phase hyperenhancement, a cut-off for absolute arterial phase hyperenhancement of ≥ 20 HU may increase the overall sensitivity of detection of HCC by 0.5-3.1% without affecting specificity. • Relative and various absolute washout formulae and cut-offs increased sensitivity of HCC detection, but with a drop in specificity for some/all readers.

Association of LI-RADS and Histopathologic Features with Survival in Patients with Solitary Resected Hepatocellular Carcinoma

Background Both Liver Imaging Reporting and Data System (LI-RADS) and histopathologic features provide prognostic information in patients with hepatocellular carcinoma (HCC), but whether LI-RADS is independently associated with survival is uncertain. Purpose To assess the association of LI-RADS categories and features with survival outcomes in patients with solitary resected HCC. Materials and Methods This retrospective study included patients with solitary resected HCC from three institutions examined with preoperative contrast-enhanced CT and/or MRI between January 2008 and December 2019. Three independent readers evaluated the LI-RADS version 2018 categories and features. Histopathologic features including World Health Organization tumor grade, microvascular and macrovascular invasion, satellite nodules, and tumor capsule were recorded. Overall survival and disease-free survival were assessed with Cox regression models. Marginal effects of nontargetoid features on survival were estimated using propensity score matching. Results A total of 360 patients (median age, 64 years [IQR, 56-70 years]; 280 male patients) were included. At CT and MRI, the LI-RADS LR-M category was associated with increased risk of recurrence (CT: hazard ratio [HR] = 1.83 [95% CI: 1.26, 2.66], P = .001; MRI: HR = 2.22 [95% CI: 1.56, 3.16], P < .001) and death (CT: HR = 2.47 [95% CI: 1.72, 3.55], P < .001; MRI: HR = 1.80 [95% CI: 1.32, 2.46], P < .001) independently of histopathologic features. The presence of at least one nontargetoid feature was associated with an increased risk of recurrence (CT: HR = 1.80 [95% CI: 1.36, 2.38], P < .001; MRI: HR = 1.93 [95% CI: 1.81, 2.06], P < .001) and death (CT: HR = 1.51 [95% CI: 1.10, 2.07], P < .010) independently of histopathologic features. In matched samples, recurrence was associated with the presence of at least one nontargetoid feature at CT (HR = 2.06 [95% CI: 1.15, 3.66]; P = .02) or MRI (HR = 1.79 [95% CI: 1.01, 3.20]; P = .048). Conclusion In patients with solitary resected HCC, LR-M category and nontargetoid features were negatively associated with survival independently of histopathologic characteristics. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kartalis and Grigoriadis in this issue.

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

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

Automated CT LI-RADS v2018 scoring of liver observations using machine learning: A multivendor, multicentre retrospective study

Background & Aims

Assessment of computed tomography (CT)/magnetic resonance imaging Liver Imaging Reporting and Data System (LI-RADS) v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. We assessed the performance and added-value of a machine learning (ML)-based algorithm in assessing CT LI-RADS major features and categorisation of liver observations compared with qualitative assessment performed by a panel of radiologists.

Methods

High-risk patients as per LI-RADS v2018 with pathologically proven liver lesions who underwent multiphase contrast-enhanced CT at diagnosis between January 2015 and March 2019 in seven centres in five countries were retrospectively included and randomly divided into a training set (n = 84 lesions) and a test set (n = 345 lesions). An ML algorithm was trained to classify non-rim arterial phase hyperenhancement, washout, and enhancing capsule as present, absent, or of uncertain presence. LI-RADS major features and categories were compared with qualitative assessment of two independent readers. The performance of a sequential use of the ML algorithm and independent readers were also evaluated in a triage and an add-on scenario in LR-3/4 lesions. The combined evaluation of three other senior readers was used as reference standard.

Results

A total of 318 patients bearing 429 lesions were included. Sensitivity and specificity for LR-5 in the test set were 0.67 (95% CI, 0.62-0.72) and 0.91 (95% CI, 0.87-0.96) respectively, with 242 (70.1%) lesions accurately categorised. Using the ML algorithm in a triage scenario improved the overall performance for LR-5. (0.86 and 0.93 sensitivity, 0.82 and 0.76 specificity, 78% and 82.3% accuracy for the two independent readers).

Conclusions

Quantitative assessment of CT LI-RADS v2018 major features is feasible and diagnoses LR-5 observations with high performance especially in combination with the radiologist's visual analysis in patients at high-risk for HCC.

Impact and implications

Assessment of CT/MRI LI-RADS v2018 major features leads to substantial inter-reader variability and potential decrease in hepatocellular carcinoma diagnostic accuracy. Rather than replacing radiologists, our results highlight the potential benefit from the radiologist-artificial intelligence interaction in improving focal liver lesions characterisation by using the developed algorithm as a triage tool to the radiologist's visual analysis. Such an AI-enriched diagnostic pathway may help standardise and improve the quality of analysis of liver lesions in patients at high risk for HCC, especially in non-expert centres in liver imaging. It may also impact the clinical decision-making and guide the clinician in identifying the lesions to be biopsied, for instance in patients with multiple liver focal lesions.

The role of enhancing capsule and modified capsule appearances in LI-RADS for diagnosing HCC ≤ 3.0 cm on gadoxetate disodium-enhanced MRI

OBJECTIVES

To evaluate the value of using enhancing capsule (EC) or modified capsule appearance as a major feature in LI-RADS for diagnosing HCC ≤ 3.0 cm on gadoxetate disodium-enhanced MRI (Gd-EOB-MRI), and to explore the relationship between the imaging features and the histological fibrous capsule.

METHODS

This retrospective study enrolled 342 hepatic lesions ≤ 3.0 cm in 319 patients that underwent Gd-EOB-MRIs from January 2018 to March 2021. During dynamic phases and hepatobiliary phase, the modified capsule appearance added the nonenhancing capsule (NEC) (modified LI-RADS + NEC) or corona enhancement (CoE) (modified LI-RADS + CoE) to EC as an alternative capsule appearance. Inter-reader agreement of imaging features was assessed. The diagnostic performances of LI-RADS, LI-RADS with EC ignored, and two modified LI-RADS were compared, followed by Bonferroni correction. Multivariable regression analysis was performed to identify the independent features associated with the histological fibrous capsule.

RESULTS

The inter-reader agreement on EC (0.64) was lower than that on the NEC alternative (0.71) but better than that on CoE alternative (0.58). For HCC diagnosis, compared to LI-RADS, LI-RADS with EC ignored showed significantly lower sensitivity (72.7% vs. 67.4%, p < 0.001) with comparable specificity (89.3% vs. 90.7%, p = 1.000). Two modified LI-RADS showed slightly higher sensitivity and lower specificity than LI-RADS, without statistical significance (all p ≥ 0.006). The AUC was highest with modified LI-RADS + NEC (0.82). Both EC and NEC were significantly associated with the fibrous capsule (p < 0.05).

CONCLUSION

EC appearance improved the diagnostic sensitivity of LI-RADS for HCC ≤ 3.0 cm on Gd-EOB-MRI. Considering NEC as an alternative capsule appearance allowed for better inter-reader reliability and comparable diagnostic ability.

KEY POINTS

• Using the enhancing capsule as a major feature in LI-RADS significantly improved the sensitivity of diagnosing HCC ≤ 3.0 cm without reducing specificity on gadoxetate disodium-enhanced MRI. • Compared to the corona enhancement, the nonenhancing capsule might be a preferable alternative capsule appearance for diagnosing HCC ≤ 3.0 cm. • Capsule appearance should be considered a major feature in LI-RADS for diagnosing HCC ≤ 3.0 cm, regardless whether the capsule appears to be enhancing or nonenhancing.

Improving detection performance of hepatocellular carcinoma and interobserver agreement for liver imaging reporting and data system on CT using deep learning reconstruction

PURPOSE

This study aimed to compare the hepatocellular carcinoma (HCC) detection performance, interobserver agreement for Liver Imaging Reporting and Data System (LI-RADS) categories, and image quality between deep learning reconstruction (DLR) and conventional hybrid iterative reconstruction (Hybrid IR) in CT.

METHODS

This retrospective study included patients who underwent abdominal dynamic contrast-enhanced CT between October 2021 and March 2022. Arterial, portal, and delayed phase images were reconstructed using DLR and Hybrid IR. Two blinded readers independently read the image sets with detecting HCCs, scoring LI-RADS, and evaluating image quality.

RESULTS

A total of 26 patients with HCC (mean age, 73 years ± 12.3) and 23 patients without HCC (mean age, 66 years ± 14.7) were included. The figures of merit (FOM) for the jackknife alternative free-response receiver operating characteristic analysis in detecting HCC averaged for the readers were 0.925 (reader 1, 0.937; reader 2, 0.913) in DLR and 0.878 (reader 1, 0.904; reader 2, 0.851) in Hybrid IR, and the FOM in DLR were significantly higher than that in Hybrid IR (p = 0.038). The interobserver agreement (Cohen's weighted kappa statistics) for LI-RADS categories was moderate for DLR (0.595; 95% CI, 0.585-0.605) and significantly superior to Hybrid IR (0.568; 95% CI, 0.553-0.582). According to both readers, DLR was significantly superior to Hybrid IR in terms of image quality (p ≤ 0.021).

CONCLUSION

DLR improved HCC detection, interobserver agreement for LI-RADS categories, and image quality in evaluations of HCC compared to Hybrid IR in abdominal dynamic contrast-enhanced CT.

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.

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.

Do transition and hepatobiliary phase hypointensity improve LI-RADS categorization as an alternative washout: a systematic review and meta-analysis

OBJECTIVE

The definition of washout in gadoxetate disodium-enhanced MRI (Gd-EOB-MRI) is controversial. The current Liver Imaging Reporting and Data System (LI-RADS) defines washout only in the portal venous phase on Gd-EOB-MRI, leading to low diagnostic sensitivity for HCC. We performed a meta-analysis to compare the diagnostic performance of Gd-EOB-MRI using conventional (cWO) and modified (mWO) definitions of washout.

METHODS

The PubMed and EMBASE databases were searched to identify studies published between January 1, 2010, and August 1, 2021, that compared the diagnostic performance of cWO and mWO for HCC. The mWOs added transition phase (TP) hypointensity (mWO-1), hepatobiliary phase (HBP) hypointensity (mWO-2), or both (mWO-3). The pooled sensitivity and specificity were calculated using a bivariate random-effects model. Study heterogeneity was explored by subgroup analysis and meta-regression analysis.

RESULTS

Ten comparative studies with 2391 patients were included. Compared to cWO, the overall mWO yielded significantly higher sensitivity (71% vs. 81%, p = 0.00) and lower specificity (97% vs. 93%, p = 0.01) for diagnosing HCC. The area under the curve (AUC) was 0.90 and 0.94 for the cWO and mWO, respectively. Regarding the three types of mWOs, mWO-2 showed the highest sensitivity (85%) and specificity (96%) for diagnosing HCC. mWO-2 achieved the highest AUC (0.97), followed by mWO-1 (0.90), and mWO-3 (0.89). Average reviewer experience and scanner field strength were significantly associated with study heterogeneity (p < 0.05).

CONCLUSIONS

Inclusion of TP and HBP hypointensity in the definition of washout improved the sensitivity with slightly lower specificity for diagnosing HCC in LI-RADS.

KEY POINTS

• Compared to the conventional definition of washout, studies using a modified definition had higher sensitivity (71% vs. 81%) but lower specificity (97% vs. 93%) in LI-RADS for the diagnosis of HCC. • Hepatobiliary phase hypointensity may be a preferred alternative washout for HCC diagnosis with the highest area under the curve. • Studies with experienced reviewer or 3.0T MRI showed higher sensitivity and lower specificity for diagnosing HCC when using modified washout (p < 0.05).

Trends in Incidence and Prognostic Factors of Two Subtypes of Primary Liver Cancers: A Surveillance, Epidemiology, and End Results-Based Population Study

OBJECTIVES

The objective of our study was to investigate and compare the epidemiologic characteristics, prognostic factors, and survival between hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) patients.

METHODS

Age-adjusted incidence rates were evaluated from 1975 to 2016 using the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival (OS) was investigated using the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression analyses were performed to identify the independent prognostic factors for OS.

RESULTS

In the last 10 years, the incidence rate of ICC increased rapidly by 109% (annual percentage change (APC) = 8.24, 95% CI = 6.64 to 9.86; P < .001), compared with a much more modest 12% increase in the incidence of HCC (APC = 1.59, 95% CI = .56 to 2.62; P < .001). This trend persisted throughout the study across different age groups, sexes, and races. Males older than 70 years and of other races (non-African American and non-Caucasian) showed the highest incidence rates of HCC and ICC. Multivariate Cox regression analysis demonstrated that other race, married status, later year of diagnosis, more examined lymph nodes, and surgery were significant protective factors of OS in HCC patients. In contrast, the race and year of diagnosis were not independent prognostic factors, but radiation and chemotherapy were protective factors of OS in ICC patients. The median OS was 18 months and 12 months in HCC and ICC patients, respectively.

CONCLUSION

In the last 10 years, the incidence of HCC had a slow growth in the United States, whereas ICC showed a remarkable increase. The 5-year OS of the former has improved in recent years while that of the latter showed no significant improvement. Therefore, surgery could contribute to superior survival outcomes as compared to other treatments.

Inter-reader reliability of contrast-enhanced ultrasound Liver Imaging Reporting and Data System: a meta-analysis

PURPOSE

To systematically determine the inter-reader reliability of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS), with emphasis on its major features for hepatocellular carcinoma (HCC) and LR-M (LI-RADS category M) features for non-HCC malignancy.

METHODS

MEDLINE, EMBASE, and Cochrane databases were searched from January 2016 to March 2021 to identify original articles reporting the inter-reader reliability of CEUS LI-RADS. Meta-analytic pooled kappa values (κ) were calculated for major features [nonrim arterial-phase hyperenhancement (APHE), mild and late washout], LR-M features (rim APHE, early washout), and LI-RADS categorization using the DerSimonian-Laird random-effects model. Meta-regression analysis was performed to explore any causes of study heterogeneity.

RESULTS

Twelve studies with a total of 2862 lesions were included. The meta-analytic pooled κ of nonrim APHE, mild and late washout, rim APHE, early washout, and LI-RADS categorization were 0.73 [95% confidence interval (CI), 0.67 - 0.79], 0.69 (95% CI, 0.54-0.84), 0.54 (95% CI, 0.37-0.71), 0.62 (95% CI, 0.45-0.79), and 0.75 (95% CI, 0.64-0.87), respectively. Compared with the major features, LR-M features had a lower meta-analytic pooled κ. Substantial study heterogeneity was noted in the LI-RADS categorization, and lesion size (p = 0.03) and the homogeneity in reader experience (p = 0.03) were significantly associated with study heterogeneity.

CONCLUSIONS

CEUS LI-RADS showed substantial inter-reader reliability for major features and LI-RADS categorization, but relatively lower reliability was found for LR-M features. In our opinion, the definitions of imaging features require further refinement to improve the inter-reader reliability of CEUS LI-RADS.