Interobserver and intermodality agreement of standardized algorithms for non-invasive diagnosis of hepatocellular carcinoma in high-risk patients: CEUS-LI-RADS versus MRI-LI-RADS

Training on contrast-enhanced ultrasound LI-RADS classification for resident radiologists: a retrospective comparison of performance after training

OBJECTIVES

To evaluate the effects and benefits of training radiology residents on contrast-enhanced ultrasound (CEUS) according to the Liver Imaging Reporting and Data System (LI-RADS).

METHODS

In total, 234 patients at high risk of hepatocellular carcinoma (HCC) who underwent CEUS were enrolled, including 27 lesions in the education set and 207 lesions in the test sets (a-d). Forty-five radiology residents and 4 radiology experts involved in CEUS LI-RADS training individually reviewed the test sets before, immediately after, and 3-months after training. The consistency with kappa values of the description of CEUS features, the classification of focal liver lesions (FLLs), and the diagnostic performance were evaluated.

RESULTS

The level of agreement between the radiology experts and residents improved after training (all p < 0.05), while there were no significant differences between the post-training and 3-months post-training results (all p > 0.05). The sensitivity, specificity, positive predictive value, and area under the curve (AUC) based on the CEUS LI-RADS classification of the radiology experts in the diagnosis of HCC were 62.9%, 96.4%, 96.3%, and 0.796, respectively. The diagnostic performance of the radiology residents significantly improved after training (all p < 0.05). Misunderstanding of definitions and subjective interpretation of images were the main reasons for disagreement with multiple responses.

CONCLUSION

Dedicated CEUS LI-RADS training improved the performance of radiology residents in diagnosing FLLs and their agreement with radiology experts on CEUS features. Images and videos to explain typical features of the training were essential to improve agreement between the radiology experts and residents.

CRITICAL RELEVANCE STATEMENT

Agreement on lesion descriptors between radiology experts and residents can improve with training.

KEY POINTS

The diagnostic performance of less experienced radiologists for diagnosing HCC could be improved by training. Images and videos to explain typical features during training were essential. Agreement on lesion descriptors between radiology experts and residents improved after training.

The comparison of contrast-enhanced ultrasound and gadoxetate disodium-enhanced MRI LI-RADS for nodules ≤2 cm in patients at high risk for HCC: a prospective study

Objectives

To investigate the consistency of LI-RADS of CEUS and EOB-MRI in the categorization of liver nodules ≤2cm in patients at high risk for HCC.

Methods

Patients at high risk for HCC with nodules ≤2cm who underwent CEUS and EOB-MRI in our hospital were prospectively enrolled. The CEUS images and EOB-MRI imaging of each liver nodule were observed to evaluate inter-observer consistency and category according to CEUS LI-RADS V2017 and CT/MRI LI-RADS V2017 criteria double blinded. Pathology and/or follow-up were used as reference standard.

Results

A total of 127 nodules in 119 patients met the inclusion criteria. The inter-observer agreement was good on CEUS and EOB-MRI LI-RADS (kappa = 0.76, 0.76 p < 0.001). The inter-modality agreement was fair (kappa=0.21, p < 0.001). There was no statistical difference in PPV and specificity between CEUS and EOB-MRI LR-5 for HCC, while the difference in AUC was statistically significant. We used new criteria (CEUS LR-5 and EOB-MRI LR-4/5 or CEUS LR-4/5 and EOB-MRI LR-5) to diagnose HCC. The sensitivity, specificity, and AUC of this criteria was 63.4%, 95.6%, and 0.80.

Conclusions

CEUS and EOB-MRI showed fair inter-modality agreement in LI-RADS categorization of nodules ≤2 cm. The inter-observer agreement of CEUS and EOB-MRI LI-RADS were substantial. CEUS and EOB-MRI LR-5 have equally good positive predictive value and specificity for HCC ≤ 2cm, and combining these two modalities may better diagnose HCC ≤ 2 cm.

Clinical Trial Registration

https://clinicaltrials.gov/, identifier NCT04212286.

Differences between CEUS LI-RADS and CECT LI-RADS in the diagnosis of focal liver lesions in patients at risk for HCC

OBJECTIVES

To compare the inter-modality consistency and diagnostic performances of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) and contrast-enhanced computed tomography (CECT) LI-RADS in patients at risk for hepatocellular carcinoma (HCC), so as to help clinicians to select a more appropriate modality to follow the focal liver lesions (FLLs).

METHODS

This retrospective study included untreated 277 FLLs from 247 patients who underwent both CEUS and CECT within 1 month. The ultrasound contrast medium used was SonoVue. FLL categories were independently assigned by two ultrasound physicians and two radiologists using CEUS LI-RADS v2017 and CECT LI-RADS v2018, respectively. The diagnostic performances of CEUS and CECT LI-RADS were evaluated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value. Cohen's Kappa was employed to evaluate the concordance of the LI-RADS category.

RESULTS

The inter-modality consistency for CEUS and CECT LI-RADS was 0.31 (p < 0.001). HCC was more frequently observed in CECT LR-3 and LR-4 hepatic lesions than in CEUS (7.3% vs. 19.5%, p < 0.001). The specificity and PPV of CEUS and CECT LR-5 for the diagnosis of HCC were 89.5%, 95.0%, and 82.5%, 94.4%, respectively. The sensitivity of CEUS LR-5 + LR-M for the diagnosis of hepatic malignancies was higher than that of CECT (93.7% vs. 82.7%, p < 0.001). The specificity and PPV of CEUS LR-M for the diagnosis of non-HCC malignancies were lower than those of CECT (59.7% vs. 95.5%, p < 0.001; 23.4% vs. 70.3%, p < 0.001).

CONCLUSIONS

The inter-modality consistency between the CEUS and CECT LI-RADS categories is fair. CEUS LI-RADS was more sensitive than CECT LI-RADS in terms of identifying hepatic malignancies, but weaker in terms of separating HCC from non-HCC malignancies.

Development of a deep-learning model for classification of LI-RADS major features by using subtraction images of MRI: a preliminary study

PURPOSE

Liver Imaging Reporting and Data System (LI-RADS) is limited by interreader variability. Thus, our study aimed to develop a deep-learning model for classifying LI-RADS major features using subtraction images using magnetic resonance imaging (MRI).

METHODS

This single-center retrospective study included 222 consecutive patients who underwent resection for hepatocellular carcinoma (HCC) between January, 2015 and December, 2017. Subtraction arterial, portal venous, and transitional phase images of preoperative gadoxetic acid-enhanced MRI were used to train and test the deep-learning models. Initially, a three-dimensional (3D) nnU-Net-based deep-learning model was developed for HCC segmentation. Subsequently, a 3D U-Net-based deep-learning model was developed to assess three LI-RADS major features (nonrim arterial phase hyperenhancement [APHE], nonperipheral washout, and enhancing capsule [EC]), utilizing the results determined by board-certified radiologists as reference standards. The HCC segmentation performance was assessed using the Dice similarity coefficient (DSC), sensitivity, and precision. The sensitivity, specificity, and accuracy of the deep-learning model for classifying LI-RADS major features were calculated.

RESULTS

The average DSC, sensitivity, and precision of our model for HCC segmentation were 0.884, 0.891, and 0.887, respectively, across all the phases. Our model demonstrated a sensitivity, specificity, and accuracy of 96.6% (28/29), 66.7% (4/6), and 91.4% (32/35), respectively, for nonrim APHE; 95.0% (19/20), 50.0% (4/8), and 82.1% (23/28), respectively, for nonperipheral washout; and 86.7% (26/30), 54.2% (13/24), and 72.2% (39/54) for EC, respectively.

CONCLUSION

We developed an end-to-end deep-learning model that classifies the LI-RADS major features using subtraction MRI images. Our model exhibited satisfactory performance in classifying LI-RADS major features.

A Multicenter Assessment of Interreader Reliability of LI-RADS Version 2018 for MRI and CT

Background Various limitations have impacted research evaluating reader agreement for Liver Imaging Reporting and Data System (LI-RADS). Purpose To assess reader agreement of LI-RADS in an international multicenter multireader setting using scrollable images. Materials and Methods This retrospective study used deidentified clinical multiphase CT and MRI and reports with at least one untreated observation from six institutions and three countries; only qualifying examinations were submitted. Examination dates were October 2017 to August 2018 at the coordinating center. One untreated observation per examination was randomly selected using observation identifiers, and its clinically assigned features were extracted from the report. The corresponding LI-RADS version 2018 category was computed as a rescored clinical read. Each examination was randomly assigned to two of 43 research readers who independently scored the observation. Agreement for an ordinal modified four-category LI-RADS scale (LR-1, definitely benign; LR-2, probably benign; LR-3, intermediate probability of malignancy; LR-4, probably hepatocellular carcinoma [HCC]; LR-5, definitely HCC; LR-M, probably malignant but not HCC specific; and LR-TIV, tumor in vein) was computed using intraclass correlation coefficients (ICCs). Agreement was also computed for dichotomized malignancy (LR-4, LR-5, LR-M, and LR-TIV), LR-5, and LR-M. Agreement was compared between research-versus-research reads and research-versus-clinical reads. Results The study population consisted of 484 patients (mean age, 62 years ± 10 [SD]; 156 women; 93 CT examinations, 391 MRI examinations). ICCs for ordinal LI-RADS, dichotomized malignancy, LR-5, and LR-M were 0.68 (95% CI: 0.61, 0.73), 0.63 (95% CI: 0.55, 0.70), 0.58 (95% CI: 0.50, 0.66), and 0.46 (95% CI: 0.31, 0.61) respectively. Research-versus-research reader agreement was higher than research-versus-clinical agreement for modified four-category LI-RADS (ICC, 0.68 vs 0.62, respectively; P = .03) and for dichotomized malignancy (ICC, 0.63 vs 0.53, respectively; P = .005), but not for LR-5 (P = .14) or LR-M (P = .94). Conclusion There was moderate agreement for LI-RADS version 2018 overall. For some comparisons, research-versus-research reader agreement was higher than research-versus-clinical reader agreement, indicating differences between the clinical and research environments that warrant further study. © RSNA, 2023 Supplemental material is available for this article. See also the editorials by Johnson and Galgano and Smith in this issue.

Identification of the origin of tumor in vein: comparison between CEUS LI-RADS v2017 and v2016 for patients at high risk

Objectives

To compare the diagnostic performance of the Contrast-Enhanced Ultrasound (CEUS) Liver Imaging Report and Data System (LI-RADS) v2016 and v2017 in identifying the origin of tumor in vein (TIV).

Methods

From April 2014 to December 2018, focal liver lesions (FLLs) accompanied by TIV formation in patients at high risk for hepatocellular carcinoma (HCC) were enrolled. Histologic evaluation or composite imaging reference standard were served as the reference standard. Each case was categorized according to the CEUS LI-RADS v2016 and v2017, respectively. Diagnostic performance of CEUS LI-RADS v2016 and v2017 in identifying the originated tumor of TIV was validated via sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value.

Results

A total of 273 FLLs with TIV were analyzed finally, including 266 HCCs and 7 non-HCCs. In v2016, when adopting all TIV as LR-5V, the accuracy and PPV in identifying the originated tumor were both 97.4%. In v2017, when assigning TIV according to contiguous FLLs CEUS LI-RADS category, the accuracy and PPV were 61.9% and 99.4% in subclass of LR-5 as the diagnostic criteria of HCC, and 64.1% and 99.4% in subclass of LR-4/5 as the criteria of HCC diagnosis. There were significant differences in diagnostic accuracy between CEUS LI-RADS v2016 and v2017 in identifying the originated tumor of TIV (p < 0.001).

Conclusions

CEUS LI-RADS v2016 could be better than v2017 in identifying the originated tumor of TIV.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-022-00912-4.

A comparative study of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging and contrast-enhanced ultrasound in the detection of intrahepatic lesion

We evaluated the diagnostic performance of both gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging (Gd-EOB-DTPA-MRI) and contrast-enhanced ultrasound (CEUS) for focal liver lesions, especially for the detection of small (<2 cm) intrahepatic lesions. We retrospectively reviewed patients who underwent Gd-EOB-DTPA-MRI and CEUS before liver resection and compared Gd-EOB-DTPA-MRI and CEUS in the detection of focal liver lesions. A total of 216 patients were included, and 309 lesions were found. The sensitivity values of MRI and CEUS for the main lesion were both more than 95%, and the coincidence rates were both more than 80%. Regarding lesions <2 cm, 135 such lesions were detected by MRI, whereas only 85 were detected by CEUS. For lesions <2 cm, the sensitivity, specificity, and coincidence rates of MRI were significantly better than those of CEUS. Among 27 patients, 50 more lesions were detected by MRI than CEUS, 56% (28/50) of which were malignant. For the large lesion, the diagnostic performance is similar between Gd-EOB-DTPA-MRI and CEUS, and the sensitivity and coincidence rates of both methods are high. Gd-EOB-DTPA-MRI is likely to detect small (<2 cm) focal intrahepatic lesions.

Interrater reliability and agreement of the liver imaging reporting and data system (LI-RADS) v2018 for the evaluation of hepatic lesions

Purpose

The liver imaging reporting and data system (LI-RADS) is a structured reporting system that categorizes hepatic observations according to major imaging features and lesion size, with an optional ancillary features contribution. This study aimed to evaluate inter-reader agreement of dynamic magnetic resonance imaging (MRI) using LI-RADS v2018 lexicon.

Material and methods

Forty-nine patients with 69 hepatic observations were included in our study. The major and ancillary features of each hepatic observation were evaluated by 2 radiologists using LI-RADS v2018, and the interreader agreement was allocated.

Results

The inter-reader agreement of major LI-RADS features was substantial; κ of non-rim arterial hyperenhancement, non-peripheral washout appearance, and enhancing capsule was 0.796, 0.799, and 0.772 (p < 0.001), respectively. The agreement of the final LI-RADS category was substantial with κ = 0.651 (p < 0.001), and weighted κ = 0.786 (p < 0.001). The inter-reader agreement of the ancillary features was substantial to almost perfect (k range from 0.718 to 1; p < 0.001). An almost perfect correlation was noted for the hepatic lesion size measurement with ICC = 0.977 (p < 0.001).

Conclusions

The major and ancillary features of the LI-RADS v2018, as well as the final category and lesions size, have substantial to almost perfect inter-reader agreement.

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

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

Deep learning radiomics for focal liver lesions diagnosis on long-range contrast-enhanced ultrasound and clinical factors

BACKGROUND

Routine clinical factors play an important role in the clinical diagnosis of focal liver lesions (FLLs); however, they are rarely used in computer-assisted diagnosis. Therefore, we developed a deep learning (DL) radiomics model, and investigated its effectiveness in diagnosing FLLs using long-range contrast-enhanced ultrasound (CEUS) cines and clinical factors.

METHODS

Herein, 303 patients with pathologically confirmed FLLs after surgery at three hospitals were retrospectively enrolled and divided into a training cohort (n=203), internal validation (IV) cohort (n=50) from one hospital with the ratio of 4:1, and external validation (EV) cohort (n=50) from the other two hospitals. Four DL radiomics models, namely Four Stream 3D convolutional neural network (FS3DU) (trained with CEUS cines only), FS3DU+A (trained with CEUS cines and alpha fetoprotein), FS3DU+H (trained with CEUS cines and hepatitis), and FS3DU+A+H (trained with CEUS cines, alpha fetoprotein, and hepatitis), were formed based on 3D convolutional neural networks (CNNs). They used approximately 20-s preoperative CEUS cines and/or clinical factors to extract spatiotemporal features for the classification of FLLs and the location of the region of interest. The area under curve of the receiver operating characteristic and diagnosis speed were calculated to evaluate the models in the IV and EV cohorts, and they were compared with those of two radiologists. Two-sided Delong tests were used to calculate the statistical differences between the models and radiologists.

RESULTS

FS3DU+A+H, which incorporated CEUS cines, hepatitis, and alpha fetoprotein, achieved the highest area under curve of 0.969 (95% CI: 0.901-1.000) and 0.957 (95% CI: 0.894-1.000) among radiologists and other models in IV and EV cohorts, respectively. A significant difference was observed when comparing FS3DU and radiologist 2 (all P<0.05). The diagnosis speed of all the models was the same (10.76 s per patient), and it was two times faster than those of the radiologists (radiologist 1: 23.74 and 27.75 s; radiologist 2: 25.95 and 29.50 s in IV and EV cohorts, respectively).

CONCLUSIONS

The proposed DL radiomics demonstrated excellent performance on the benign and malignant diagnosis of FLLs by combining CEUS cines and clinical factors. It could help the individualized characterization of FLLs, and enhance the accuracy of diagnosis in the future.

Diagnostic accuracy and inter-reader reliability of the MRI Liver Imaging Reporting and Data System (version 2018) risk stratification and management system

Background

Hepatocellular carcinoma (HCC) can be diagnosed non-invasively, provided certain imaging criteria are met. However, the recent Liver Imaging Reporting and Data System (LI-RADS) version 2018 has not been widely validated.

Objectives

This study aimed to evaluate the diagnostic accuracy and reader reliability of the LI-RADS version 2018 lexicon amongst fellowship trained radiologists compared with an expert consensus reference standard.

Method

This retrospective study was conducted between 2018 and 2020. A total of 50 contrast enhanced liver magnetic resonance imaging (MRI) studies evaluating focal liver observations in patients with cirrhosis, hepatitis B virus (HBV) or prior HCC were acquired. The standard of reference was a consensus review by three fellowship-trained radiologists. Diagnostic accuracy including sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV) and area under the curve (AUC) values were calculated per LI-RADS category for each reader. Kappa statistics were used to measure reader agreement.

Results

Readers demonstrated excellent specificities (88% – 100%) and NPVs (85% – 100%) across all LI-RADS categories. Sensitivities were variable, ranging from 67% to 83% for LI-RADS 1, 29% to 43% for LI-RADS 2, 100% for LI-RADS 3, 70% to 80% for LI-RADS 4 and 80% to 84% for LI-RADS 5. Readers showed excellent accuracy for differentiating benign and malignant liver lesions with AUC values > 0.90. Overall inter-reader agreement was ‘good’ (kappa = 0.76, p < 0.001). Pairwise inter-reader agreement was ‘very good’ (kappa ≥ 0.90, p < 0.001).

Conclusion

The LI-RADS version 2018 demonstrates excellent specificity, NPV and AUC values for risk stratification of liver observations by radiologists. Liver Imaging Reporting and Data System can reliably differentiate benign from malignant lesions when used in conjunction with corresponding LI-RADS management recommendations.

Risk Stratification and Distribution of Hepatocellular Carcinomas in CEUS and CT/MRI LI-RADS: A Meta-Analysis

Background

CEUS LI-RADS and CT/MRI LI-RADS have been used in clinical practice for several years. However, there is a lack of evidence-based study to compare the proportion of hepatocellular carcinomas (HCCs) in each category and the distribution of HCCs of these two categorization systems.

Purpose

The purpose of this study was to compare the proportion of HCCs between corresponding CEUS LI-RADS and CT/MRI LI-RADS categories and the distribution of HCCs and non-HCC malignancies in each category.

Methods

We searched PubMed, Embase, and Cochrane Central databases from January 2014 to December 2021. The proportion of HCCs and non-HCC malignancies and the corresponding sensitivity, specificity, accuracy, diagnostic odds ratio (DOR), and area under the curve (AUC) of the LR-5 and LR-M categories were determined using a random-effect model.

Results

A total of 43 studies were included. The proportion of HCCs in CEUS LR-5 was 96%, and that in CECT/MRI LR-5 was 95% (p > 0.05). The proportion of non-HCC malignancy in CEUS LR-M was lower than that of CT/MRI LR-M (35% vs. 58%, p = 0.01). The sensitivity, specificity, and accuracy of CEUS LR-5 for HCCs were 73%, 92%, and 78%, respectively, and of CT/MRI LR-5 for HCCs, 69%, 92%, and 76%, respectively.

Conclusion

With the upshift of the LI-RADS category, the proportion of HCCs increased. CEUS LR-3 has a lower risk of HCCs than CT/MRI LR-3. CEUS LR-5 and CT/MRI LR-5 have a similar diagnostic performance for HCCs. CEUS LR-M has a higher proportion of HCCs and a lower proportion of non-HCC malignancies compared with CT/MRI LR-M.

An assessment of liver lesions using a combination of CEUS LI-RADS and AFP

PURPOSE

To improve noninvasive diagnosis of HCC using a combination of CE US LI-RADS and alpha-fetoprotein (AFP).

METHODS

757 solitary liver nodules from 757 patients at risk of HCC with CE US and serum AFP test were categorized as LR-1 to LR-5 through LR-M according to CE US LI-RADS version 2017. In LR-3, LR-4, and LR-M nodules, those with AFP > 200 ng/ml were reclassified as mLR-5. Nodules with LR-5 and mLR-5 were reclassified as definitely HCC to modify CE US LI-RADS. Diagnostic performance was assessed with specificity, sensitivity, and PPV.

RESULTS

The sensitivity, specificity, and PPV of LR-5 as a predictor of HCC were 64.7%, 97.8%, and 98.9%, respectively. 32.1% patients with solitary liver nodule had AFP greater than 200 ng/ml, of which 98.8% were HCC (25.8%, 7.5%, 2.5% assigned to LR-M, LR-4, LR-3, respectively) and 1.2% were Combined Hepatocellular Cholangiocarcinoma. After modification, the sensitivity increased to 79.6% (P < 0.001), while specificity and PPV remained high (96.6% and 98.7%, P > 0.050).

CONCLUSION

The combination of CE US LI-RADS and AFP for diagnosing HCC improved diagnostic sensitivity significantly, while maintaining high PPV and specificity in patients with the solitary liver nodule.

Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System in Diagnosing Hepatocellular Carcinoma: Diagnostic Performance and Interobserver Agreement

OBJECTIVES

 To determine the diagnostic performance and inter-reader agreement of the contrast-enhanced ultrasound liver imaging reporting and data system (CEUS-LI-RADS) for diagnosing hepatocellular carcinoma (HCC) in high-risk patients.

METHODS

 In this prospective study, CEUS-LI-RADS categories (LR-5 for predicting HCC) were assigned by six blinded readers and compared to the definitive HCC diagnosis in patients with liver cirrhosis per the 2017 China Liver Cancer Guidelines (CLCG). CEUS features were recorded in 96 patients with 96 histology-proven lesions. The diagnostic performance of LR-5 was described by the sensitivity, specificity and accuracy. Multi-reader agreement was assessed by using intraclass correlation coefficients (ICC).

RESULTS

 In cirrhotic patients, the specificity of LR-5 (range: 92.7-100.0 %) was statistically higher than that of CLCG for each reader (range: 28.6-64.3 %). However, the sensitivity (range: 38.6-63.6 %) and accuracy (range: 53.4-70.7 %) were statistically lower in CEUS-LIRADS than in CLCG (sensitivity range: 88.6-100.0 %; accuracy range: 77.6-86.2 %). Only fair to moderate inter-reader agreement was achieved for the CEUS-LI-RADS category (ICC = 0.595) and washout appearance (ICC range: 0.338 to 0.555). Neither nodule-in-nodule nor mosaic architecture was observed more often in HCC (all P > 0.05), with poor inter-reader consistency for both (both ICC < 0.20).

CONCLUSION

 CEUS-LI-RADS category 5 has a high specificity but a low accuracy for identifying HCC in high-risk patients. Inter-reader agreement is not satisfactory concerning CEUS-LIRADS category and washout appearance. Moreover, the clinical value of ancillary features favoring HCC is quite limited.

Contrast-Enhanced Ultrasound Patterns for the Non-invasive Diagnosis of Hepatocellular Carcinoma: A Prospective Multicenter Study in Histologically Proven Liver Lesions in a Real-Life Setting Demonstrating the Benefit of Extended Late Phase Observation

The hallmark for the non-invasive diagnosis of hepatocellular carcinoma (HCC) with contrast-enhanced ultrasound (CEUS) in cirrhosis is arterial phase hyperenhancement (APHE), followed by late-onset (>60 s), mild washout. Large retrospective studies report this pattern of washout to occur in the vast majority of HCCs. However, a prospective multicenter validation of these findings is still missing. Thus, we initiated a prospective multicenter validation study assessing CEUS enhancement patterns in focal liver lesions of patients at risk for HCC. We analyzed lesions that were eventually histology proven in a real-life setting. CEUS patterns were assessed for subgroups of HCC, intrahepatic cholangiocellular carcinoma (iCCA) and non-HCC, non-iCCA lesions. The diagnosis was HCC in 316 lesions (median size: 40 mm), iCCA in 26 lesions (median size: 47.5 mm) and non-HCC, non-iCCA in 53 lesions (median size: 27 mm). Overall, 85.8% of HCCs exhibited APHE. APHE followed by washout occurred in 72.8% of HCCs and 50% of iCCAs and non-HCC, non-iCCA malignancies (p < 0.05). Early and marked washout was associated more commonly with iCCA; HCCs exhibited mostly late and mild washout (onset >4-6 min in 10% of cases). Our prospective data confirm that the typical pattern of APHE followed by late-onset, mild washout occurs in the majority of HCCs.

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.

Deep learning applied to the imaging diagnosis of hepatocellular carcinoma

Each year, hepatocellular carcinoma is diagnosed in more than half a million people worldwide. It is the fifth most common cancer in men and the seventh most common cancer in women. Its diagnosis is currently made using imaging techniques, such as computed tomography and magnetic resonance imaging. For most cirrhotic patients, these methods are enough for diagnosis, foregoing the necessity of a liver biopsy. In order to improve outcomes and bypass obstacles, many companies and clinical centers have been trying to develop deep learning systems that could be able to diagnose and classify liver nodules in the cirrhotic liver, in which the neural networks are one of the most efficient approaches to accurately diagnose liver nodules. Despite the advances in deep learning systems for the diagnosis of imaging techniques, there are many issues that need better development in order to make such technologies more useful in daily practice.

A Semi-Automatic Step-by-Step Expert-Guided LI-RADS Grading System Based on Gadoxetic Acid-Enhanced MRI

PURPOSE

Liver imaging reporting and data system (LI-RADS) classification, especially the identification of LR-3 to 5 lesions with hepatocellular carcinoma (HCC) probability, is of great significance to treatment strategy determination. We aimed to develop a semi-automatic LI-RADS grading system on multiphase gadoxetic acid-enhanced MRI using deep convolutional neural networks (CNN).

PATIENTS AND METHODS

An internal data set of 439 patients and external data set of 71 patients with suspected HCC were included and underwent gadoxetic acid-enhanced MRI. The expert-guided LI-RADS grading system consisted of four deep 3D CNN models including a tumor segmentation model for automatic diameter estimation and three classification models of LI-RADS major features including arterial phase hyper-enhancement (APHE), washout and enhancing capsule. An end-to-end learning system comprising single deep CNN model that directly classified the LI-RADS grade was developed for comparison.

RESULTS

On internal testing set, the segmentation model reached a mean dice of 0.84, with the accuracy of mapped diameter intervals as 82.7% (95% CI: 74.4%, 91.7%). The area under the curves (AUCs) were 0.941 (95% CI: 0.914, 0.961), 0.859 (95% CI: 0.823, 0.890) and 0.712 (95% CI: 0.668, 0.754) for APHE, washout and capsule, respectively. The expert-guided system significantly outperformed the end-to-end system with a LI-RADS grading accuracy of 68.3% (95% CI: 60.8%, 76.5%) vs 55.6% (95% CI: 48.8%, 63.0%) (P<0.0001). On external testing set, the accuracy of mapped diameter intervals was 91.5% (95% CI: 81.9%, 100.0%). The AUCs were 0.792 (95% CI: 0.745, 0.833), 0.654 (95% CI: 0.602, 0.703) and 0.658 (95% CI: 0.606, 0.707) for APHE, washout and capsule, respectively. The expert-guided system achieved an overall grading accuracy of 66.2% (95% CI: 58.0%, 75.2%), significantly higher than the end-to-end system of 50.1% (95% CI: 43.1%, 58.1%) (P<0.0001).

CONCLUSION

We developed a semi-automatic step-by-step expert-guided LI-RADS grading system (LR-3 to 5), superior to the conventional end-to-end learning system. This deep learning-based system may improve workflow efficiency for HCC diagnosis in clinical practice.

Does Training in LI-RADS Version 2018 Improve Readers' Agreement with the Expert Consensus and Inter-reader Agreement in MRI Interpretation?

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS) was established for noninvasive diagnosis for hepatocellular carcinoma (HCC). However, whether training can improve readers' agreement with the expert consensus and inter-reader agreement for final categories is still unclear.

PURPOSE

To explore training effectiveness on readers' agreement with the expert consensus and inter-reader agreement.

STUDY TYPE

Prospective.

SUBJECTS

Seventy lesions in 61 patients at risk of HCC undergoing liver MRI; 20 visiting scholars.

FIELD STRENGTH/SEQUENCE

1.5 T or 3 T, Dual-echo T₁ WI, Fast spin-echo T₂ WI, SE-EPI DWI, and Dynamic multiphase fast gradient-echo T₁ WI.

ASSESSMENT

Seventy lesions assigned LI-RADS categories of LR1-LR5, LR-M, and LR-TIV by three radiologists in consensus were randomly selected, with 10 cases for each category. The consensus opinion was the standard reference. The third radiologist delivered the training. Twenty readers reviewed images independently and assigned each an LI-RADS category both before and after the training.

STATISTICAL TESTS

Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, receiver operating characteristic (ROC) analysis, simple and weighted kappa statistics, and Fleiss kappa statistics.

RESULTS

Before and after training: readers' AUC (areas under ROC) for LR-1-LR-5, LR-M, and LR-TIV were 0.898 vs. 0.913, 0.711 vs. 0.876, 0.747 vs. 0.860, 0.724 vs. 0.815, 0.844 vs. 0.895, 0.688 vs. 0.873, and 0.720 vs. 0.948, respectively, and all improved significantly (P < 0.05), except LR-1(P = 0.25). Inter-reader agreement between readers for LR-1-LR-5, LR-M, LR-TIV were 0.725 vs. 0.751, 0.325 vs. 0.607, 0.330 vs. 0.559, 0.284 vs. 0.488, 0.447 vs. 0.648, 0.229 vs. 0.589, and 0.362 vs. 0.852, respectively, and all increased significantly (P < 0.05). For training effectiveness on both AUC and inter-reader agreement, LR-TIV, LR-M, and LR-2 improved most, and LR-1 made the least.

DATA CONCLUSION

This study shows LI-RADS training could improve reader agreement with the expert consensus and inter-reader agreement for final categories.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

MR versus CEUS LI-RADS for Distinguishing Hepatocellular Carcinoma from other Hepatic Malignancies in High-Risk Patients

Distinguishing between other hepatic malignancies (OMs) and hepatocellular carcinoma (HCC) is vital to allow clinicians to determine optimal treatment and assess prognosis in patients at high risk for HCC. This study evaluated the performance of the Liver Imaging Reporting and Data System (LI-RADS) using magnetic resonance imaging (MRI) versus contrast-enhanced ultrasonography (CEUS) for differentiating HCC from OMs in patients at high risk for HCC. This retrospective study consecutively enrolled 106 high-risk patients with HCC and 52 high-risk patients with OMs. Patients underwent both MRI and CEUS, with histologic diagnosis as a reference standard. The diagnostic performance of MR versus CEUS LI-RADS was calculated and compared. The performance of the modified CEUS LI-RADS criteria was also evaluated and compared. Our research found that MRI features significantly differed between patients with OMs and those with HCC (p < 0.05), with sensitivities of 34.6%-69.2% and specificities of 83.0%-95.3% for diagnosing OMs and an LI-RADS M (LR-M): definite or probable malignancy, not specific for hepatocellular carcinoma sensitivity of 90.4% and specificity of 83.0% for diagnosing OM. CEUS features also significantly differed between patients with OM and HCC (p < 0.05), with sensitivities of 11.5%-96.2% and specificities of 23.6%-100% for diagnosing OMs, and an LR-M sensitivity of 98.1% and specificity of 84.0% for diagnosing OMs. Accuracies of category LR-M did not significantly differ between MR and CEUS LI-RADS (85.4% vs. 88.6%, p = 0.724). After reclassification of category LR-M nodules to category LR-5 if they exhibited clear intratumoral non-enhanced area boundaries and no punched-out appearance before 5 min, accuracy increased from 88.6% to 96.8% for CEUS LR-M and from 84.8% to 91.1% for CEUS LR-5. LR-M accuracies were significantly higher for the modified version of the CEUS LI-RADS than for MR LI-RADS (96.8% vs. 85.4%, respectively, p = 0.04). CEUS LI-RADS and MR LI-RADS can effectively be used to distinguish HCC from OMs. In patients at high risk of HCC, performance may be further improved by using a modified CEUS LI-RADS classification system in which category LR-M lesions are considered LR-5 if they have clear intratumoral non-enhanced area boundaries and do not have a punched-out appearance.

Real-life assessment of standardized contrast-enhanced ultrasound (CEUS) and CEUS algorithms (CEUS LI-RADS®/ESCULAP) in hepatic nodules in cirrhotic patients-a prospective multicenter study

Objectives

Hepatocellular carcinoma (HCC) can be diagnosed non-invasively with contrast-enhanced ultrasound (CEUS) in cirrhosis if the characteristic pattern of arterial phase hyperenhancement followed by hypoenhancement is present. Recent studies suggest that diagnosis based on this “hyper-hypo” pattern needs further refinement. This study compares the diagnostic accuracies of standardized CEUS for HCC according to the current guideline definition and following the newly developed CEUS algorithms (CEUS LI-RADS®, ESCULAP) in a prospective multicenter real-life setting.

Methods

Cirrhotic patients with liver lesions on B-mode ultrasound were recruited prospectively from 04/2018 to 04/2019, and clinical and imaging data were collected. The CEUS standard included an additional examination point after 4–6 min in case of no washout after 3 min. The diagnostic accuracies of CEUS following the guidelines (“hyper-hypo” pattern), based on the examiner’s subjective interpretation (“CEUS subjective”), and based on the CEUS algorithms ESCULAP and CEUS LI-RADS® were compared.

Results

In total, 470 cirrhotic patients were recruited in 43 centers. The final diagnosis was HCC in 378 cases (80.4%) according to the reference standard (histology 77.4%, MRI 16.4%, CT 6.2%). The “hyper-hypo” pattern yielded 74.3% sensitivity and 63% specificity. “CEUS subjective” showed a higher diagnostic accuracy (sensitivity, 91.5%; specificity, 67.4%; positive predictive value, 92%; negative predictive value, 66%). Sensitivity was higher for ESCULAP (95%) and “CEUS subjective” (91.5%) versus CEUS LI-RADS® (65.2%; p < 0.001). Specificity was highest for CEUS LI-RADS® (78.6%; p < 0.001).

Conclusions

CEUS has an excellent diagnostic accuracy for the non-invasive diagnosis of HCC in cirrhosis. CEUS algorithms may be a helpful refinement of the “hyper-hypo” pattern defined by current HCC guidelines.

Key Points

• Contrast-enhanced ultrasound (CEUS) has a high diagnostic accuracy for the non-invasive diagnosis of hepatocellular carcinoma (HCC) in cirrhosis.

• The CEUS algorithm ESCULAP (Erlanger Synopsis for Contrast-enhanced Ultrasound for Liver lesion Assessment in Patients at risk) showed the highest sensitivity, whereas the CEUS LI-RADS® (Contrast-Enhanced UltraSound Liver Imaging Reporting and Data System) algorithm yielded the highest specificity.

• A standardized CEUS examination procedure with an additional examination point in the late phase, after 4–6 min in lesions with no washout after 3 min, is vital.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-07872-3.

Diagnosis of Non-Hepatocellular Carcinoma Malignancies in Patients With Risks for Hepatocellular Carcinoma: CEUS LI-RADS Versus CT/MRI LI-RADS

Objective

Data regarding direct comparison of contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) and Computed Tomography/Magnetic Resonance Imaging (CT/MR) LI-RADS in diagnosis of non-hepatocelluar carcinoma (non-HCC) malignancies remain limited. Our study aimed to compare the diagnostic performance of the CEUS LI-RADS version 2017 and CT/MRI LI-RADS v2018 for diagnosing non-HCC malignancies in patients with risks for HCC.

Materials and Methods

In this retrospective study, 94 liver nodules pathologically-confirmed as non-HCC malignancies in 92 patients at risks for HCC from January 2009 to December 2018 were enrolled. The imaging features and the LI-RADS categories on corresponding CEUS and CT/MRI within 1 month were retrospectively analyzed according to the ACR CEUS LI-RADS v2017 and ACR CT/MRI LI-RADS v2018 by two radiologists in consensus for each algorithm. The sensitivity of LR-M category, inter-reader agreement and inter-modality agreement was compared between these two standardized algorithms.

Results

Ninety-four nodules in 92 patients (mean age, 54 years ± 10 [standard deviation] with 65 men [54 years ± 11] and 27 women [54 years ± 8]), including 56 intrahepatic cholangiocarcinomas, 34 combined hepatocellular cholangiocarcinomas, two adenosquamous carcinomas of the liver, one primary hepatic neuroendocrine carcinoma and one hepatic undifferentiated sarcoma were included. On CEUS, numbers of lesions classified as LR-3, LR-4, LR-5 and LR-M were 0, 1, 10 and 83, and on CT/MRI, the corresponding numbers were 3, 0, 14 and 77. There was no significant difference in the sensitivity of LR-M between these two standardized algorithms (88.3% of CEUS vs 81.9% of CT/MRI, p = 0.210). Seventy-seven lesions (81.9%) were classified as the same LI-RADS categories by both standardized algorithms (five for LR-5 and 72 for LR-M, kappa value = 0.307). In the subgroup analysis for ICC and CHC, no significant differences were found in the sensitivity of LR-M category between these two standardized algorithms (for ICC, 94.6% of CEUS vs 89.3% of CT/MRI, p = 0.375; for CHC, 76.5% of CEUS vs 70.6% of CT/MRI, p = 0. 649).

Conclusion

CEUS LI-RADS v2017 and CT/MRI LI-RADS v2018 showed similar value for diagnosing non-HCC primary hepatic malignancies in patients with risks.

Contrast-Enhanced Ultrasound Algorithms (CEUS-LIRADS/ESCULAP) for the Noninvasive Diagnosis of Hepatocellular Carcinoma - A Prospective Multicenter DEGUM Study

BACKGROUND

 This prospective multicenter study funded by the DEGUM assesses the diagnostic accuracy of standardized contrast-enhanced ultrasound (CEUS) for the noninvasive diagnosis of hepatocellular carcinoma (HCC) in high-risk patients.

METHODS

 Patients at high risk for HCC with a histologically proven focal liver lesion on B-mode ultrasound were recruited prospectively in a multicenter approach. Clinical and imaging data were entered via online entry forms. The diagnostic accuracies for the noninvasive diagnosis of HCC were compared for the conventional interpretation of standardized CEUS at the time of the examination (= CEUS on-site) and the two CEUS algorithms ESCULAP (Erlanger Synopsis for Contrast-enhanced Ultrasound for Liver lesion Assessment in Patients at risk) and CEUS LI-RADS (Contrast-Enhanced UltraSound Liver Imaging Reporting and Data System).

RESULTS

 321 patients were recruited in 43 centers; 299 (93.1 %) had liver cirrhosis. The diagnosis according to histology was HCC in 256 cases, and intrahepatic cholangiocarcinoma (iCCA) in 23 cases. In the subgroup of cirrhotic patients (n = 299), the highest sensitivity for the diagnosis of HCC was achieved with the CEUS algorithm ESCULAP (94.2 %) and CEUS on-site (90.9 %). The lowest sensitivity was reached with the CEUS LI-RADS algorithm (64 %; p < 0.001). However, the specificity of CEUS LI-RADS (78.9 %) was superior to that of ESCULAP (50.9 %) and CEUS on-site (64.9 %; p < 0.001). At the same time, the negative predictive value (NPV) of CEUS LI-RADS was significantly inferior to that of ESCULAP (34.1 % vs. 67.4 %; p < 0.001) and CEUS on-site (62.7 %; p < 0.001). The positive predictive values of all modalities were high (around 90 %), with the best results seen for CEUS LI-RADS and CEUS on-site.

CONCLUSION

 This is the first multicenter, prospective comparison of standardized CEUS and the recently developed CEUS-based algorithms in histologically proven liver lesions in cirrhotic patients. Our results reaffirm the excellent diagnostic accuracy of CEUS for the noninvasive diagnosis of HCC in high-risk patients. However, on-site diagnosis by an experienced examiner achieves an almost equal diagnostic accuracy compared to CEUS-based diagnostic algorithms.

The diagnostic performance of gadoxetic acid disodium-enhanced magnetic resonance imaging and contrast-enhanced ultrasound in detecting hepatocellular carcinoma: A meta-analysis

The purpose of this study was to identify and compare the diagnostic performance of gadolinium-ethoxybenzyl-diethyltriethylenetriacetic acid (Gd-EOB-DTPA) enhanced magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS) in hepatocellular carcinoma (HCC).Two researchers searched PubMed, EMBASE, and Cochrane Library databases from the inception of each database to 10 February 2020, to find comparative studies of Gd-EOB-DTPA-MRI and CEUS in detection of HCC.The study included eight studies (374 patients). MRI is superior to CEUS in diagnostic sensitivity of HCC, P = .03. The diagnostic sensitivity of MRI in lesions with a diameter of less than 30 mm was significantly higher than that of CEUS, P = .04. MRI and CEUS had no significant difference in diagnostic specificity of HCC, P = .95. Summary Receiver Operating Characteristics (SROC) of MRI showed a larger than that of CEUS, but with P > .05.Gd-EOB-DTPA-MRI showed higher sensitivity than CEUS for hepatocellular carcinoma lesions, especially for lesions of less than 30 mm across.

Sonazoid-enhanced ultrasonography: comparison with CT/MRI Liver Imaging Reporting and Data System in patients with suspected hepatocellular carcinoma

Purpose

The aim of this study was to evaluate the association of contrast-enhanced ultrasound (CEUS) features using Sonazoid for liver nodules with Liver Imaging Reporting and Data System (LI-RADS) categories and to identify the usefulness of Kupffer-phase images.

Methods

This retrospective study was conducted in 203 patients at high risk of hepatocellular carcinoma (HCC) who underwent CEUS with Sonazoid from 2013 to 2016. Nodule enhancement in the arterial, portal venous, late, and Kupffer phases; CEUS LI-RADS major features; and Kupffer-phase defects were evaluated. According to the computed tomography/magnetic resonance imaging (CT/MRI) LI-RADS v2018, all nodules were assigned an LR category (n=4/33/99/67 for LR-M/3/4/5) and comparisons across LR categories were made. We defined modified CEUS LI-RADS as using Kupffer-phase defects as an alternative to late and mild washout in CEUS LI-RADS and compared the diagnostic performance for HCC.

Results

On CEUS of 203 nodules, 89.6% of CT/MRI LR-5 and 85.9% of LR-4 nodules showed hyperenhancement in the arterial phase, while 57.6% of LR-3 nodules showed hyperenhancement. Among the CT/MRI LR-5 nodules that showed arterial phase hyperenhancement or isoenhancement, 59.7% showed hypoenhancing changes from the portal venous phase, 23.9% from the late phase, and 13.4% additionally in the Kupffer phase. The modified CEUS LI-RADS showed higher sensitivity than CEUS LI-RADS (83.2% vs. 74.2%, P=0.008) without compromising specificity (63.6% vs. 69.7%, P=0.500).

Conclusion

The Kupffer phase best shows hypoenhancing changes in LR-5 lesions and is expected to improve the sensitivity for HCC in high-risk patients.

LI-RADS and transplantation: challenges and controversies

Patients with early stage hepatocellular carcinoma (HCC) can be cured by liver transplantation. HCC imaging features on CT or MRI are specific enough to allow for definitive diagnosis and treatment without the need of confirmatory biopsy. When applied to the appropriate at-risk population the Liver Imaging Reporting and Data System (LI-RADS) imaging criteria achieve high specificity and positive predictive value for the diagnosis of HCC. The Organ Procurement and Transplantation Network (OPTN) is the United States organization that aims to assure the adequate and fair distribution of livers across candidates. Given the importance of fair organ allocation, OPTN also provides stringent imaging criteria for the diagnosis of HCC aiming to avoid false positive diagnosis. Although most imaging criteria are identical for both systems, discrepancies between LI-RADS and the current OPTN classification system for HCC diagnosis exists. Main differences include, but are not limited to, the binary approach of OPTN to classify lesions as HCC or not, versus the probabilistic algorithmic approach of LI-RADS, technical and interpretation considerations, and the approach towards treated lesions. The purpose of this article is to highlight the similarities and discrepancies between LI-RADS and the current OPTN criteria for HCC diagnosis and the implications that these differences may have on the management of patients who are transplant candidates.

Diagnostic Accuracy of Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS) for Differentiating Between Hepatocellular Carcinoma and Other Hepatic Malignancies in High-Risk Patients: A Meta-Analysis

OBJECTIVES

 The American College of Radiology (ACR) contrast-enhanced ultrasound liver imaging reporting and data system (CEUS LI-RADS), which includes diagnostic criteria for hepatocellular carcinoma (HCC) and other hepatic malignancies (OM), is increasingly used in clinical practice. This study performed a meta-analysis to assess the diagnostic accuracy of CEUS LI-RADS for differentiating between HCC and OM in high-risk patients.

METHODS

 PubMed, Embase (Ovid), and Cochrane (CENTRAL) were searched for relevant studies. All studies that reported the percentage of HCC and OM in the LI-RADS categories were included. Random-effects models were used to calculate the pooled sensitivity and specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curve.

RESULTS

 Eight studies involving 4215 focal liver lesions were included in the final analysis. The pooled sensitivity and specificity of the LR-5 criteria for HCC were 0.71 (95 % CI, 0.69-0.72) and 0.88 (0.85-0.91), respectively, the DOR was 18.36 (7.41-45.52), and the area under the SROC curve (AUC) was 0.8128. The pooled sensitivity and specificity of the LR-M criteria for OMs were 0.85 (0.81-0.88) and 0.86 (0.85-0.87), the DOR was 27.82 (11.83-65.40), respectively, and the SROC AUC was 0.9098.

CONCLUSION

 The CEUS LI-RADS can effectively distinguish HCC from other hepatic malignancy in high-risk patients based on LR-5 criteria and LR-M criteria. However, further studies are needed for validation due to the limited number of included studies and the potential heterogeneity among the included studies.

Diagnostic efficacy of contrast-enhanced ultrasound versus MRI Liver Imaging Reporting and Data System (LI-RADS) for categorising hepatic observations in patients at risk of hepatocellular carcinoma

AIM

To investigate the diagnostic efficacy of the contrast-enhanced ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS) for categorising hepatic observations in patients at risk of hepatocellular carcinoma (HCC) compared with magnetic resonance imaging (MRI) LI-RADS.

MATERIALS AND METHODS

CEUS and MRI data were analysed retrospectively according to the LI-RADS scheme. Follow-up results and pathological findings served as the reference standard. Receiver operating characteristic (ROC) curve analysis was used to reveal the area under the curve (AUC). The sensitivity, specificity, accuracy, and positive (PPV) and negative predictive values (NPV) of LR-5 for determining HCC were calculated. The intra-observer agreement of CEUS LI-RADS was also evaluated.

RESULTS

Eighty-four patients with 86 liver observations were enrolled. Forty-two observations were classified as LR-5 by CEUS and MRI, respectively. Based on the reference standard, 53 nodules were HCC. The AUCs were 0.876 for CEUS and 0.873 for MRI, without a significant difference (Z=0.050, p=0.960). The sensitivity, specificity, PPV, NPV, and accuracy of LR-5 was 75.47%, 93.94%, 95.24%, 70.45%, 82.56% with CEUS and 73.58%, 90.9%, 92.86%, 68.18%, 80.23% with MRI, respectively. There was a significant difference in specificity between CEUS and MRI (p=0.006). There was almost perfect agreement for arterial phase hyperenhancement (k=0.870), substantial agreement for washout (k=0.765) and CEUS LI-RADS category (k=0.787).

CONCLUSION

The CEUS LI-RADS scheme is an effective diagnostic tool for HCC with substantial intra-observer reliability. The diagnostic performance of CEUS LI-RADS for determining HCC was comparable to MRI LI-RADS, and the specificity of CEUS LR-5 was significantly higher.

Risk Factors of Ureteral Stenosis After Percutaneous Microwave Ablation of Renal Tumor, a Single-Center Experience

Background

Ureteral stenosis after percutaneous microwave ablation (MWA) of renal tumor is a rare but severe complication, and its risk factors are not apparent.

Purpose

This study aimed to investigate the risk factors for stenosis of ureter after MWA treatment of the renal tumor that is a rare complication.

Materials and Methods

Data of 211 patients who underwent MWA for the treatment of renal tumor were retrospectively analyzed from September 2006 to August 2019. Demographic characteristics, clinical features, ablation parameters, and outcomes were analyzed to find out the potential risk factors of this complication. P < 0.05 is considered significant.

Results

Six of 211 patients developed ureter stenosis, and the rate of this complication is 2.84%. The median time of emergence of hydronephrosis was 226 (range, 3-390) days. Univariate analysis shows the distance between ureter and tumor (P = 0.225) or ablation zone (P = 0.089) is not related to this complication. Postoperative urine routine (red blood cell, P = 0.001; white blood cell, P = 0.035) and R.E.N.A.L. score (P < 0.001) is related to this complication. But after multivariate logistic analysis, only R.E.N.A.L. score (P = 0.004) is associated with this complication. The location and growth pattern of tumor and the energy of ablation were not related to this complication independently.

Conclusion

The stenosis of the ureter after MWA of renal tumor is not associated with the tumor size, location, or the distance between the ureter and tumor and ablation site independently. But R.E.N.A.L. score is associated with ureter stenosis after MWA for the treatment of renal tumor, which combines the information of location, depth, and size of tumor. Preoperative evaluation of the tumor is necessary for avoiding ureter stenosis. Further studies should focus on these risk factors of this complication.

Guidelines and Good Clinical Practice Recommendations for Contrast Enhanced Ultrasound (CEUS) in the Liver - Update 2020 - WFUMB in Cooperation with EFSUMB, AFSUMB, AIUM, and FLAUS

The present, updated document describes the fourth iteration of recommendations for the hepatic use of contrast enhanced ultrasound (CEUS), first initiated in 2004 by the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB). The previous updated editions of the guidelines reflected changes in the available contrast agents and updated the guidelines not only for hepatic but also for non-hepatic applications.The 2012 guideline requires updating as previously the differences of the contrast agents were not precisely described and the differences in contrast phases as well as handling were not clearly indicated. In addition, more evidence has been published for all contrast agents. The update also reflects the most recent developments in contrast agents, including the United States Food and Drug Administration (FDA) approval as well as the extensive Asian experience, to produce a truly international perspective.These guidelines and recommendations provide general advice on the use of ultrasound contrast agents (UCA) and are intended to create standard protocols for the use and administration of UCA in liver applications on an international basis to improve the management of patients.

Guidelines and Good Clinical Practice Recommendations for Contrast-Enhanced Ultrasound (CEUS) in the Liver-Update 2020 WFUMB in Cooperation with EFSUMB, AFSUMB, AIUM, and FLAUS

The present, updated document describes the fourth iteration of recommendations for the hepatic use of contrast-enhanced ultrasound, first initiated in 2004 by the European Federation of Societies for Ultrasound in Medicine and Biology. The previous updated editions of the guidelines reflected changes in the available contrast agents and updated the guidelines not only for hepatic but also for non-hepatic applications. The 2012 guideline requires updating as, previously, the differences in the contrast agents were not precisely described and the differences in contrast phases as well as handling were not clearly indicated. In addition, more evidence has been published for all contrast agents. The update also reflects the most recent developments in contrast agents, including U.S. Food and Drug Administration approval and the extensive Asian experience, to produce a truly international perspective. These guidelines and recommendations provide general advice on the use of ultrasound contrast agents (UCAs) and are intended to create standard protocols for the use and administration of UCAs in liver applications on an international basis to improve the management of patients.

Examining LI-RADS recommendations: should observation size only be measured on non-arterial phases?

OBJECTIVE

To investigate if size measurements of liver observations is more variable in the arterial phase as suggested by LI-RADS and assess potential higher instability in categorization in this particular phase. Secondarily, to assess inter- and intra-reader agreement for size across phases.

MATERIALS AND METHODS

Patients with liver cirrhosis who underwent multi-arterial phase MRI between 2017 and 2018 were retrospectively selected. Three radiologists measured liver observations in each phase, independently, in a random order. Mean size between early and late arterial phases (AP), 2, 3 and 10 min delay and the number of observations crossing the LI-RADS size thresholds (10 and 20 mm) per phase were compared using McNemar's test. Reader agreement was evaluated using intraclass correlation coefficient (ICC) and bootstrap-based comparisons. Bonferroni's correction was applied to pairwise comparisons.

RESULTS

94 observations (LR-3, LR-4, LR-5, and LR-M) were included. Mean sizes (mm) were late AP: 19.9 (95% CI 17.2, 24.2), 2 min delay: 19.8 (95% CI 17.1, 24.0), 3 min delay: 19.8 (95% CI 17.2, 24.0), 10 min delay: 20.2 (95% CI 17.5, 24.5) (p = 0.10-0.88). There was no difference between phases in number of observations that could have changed category due to variability in size (p = 0.546-1.000). Inter- and intra-reader agreement was excellent (ICC = 0.952-0.981).

CONCLUSION

Measurements of focal liver observations were consistent across all post-contrast imaging phases and we found no higher instability in LI-RADS category in any particular phase. Inter- and intra-reader agreement for size was excellent for each phase. Based on these findings, size measurement could be allowed on any post-contrast phase, including the arterial phase, if deemed appropriate by the radiologist.

Contrast-Enhanced Ultrasound for Focal Hepatic Lesions: When to Use and How to Differentiate Lesions?

Contrast-enhanced ultrasound can be used effectively to evaluate focal hepatic lesions and offers unique advantages over computed tomography and magnetic resonance imaging. Serial vascular filling patterns of focal hepatic lesions during arterial, portal, and late phases can provide unique information on lesion characterization and differentiation. Sensitive depiction of arterial hypervascularity and analysis of washout pattern are clues for differentiation of several indeterminate hepatic nodules on conventional ultrasound and computed tomography/magnetic resonance. In this report, we present cases demonstrating clinical applications of contrast-enhanced ultrasound in the diagnosis and management of focal hepatic lesions.

Contrast-enhanced ultrasound LI-RADS 2017: comparison with CT/MRI LI-RADS

OBJECTIVE

To compare the classification based on contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) with that of contrast-enhanced CT and MRI (CECT/MRI) LI-RADS for liver nodules in patients at high risk of hepatocellular carcinoma.

METHODS

Two hundred thirty-nine patients with 273 nodules were enrolled in this retrospective study. Each nodule was categorized according to the CEUS LI-RADS version 2017 and CECT/MRI LI-RADS version 2017. The diagnostic performance of CEUS and CECT/MRI was compared. The reference standard was histopathology diagnosis. Inter-modality agreement was assessed with Cohen's kappa.

RESULTS

The inter-modality agreement for CEUS LI-RADS and CECT/MRI LI-RADS was fair with a kappa value of 0.319 (p < 0.001). The positive predictive values (PPVs) of hepatocellular carcinoma (HCC) in LR-5, LR-4, and LR-3 were 98.3%, 60.0%, and 25.0% in CEUS, and 95.9%, 65.7%, and 48.1% in CECT/MRI, respectively. The sensitivities and specificities of LR-5 for diagnosing HCC were 75.6% and 93.8% in CEUS, and 83.6% and 83.3% in CECT/MRI, respectively. The positive predictive values of non-HCC malignancy in CEUS LR-M and CECT/MRI LR-M were 33.9% and 93.3%, respectively. The sensitivity, specificity, and accuracy for diagnosing non-HCC malignancy were 90.9%, 84.5%, and 85.0% in CEUS LR-M and 63.6%, 99.6%, and 96.7% in CECT/MRI LR-M, respectively.

CONCLUSIONS

The inter-modality agreement of the LI-RADS category between CEUS and CECT/MRI is fair. The positive predictive values of HCCs in LR-5 of the CEUS and CECT/MRI LI-RADS are comparable. CECT/MRI LR-M has better diagnostic performance for non-HCC malignancy than CEUS LR-M.

KEY POINTS

• The inter-modality agreement for the final LI-RADS category between CEUS and CECT/MRI is fair. • The LR-5 of CEUS and CECT/MRI LI-RADS corresponds to comparable positive predictive values (PPVs) of HCC. For LR-3 and LR-4 nodules categorized by CECT/MRI, CEUS examination should be performed, at least if they can be detected on plain ultrasound. • CECT/MRI LR-M has better diagnostic performance for non-HCC malignancy than CEUS LR-M. For LR-M nodules categorized by CEUS, re-evaluation by CECT/MRI is necessary.

Usefulness of the Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System in Diagnosing Focal Liver Lesions by Inexperienced Radiologists

OBJECTIVES

To evaluate the usefulness of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) in diagnosing focal liver lesions (FLLs) by inexperienced radiologists.

METHODS

Images and clinical data from 258 patients at risk for hepatocellular carcinoma who underwent CEUS were collected retrospectively. Two trained inexperienced radiologists and 2 experienced radiologists reviewed all CEUS clips. Each inexperienced radiologist assigned a CEUS LI-RADS category for each observation and labeled it benign or malignant independently. Each experienced radiologist labeled each lesion malignant or benign independently using a conventional diagnostic method. Interobserver agreement of CEUS LI-RADS was analyzed by the κ test. The overall diagnostic accuracy of the LI-RADS category and conventional diagnosis was described by the sensitivity, specificity, positive predictive value, and negative predictive value. All test results were considered significant at P < .05.

RESULTS

A κ value of 0.774 indicated that the CEUS LI-RADS algorithm resulted in substantial consistency between the inexperienced radiologists. For the diagnosis of hepatocellular carcinoma, the sensitivity, specificity, positive predictive value, and negative predictive value were improved significantly in inexperienced radiologists using the CEUS LI-RADS compared to conventional methods. The overall diagnostic accuracy of the experienced radiologists was almost equal to that of CEUS LI-RADS categories assigned by the inexperienced radiologists.

CONCLUSIONS

The CEUS LI-RADS algorithm can not only obtain substantial consistency among inexperienced radiologists but also have excellent diagnostic efficacy in the differentiation of benign from malignant FLLs compared to conventional methods. As a comprehensive algorithm, the CEUS LI-RADS can act as a guide for trainees in learning how to diagnose FLLs.

Contrast-enhanced ultrasound for the characterization of portal vein thrombosis vs tumor-in-vein in HCC patients: a systematic review and meta-analysis

OBJECTIVES

Portal vein thrombosis (PVT) is a common complication of liver cirrhosis. However, differentiation of thrombosis and tumor-in-vein (TIV) may be challenging. Contrast-enhanced ultrasound (CEUS) is an excellent method for detection of vascularization and could help in the distinction. We performed a systematic review and meta-analysis for evaluating the diagnostic value of CEUS in differentiating between PVT and TIV in hepatocellular carcinoma (HCC) patients.

METHODS

PubMed, Embase, Cochrane Library, and Web of Science were searched up to the 5th of May 2019. The study quality was assessed by QUADAS-2 tool. Pooled sensitivity and specificity were calculated by the bivariate random effect model and hierarchical summary receiver-operating characteristic (SROC) curve was plotted.

RESULTS

Seven studies including 425 participants were analyzed after screening 986 articles searched from databases. The pooled sensitivity and specificity of CEUS in diagnosing TIV were 0.94 (95%CI, 0.89-0.97) and 0.99 (95%CI, 0.80-1.00), respectively. The area under the curve (AUC) of SROC curve was 0.97 (95%CI, 0.95-0.98). The pooled sensitivity and AUC were consistent across all the subgroups of different subject numbers, country, study design, CEUS contrast agents, and diagnostic criteria.

CONCLUSIONS

CEUS is highly efficient in differentiating TIV from PVT and is an alternative or a substitute for CT and/or MRI.

TRIAL REGISTRATION

PROSPERO registration number: CRD42019138847 KEY POINTS: • Characterization of portal vein thrombosis (PVT) vs tumor-in-vein (TIV) is critical for HCC staging. • CEUS has an excellent safety profile, provides a real-time analysis without any loss in accuracy compared with CT and MRI. • This meta-analysis demonstrates that contrast-enhanced ultrasound (CEUS) is a suitable method for the detection of PVT and distinction with TIV.

Use of CEUS LI-RADS for the Accurate Diagnosis of Nodules in Patients at Risk for Hepatocellular Carcinoma: A Validation Study

Purpose

To validate the contrast agent-enhanced US Liver Imaging Reporting and Data System (CEUS LI-RADS) algorithm for accurate diagnosis of hepatocellular carcinoma (HCC) and categorization of all nodules encountered in patients at risk for HCC.

Materials and Methods

A single-center retrospective review of 196 nodules in 184 patients at risk for HCC (consisting of 139 HCCs, 18 non-HCC malignancies, and 39 benign nodules) was performed in a three-reader blinded read format, with the use of the CEUS LI-RADS algorithm. Pathologic confirmation was available for 143 nodules (122 HCCs, 18 non-HCC malignancies, and three benign nodules). Nodule sizes ranged between 1.0 and 16.2 cm. Nodules assessed with contrast-enhanced US were assigned various CEUS LI-RADS categories by three blinded readers. CEUS LI-RADS categorization was then compared against histopathologic findings, concurrent CT, and/or MR images or follow-up imaging to assess diagnostic accuracy of CEUS LI-RADS. In addition, the proportion of HCC in all LI-RADS (LR) categories, univariable and multivariable feature analysis, and interrater agreement using Light κ were determined.

Results

The LR-5 category, determined through radiologist categorization of nodules using the CEUS LI-RADS criteria, showed sensitivity, specificity, positive predictive value, and negative predictive value of 86% (119 of 139), 96% (55 of 57), 98% (119 of 121), and 73% (55 of 75), respectively, for the diagnosis of HCC. Two false-positive cases of LR-5 included a cholangiocarcinoma and a combined hepatocellular and cholangiocarcinoma. The remainder of the cholangiocarcinomas in the sample (n = 8) were appropriately categorized as LR-M. Multivariable logistic regression analysis showed that washout of greater than 60 seconds was the contrast-enhanced US feature most predictive of HCC diagnosis, whereas washout of less than 60 seconds was the feature most predictive of nonhepatocellular malignancy. The proportion of HCC nodules categorized in the LR-M and LR-4 categories was 35% and 20%, respectively. Light κ agreement between readers for LI-RADS categorization was 90%.

Conclusion

This study showed excellent specificity for the CEUS LI-RADS LR-5 category, allowing for confident imaging diagnosis of HCC, without necessity for pathologic confirmation. In addition, there was accurate differentiation of HCC from non-HCC malignancies and benign nodules. Only a single cholangiocarcinoma was misdiagnosed as category LR-5, with the remainder of the cholangiocarcinomas in the sample appropriately characterized as category LR-M.Keywords: Abdomen/GI, Evidence Based Medicine, Liver, Neoplasms-Primary, Ultrasound-Contrast© RSNA, 2020.

Interobserver Agreement of Magnetic Resonance Imaging of Liver Imaging Reporting and Data System Version 2018

AIM

This study aimed to assess the interobserver agreement of magnetic resonance (MR) imaging of Liver Imaging Reporting and Data System version 2018 (LI-RADS v2018).

SUBJECTS AND METHODS

Retrospective analysis was done for 119 consecutive patients (77 male and 42 female) at risk of hepatocellular carcinoma who underwent dynamic contrast MR imaging. Image analysis was done by 2 independent and blinded readers for arterial phase hyperenhancement, washout appearance, enhancing capsule appearance, and size. Hepatic lesions were classified into 7 groups according to LI-RADS v2018.

RESULTS

There was excellent interobserver agreement of both reviewers for LR version 4 (κ = 0.887, P = 0.001) with 90.76% agreement. There was excellent interobserver agreement for nonrim arterial phase hyperenhancement (κ = 0.948; 95% confidence interval [CI], 0.89-0.99; P = 0.001), washout appearance (κ = 0.949; 95% CI, 0.89-1.0; P = 0.001); and enhancing capsule (κ = 0.848; 95% CI, 0.73-0.97; P = 0.001) and excellent reliability of size (interclass correlation, 0.99; P = 0.001). There was excellent interobserver agreement for LR-1 (κ = 1.00, P = 0.001), LR-2 (κ = 0.94, P = 0.001), LR-5 (κ = 0.839, P = 0.001), LR-M (κ = 1.00, P = 0.001), and LR-TIV (κ = 1.00; 95% CI, 1.0-1.0; P = 0.001), and good agreement for LR-3 (κ = 0.61, P = 0.001) and LR-4 (κ = 0.61, P = 0.001).

CONCLUSION

MR imaging of LI-RADS v2018 is a reliable imaging modality and reporting system that may be used for standard interpretation of hepatic focal lesions.

Deep convolutional neural network applied to the liver imaging reporting and data system (LI-RADS) version 2014 category classification: a pilot study

PURPOSE

To develop a deep convolutional neural network (CNN) model to categorize multiphase CT and MRI liver observations using the liver imaging reporting and data system (LI-RADS) (version 2014).

METHODS

A pre-existing dataset comprising 314 hepatic observations (163 CT, 151 MRI) with corresponding diameters and LI-RADS categories (LR-1-5) assigned in consensus by two LI-RADS steering committee members was used to develop two CNNs: pre-trained network with an input of triple-phase images (training with transfer learning) and custom-made network with an input of quadruple-phase images (training from scratch). The dataset was randomly split into training, validation, and internal test sets (70:15:15 split). The overall accuracy and area under receiver operating characteristic curve (AUROC) were assessed for categorizing LR-1/2, LR-3, LR-4, and LR-5. External validation was performed for the model with the better performance on the internal test set using two external datasets (EXT-CT and EXT-MR: 68 and 44 observations, respectively).

RESULTS

The transfer learning model outperformed the custom-made model: overall accuracy of 60.4% and AUROCs of 0.85, 0.90, 0.63, 0.82 for LR-1/2, LR-3, LR-4, LR-5, respectively. On EXT-CT, the model had an overall accuracy of 41.2% and AUROCs of 0.70, 0.66, 0.60, 0.76 for LR-1/2, LR-3, LR-4, LR-5, respectively. On EXT-MR, the model had an overall accuracy of 47.7% and AUROCs of 0.88, 0.74, 0.69, 0.79 for LR-1/2, LR-3, LR-4, LR-5, respectively.

CONCLUSION

Our study shows the feasibility of CNN for assigning LI-RADS categories from a relatively small dataset but highlights the challenges of model development and validation.

Prevalence and clinical significance of discordant LI-RADS® observations on multiphase contrast-enhanced MRI in patients with cirrhosis

PURPOSE

To determine the prevalence and clinical significance of discordant LI-RADS^® (Liver Imaging Reporting and Data System) liver observations on multiphase contrast-enhanced (MCE) magnetic resonance imaging (MRI) in patients with cirrhosis.

METHODS

This cross-sectional study included 93 cirrhosis patients who underwent 1.5 or 3 T MCE MRI for evaluation of hepatocellular carcinoma (HCC). Two abdominal radiologists independently reviewed T1-, T2-, diffusion-weighted unenhanced images as well as MCE T1-weighted fat-suppressed images and reported liver observations using LI-RADS^®. Concordance were recorded for detection (co-detected by both radiologists or not), size category (< 10; 10-19; ≥ 20 mm), and LI-RADS^® category assignment as reportable (LR-3/4/5/M) and actionable (LR-4/5/M). The overall concordance (i.e., concordant in detection, size, and LR-category) was calculated with 95% confidence interval [CI], and separately for detection, size, and LR-category. Clinical significance of discordance was assessed as impact on follow-up imaging, referral for biopsy, liver transplant eligibility, or treatment modality.

RESULTS

Reportable and actionable observations were overall concordant between two radiologists only in 32.3% [24.6, 41.0] and 40.1% [29.5, 51.5] of cases, respectively. Poor overall concordance was related to detection concordance of 52.0% [44.3, 59.5] and 62.5% [52.3, 71.8], as well as LR-category concordance of 73.7% [61.6, 83.1] and 70.9% [57.3, 81.6], for reportable and actionable observations, respectively. Discordant LI-RADS^® observations would have impacted clinical management in 30 subjects (43.5%), most (66.7%) of whom were due to discordant detection.

CONCLUSION

Discordant MRI LI-RADS^® observations are common in patients with cirrhosis and may have potential implications for patient management.

How high is the inter-observer reproducibility in the LIRADS reporting system?

Purpose

To investigate the reproducibility of LIRADS v2014 and contribute to its widespread use in clinical practice.

Material and methods

This retrospective, single-centre study was conducted between January 2010 and October 2015. A total of 132 patients who had dynamic magnetic resonance imaging (MRI)/computed tomography (CT) images in the Picture Archiving and Communication Systems (PACS) with liver nodule were included in the study, 37 of whom had histopathology results. Five radiologists who participated in the study, interpreted liver nodules independently on different PACS stations according to the LIRADS reporting system and its main parameters.

Results

We determined that level of inter-observer agreement in the LR-1, LR-5, and LR-5V categories was higher than in the LR-2, LR-3, and LR-4 categories (κ = 0.522, 0.442, and 0.600 in the LR-1, LR-5, and LR-5V categories, respectively; κ = 0.082, 0.298, and 0.143 in the LR-2, LR-3, and LR-4 categories, respectively). The parameter that we observed to have the highest level of inter-observer agreement was venous thrombus (κ = 0.600).

Conclusions

Our study showed that LIRADS achieves an acceptable inter-observer reproducibility in terms of clinical practice although it is insufficient at intermediate risk levels. We think that the prevalence of its use will be further increased with training related to the subject and the assignment of numerical values that express the probability of malignancy for each category and including the ancillary features in the algorithm according to clearer rules.

Liver Imaging Reporting and Data System (LI-RADS) Version 2018: Imaging of Hepatocellular Carcinoma in At-Risk Patients

The Liver Imaging Reporting and Data System (LI-RADS) is composed of four individual algorithms intended to standardize the lexicon, as well as reporting and care, in patients with or at risk for hepatocellular carcinoma in the context of surveillance with US; diagnosis with CT, MRI, or contrast material-enhanced US; and assessment of treatment response with CT or MRI. This report provides a broad overview of LI-RADS, including its historic development, relationship to other imaging guidelines, composition, aims, and future directions. In addition, readers will understand the motivation for and key components of the 2018 update.