Diagnostic performance of LI-RADS for MRI and CT detection of HCC: A systematic review and diagnostic meta-analysis. Eur J Radiol. 2021;134:109404. [PMID: 33276248 DOI: 10.1016/j.ejrad.2020.109404]

Diagnostic Performance of Artificial Intelligence in Detection of Hepatocellular Carcinoma: A Meta-analysis

Due to the increasing interest in the use of artificial intelligence (AI) algorithms in hepatocellular carcinoma detection, we performed a systematic review and meta-analysis to pool the data on diagnostic performance metrics of AI and to compare them with clinicians' performance. A search in PubMed and Scopus was performed in January 2024 to find studies that evaluated and/or validated an AI algorithm for the detection of HCC. We performed a meta-analysis to pool the data on the metrics of diagnostic performance. Subgroup analysis based on the modality of imaging and meta-regression based on multiple parameters were performed to find potential sources of heterogeneity. The risk of bias was assessed using Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) and Prediction Model Study Risk of Bias Assessment Tool (PROBAST) reporting guidelines. Out of 3177 studies screened, 44 eligible studies were included. The pooled sensitivity and specificity for internally validated AI algorithms were 84% (95% CI: 81,87) and 92% (95% CI: 90,94), respectively. Externally validated AI algorithms had a pooled sensitivity of 85% (95% CI: 78,89) and specificity of 84% (95% CI: 72,91). When clinicians were internally validated, their pooled sensitivity was 70% (95% CI: 60,78), while their pooled specificity was 85% (95% CI: 77,90). This study implies that AI can perform as a diagnostic supplement for clinicians and radiologists by screening images and highlighting regions of interest, thus improving workflow.

in vivo and in situ robust quantitative optical biopsy of hepatocellular carcinoma and metastasis based on two-photon autofluorescence imaging

Two-photon autofluorescence (TPAF) imaging is able to offer precise cellular metabolic information with high spatiotemporal resolution, making it a promising biopsy tool. The technique is greatly hampered by the complexity of either the optical system or data processing. Here, the excitation wavelength was optimized to simultaneously excite both flavin adenine dinucleotide and nicotinamide adenine dinucleotide and eliminate the unexpected TPAF. The optical redox ratio (ORR) images were robustly achieved without additional calibration under the optimized single-wavelength excitation. The in vitro, ex vivo, and in vivo biopsy by the TPAF method were systematically studied and compared using hepato-cellular carcinoma and metastasis as examples. It was demonstrated that the proposed TPAF method simplified the optical system, improved the robustness of ORR, and enabled early-stage cancer diagnosis, showing distinguished advantages as compared with previous methods.

Best Practice for MRI Diagnostic Accuracy Research With Lessons and Examples from the LI-RADS Individual Participant Data Group

Medical imaging diagnostic test accuracy research is strengthened by adhering to best practices for study design, data collection, data documentation, and study reporting. In this review, key elements of such research are discussed, and specific recommendations provided for optimizing diagnostic accuracy study execution to improve uniformity, minimize common sources of bias and avoid potential pitfalls. Examples are provided regarding study methodology and data collection practices based on insights gained by the liver imaging reporting and data system (LI-RADS) individual participant data group, who have evaluated raw data from numerous MRI diagnostic accuracy studies for risk of bias and data integrity. The goal of this review is to outline strategies for investigators to improve research practices, and to help reviewers and readers better contextualize a study's findings while understanding its limitations. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Radiomics and liver: Where we are and where we are headed?

Hepatic diffuse conditions and focal liver lesions represent two of the most common scenarios to face in everyday radiological clinical practice. Thanks to the advances in technology, radiology has gained a central role in the management of patients with liver disease, especially due to its high sensitivity and specificity. Since the introduction of computed tomography (CT) and magnetic resonance imaging (MRI), radiology has been considered the non-invasive reference modality to assess and characterize liver pathologies. In recent years, clinical practice has moved forward to a quantitative approach to better evaluate and manage each patient with a more fitted approach. In this setting, radiomics has gained an important role in helping radiologists and clinicians characterize hepatic pathological entities, in managing patients, and in determining prognosis. Radiomics can extract a large amount of data from radiological images, which can be associated with different liver scenarios. Thanks to its wide applications in ultrasonography (US), CT, and MRI, different studies were focused on specific aspects related to liver diseases. Even if broadly applied, radiomics has some advantages and different pitfalls. This review aims to summarize the most important and robust studies published in the field of liver radiomics, underlying their main limitations and issues, and what they can add to the current and future clinical practice and literature.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Assessment of LI-RADS efficacy in classification of hepatocellular carcinoma and benign liver nodules using DCE-MRI features and machine learning

Purpose

The current study aimed to evaluate the efficiency of dynamic contrast-enhanced (DCE) MRI visual features in classifying benign liver nodules and hepatocellular carcinoma (HCC) using a machine learning model.

Methods

115 LI-RADS3, 137 LI-RADS4, and 140 LI-RADS5 nodules were included (392 nodules from 245 patients), which were evaluated by follow-up imaging for LR-3 and pathology results for LR-4 and LR-5 nodules. Data was collected retrospectively from 3 T and 1.5 T MRI scanners. All the lesions were categorized into 124 benign and 268 HCC lesions. Visual features included tumor size, arterial-phase hyper-enhancement (APHE), washout, lesion segment, mass/mass-like, and capsule presence. Gini-importance method extracted the most important features to prevent over-fitting. Final dataset was split into training(70%), validation(10%), and test dataset(20%). The SVM model was used to train the classifying algorithm. For model validation, 5-fold cross-validation was utilized, and the test data set was used to assess the final accuracy. The area under the curve and receiver operating characteristic curves were used to assess the performance of the classifier model.

Results

For test dataset, the accuracy, sensitivity, and specificity values for classifying benign and HCC lesions were 82%,84%, and 81%, respectively. APHE, washout, tumor size, and mass/mass-like features significantly differentiated benign and HCC lesions with p-value < .001.

Conclusions

The developed classification model employing DCE-MRI features showed significant performance of visual features in classifying benign and HCC lesions. Our study also highlighted the significance of mass and mass-like features in addition to LI-RADS categorization. For future work, this study suggests developing a deep-learning algorithm for automatic lesion segmentation and feature assessment to reduce lesion categorization errors.

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

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

Preoperative prediction of cholangiocyte phenotype hepatocellular carcinoma on contrast-enhanced MRI and the prognostic implication after hepatectomy

BACKGROUND

Hepatocellular carcinoma (HCC) expressing cytokeratin (CK) 7 or CK19 has a cholangiocyte phenotype that stimulates HCC proliferation, metastasis, and sorafenib therapy resistance This study aims to noninvasively predict cholangiocyte phenotype-positive HCC and assess its prognosis after hepatectomy.

METHODS

Between January 2010 and May 2022, preoperative contrast-enhanced MRI was performed on consecutive patients who underwent hepatectomy and had pathologically confirmed solitary HCC. Two abdominal radiologists separately assessed the MRI features. A predictive model for cholangiocyte phenotype HCC was created using logistic regression analysis and five-fold cross-validation. A receiver operating characteristic curve was used to calculate the model performance. Kaplan-Meier and log-rank methods were used to evaluate survival outcomes.

RESULTS

In total, 334 patients were included in this retrospective study. Four contrast-enhanced MRI features, including "rim arterial phase hyperenhancement" (OR = 5.9, 95% confidence interval [CI]: 2.9-12.0, 10 points), "nodule in nodule architecture" (OR = 3.5, 95% CI: 2.1-5.9, 7 points), "non-smooth tumor margin" (OR = 1.6, 95% CI: 0.8-2.9, 3 points), and "non-peripheral washout" (OR = 0.6, 95% CI: 0.3-1.0, - 3 points), were assigned to the cholangiocyte phenotype HCC prediction model. The area under the curves for the training and independent validation set were 0.76 and 0.73, respectively. Patients with model-predicted cholangiocyte phenotype HCC demonstrated lower rates of recurrence-free survival (RFS) and overall survival (OS) after hepatectomy, with an estimated median RFS and OS of 926 vs. 1565 days (p < 0.001) and 1504 vs. 2960 days (p < 0.001), respectively.

CONCLUSIONS

Contrast-enhanced MRI features can be used to predict cholangiocyte phenotype-positive HCC. Patients with pathologically confirmed or MRI model-predicted cholangiocyte phenotype HCC have a worse prognosis after hepatectomy.

CRITICAL RELEVANCE STATEMENT

Four contrast-enhanced MRI features were significantly associated with cholangiocyte phenotype HCC and a worse prognosis following hepatectomy; these features may assist in predicting prognosis after surgery and improve personalized treatment decision-making.

KEY POINTS

• Four contrast-enhanced MRI features were significantly associated with cholangiocyte phenotype HCC. • A noninvasive cholangiocyte phenotype HCC predictive model was established based on MRI features. • Patients with cholangiocyte phenotype HCC demonstrated a worse prognosis following hepatic resection.

Egyptian Society of Liver Cancer Recommendation Guidelines for the Management of Hepatocellular Carcinoma

Globally, hepatocellular carcinoma (HCC) is the fourth most common cause of death from cancer. The prevalence of this pathology, which has been on the rise in the last 30 years, has been predicted to continue increasing. HCC is the most common cause of cancer-related morbidity and mortality in Egypt and is also the most common cancer in males. Chronic liver diseases, including chronic hepatitis C, which is a primary health concern in Egypt, are considered major risk factors for HCC. However, HCC surveillance is recommended for patients with chronic hepatitis B virus (HBV) and liver cirrhosis; those above 40 with HBV but without cirrhosis; individuals with hepatitis D co-infection or a family history of HCC; and Nonalcoholic fatty liver disease (NAFLD) patients exhibiting significant fibrosis or cirrhosis. Several international guidelines aid physicians in the management of HCC. However, the availability and cost of diagnostic modalities and treatment options vary from one country to another. Therefore, the current guidelines aim to standardize the management of HCC in Egypt. The recommendations presented in this report represent the current management strategy at HCC treatment centers in Egypt. Recommendations were developed by an expert panel consisting of hepatologists, oncologists, gastroenterologists, surgeons, pathologists, and radiologists working under the umbrella of the Egyptian Society of Liver Cancer. The recommendations, which are based on the currently available local diagnostic aids and treatments in the country, include recommendations for future prospects.

Imaging Findings in Cirrhotic Liver: Pearls and Pitfalls for Diagnosis of Focal Benign and Malignant Lesions

Cirrhosis is the end stage of chronic liver disease and causes architectural distortion and perfusional anomalies. It is a major risk factor for developing hepatocellular carcinoma (HCC). Common disease entities in noncirrhotic livers, such as hemangiomas, can be rare in cirrhotic livers, and benign entities such as confluent hepatic fibrosis and focal nodular hyperplasia-like lesions may mimic the appearance of malignancies,. HCC usually has typical imaging characteristics, such as the major features established by the Liver Imaging Reporting and Data System. However, HCC can also have a spectrum of atypical or uncommon appearances, such as cystic HCC, hypovascular HCC, or macroscopic fat-containing HCC. HCCs with certain genetic mutations such as CTNNB-1-mutated HCC can harbor unique imaging features not seen in other types of HCC. In addition, malignancies that are less common than HCC, such as cholangiocarcinoma and metastases, which can be difficult to differentiate, can still occur in cirrhotic livers. Atypical imaging features of benign and malignant lesions can be challenging to accurately diagnose. Therefore, familiarity with these features and an understanding of the prevalence of disease entities in cirrhotic livers are key in the daily practice of radiologists for evaluation of cirrhotic livers. The authors illustrate the typical and atypical features of benign and malignant lesions in cirrhosis and discuss the technical pitfalls and unique advantages associated with various imaging modalities in assessing cirrhotic livers, including noncontrast and contrast-enhanced US, CT, and MRI. Work of the U.S. Government published under an exclusive license with the RSNA. Quiz questions for this article are available in the supplemental material.

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

Objectives

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

Methods

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

Results

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

Conclusions

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

Detection of sFas, sCD137, and IL-27 Cytokines as Potential Biomarkers for Hepatocellular Carcinoma Diagnosis

Purpose

Hepatocellular carcinoma (HCC), a prevalent type of liver cancer, is mainly diagnosed in the advanced stage, leading to a high mortality rate. Recent advances have identified peripheral cytokines as a potential tool to predict disease outcomes and inform therapeutic decisions. Hence, in this study, we aim to build a predictive model for HCC based on serum levels of different cytokines.

Patients and Methods

We used immunoassay to quantify the concentrations of IL-27, MIP-1β, Perforin, sCD137, sFas, and TNF-α in the serum of 38 HCC patients and 15 healthy controls. Logistic regression was then used to construct classification models detecting HCC based on these cytokines. A nomogram of the best-performing model was generated to visualize HCC prediction.

Results

sFas and MIP-1β were found to be significantly higher in HCC patients compared to controls. Predictive models based on cytokine levels combining sFas, sCD137, and IL-27 performed the best in distinguishing HCC patients from healthy controls. This model has a bias-corrected area under the receiver operating characteristic (ROC) curve (AUC) of 0.948, a sensitivity of 92.11%, a specificity of 93.33%, and an accuracy of 0.925.

Conclusion

Our findings suggest that serum cytokines have the potential to be utilized in HCC screening to improve detection rates.

Multicenter Validation of Abbreviated MRI for Detecting Early-Stage Hepatocellular Carcinoma

Background Abbreviated MRI is a proposed paradigm shift for hepatocellular carcinoma (HCC) surveillance, but data on its performance are lacking for histopathologically confirmed early-stage HCC. Purpose To evaluate the sensitivity and specificity of dynamic contrast-enhanced abbreviated MRI for early-stage HCC detection, using surgical pathologic findings as the reference standard. Materials and Methods This retrospective study was conducted at three U.S. liver transplant centers in patients with cirrhosis who underwent liver resection or transplant between January 2009 and December 2019 and standard "full" liver MRI with and without contrast enhancement within 3 months before surgery. Patients who had HCC-directed treatment before surgery were excluded. Dynamic abbreviated MRI examinations were simulated from the presurgical full MRI by selecting the coronal T2-weighted and axial three-dimensional fat-suppressed T1-weighted dynamic contrast-enhanced sequences at precontrast, late arterial, portal venous, and delayed phases. Two abdominal radiologists at each center independently interpreted the simulated abbreviated examinations with use of the Liver Imaging Reporting and Data System version 2018. Patients with any high-risk liver observations (>LR-3) were classified as positive; otherwise, they were classified as negative. With liver pathologic findings as the reference standard for the presence versus absence of early-stage HCC, the sensitivity, specificity, and their 95% CIs were calculated. Logistic regression was used to identify factors associated with correct classification. Results A total of 161 patients with early-stage HCC (median age, 62 years [IQR, 58-67 years]; 123 men) and 138 patients without HCC (median age, 55 years [IQR, 47-63 years]; 85 men) were confirmed with surgical pathologic findings. The sensitivity and specificity of abbreviated MRI were 88.2% (142 of 161 patients) (95% CI: 83.5, 92.5) and 89.1% (123 of 138 patients) (95% CI: 84.4, 93.8), respectively. Sensitivity was lower for Child-Pugh class B or C versus Child-Pugh class A cirrhosis (64.1% vs 94.2%; P < .001). Conclusion With surgical pathologic findings as the reference standard, dynamic abbreviated MRI had high sensitivity and specificity for early-stage hepatocellular carcinoma detection in patients with compensated cirrhosis but lower sensitivity in those with decompensated cirrhosis. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kim in this issue.

LI-RADS Made Easy

PURPOSE

 The Liver Imaging Reporting and Data System (LI-RADS v2018) standardizes the interpretation and reporting of MDCT and MRI examinations in patients at risk for hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

 For focal liver lesions (called "observations") it assigns categories (LR-1 to 5, LR-M, LR-TIV, LR-TR), which reflect the probability of benignity or malignancy (HCC or other non-HCC malignancies) of the respective observation. The categories assigned are based on major and ancillary image features, which have been developed by the American College of Radiology (ACR), revised several times (now v2018), and validated in many studies. The value of ancillary features to modify LI-RADS categories assigned to observations based on major features is shown.

RESULTS

 This review summarizes the relevant CT and MRI features and presents a step-by-step approach for readers not familiar with LI-RADS on how to use the system. Relevant imaging features and the value of different modalities (contrast-enhanced CT, MRI with extracellular gadolinium chelates or liver-specific contrast agents) is explained.

CONCLUSION

 The widespread adoption of LI-RADS for CT/MRI reporting in high-risk patients would help to reduce inter-reader variability. It could improve communication between radiologists, oncologists, hepatologists, pathologists, and liver surgeons, and lead to better patient management.

KEY POINTS

  · LI-RADS has been developed and revised to address the need for improved diagnosis and standardized categorization of findings in chronic liver disease.. · CT/MRI LI-RADS consists of major criteria and ancillary features to classify observations.. · LI-RADS terminology helps to clarify the communication of liver observations between radiologists and referring physicians..

CITATION FORMAT

· Schima W, Kopf H, Eisenhuber E. LI-RADS made Easy. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1990-5924.

The Characteristics and Prognosis of Alpha-Fetoprotein and Des-Gamma-Carboxy Prothrombin Double-Negative Hepatocellular Carcinoma at Baseline in Higher BCLC Stages

Alpha-fetoprotein (AFP) and des-gamma-carboxyprothrombin (DCP) are widely used as tumor markers to diagnose hepatocellular carcinoma (HCC). Some advanced HCCs demonstrate neither AFP nor DCP. This study investigated the characteristics and prognosis of AFP (<20 ng/mL) and DCP (<40 mAU/ml) double-negative HCC (DNHC) in higher-stage HCC. Between April 2012 and March 2022, 419 consecutive patients were enrolled with newly diagnosed HCC and 372 patients were selected that were diagnosed by histopathology and/or imaging. AFP-negative, DCP-negative, and double-negative HCC were identified in 262 patients (70.4%), 143 patients (38.2%), and 120 patients (32.3%), respectively. In higher-BCLC stages (BCLC-B, C, and D), 17 patients (14.7%) were DNHC. Although there was no difference in BCLC staging, there were more cases under TNM Stage III in DNHC (71.0% vs. 41.4%, p = 0.026). The median maximum tumor diameter was smaller in DNHC [3.2 (1.8−5.0) vs. 5.5 (3.5−9.0) cm, p = 0.001] and their median survival time was significantly better, even in higher-stage HCC [47.0 (24.0−84.0) vs. 19.0 (14.0−30.0) months, p = 0.027). DNHC in higher-BCLC stage HCC is independent of BCLC staging, characterized by a tumor diameter < 5 cm, and is treatable with a good prognosis.

Abbreviated MRI with second shot arterial phase for HCC evaluation: modified version of LI-RADS and recall reduction strategy

OBJECTIVES

To evaluate the feasibility of simulated abbreviated MRI (AMRI) with second shot arterial phase (SSAP) for HCC surveillance and diagnosis.

METHODS

A total of 129 consecutive patients (age, 58.8 ± 11.4 years; male, 71.3%) underwent gadoxetic acid-enhanced MRI using a modified injection protocol for HCC evaluation from July 2017 to February 2018. The modified injection protocol consisted of routine dynamic imaging (6 mL) and SSAP imaging (4 mL). Two radiologists independently reviewed two AMRI sets: AMRI without SSAP (surveillance set) and AMRI with SSAP (diagnosis set). A modified version of the Liver Imaging Reporting and Data System (LI-RADS) for the diagnosis set was devised by referring to contrast-enhanced ultrasound LI-RADS.

RESULTS

Sixty-seven patients with HCC and 62 patients without HCC were included. In the surveillance set, sensitivity and specificity for the detection of patients with HCC were 95.5% and 96.8%, and 94.0% and 96.8% in reviewers 1 and 2, respectively. In the diagnosis set, the scores of most HCCs (76/78, 97.4%) were consistent between LI-RADS of full-protocol and modified LI-RADS of AMRI with SSAP protocol. When the HCC surveillance and diagnosis strategy was changed from strategy 1 (AMRI without SSAP) to strategy 2 (AMRI with SSAP), the recall rate significantly decreased from 52.7 to 3.9% (p < 0.001).

CONCLUSIONS

The modified LI-RADS score of the AMRI with SSAP protocol showed high agreement with the LI-RADS score of the full protocol. The HCC surveillance and diagnosis strategy using the AMRI with SSAP protocol reduced the recall rate. These results may enable to diagnose HCC simultaneously with surveillance.

KEY POINTS

• A modified version of LI-RADS was devised for the diagnostic algorithm using AMRI with the second shot arterial phase (SSAP) by referring to CEUS LI-RADS. • The modified LI-RADS scores using AMRI with SSAP showed a high concordance rate with the conventional LI-RADS score using full-protocol MRI. • The recall rate significantly decreased when the HCC surveillance and diagnosis strategy was changed from strategy 1 (AMRI without SSAP; surveillance then recall test) to strategy 2 (AMRI with SSAP; simultaneous surveillance and diagnosis).

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.

A gadoxetic acid-enhanced MRI-based multivariable model using LI-RADS v2018 and other imaging features for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma

PURPOSE

To identify imaging features of macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) using LI-RADS v2018 and other imaging features and to develop a gadoxetic acid-enhanced MRI (EOB-MRI)-based model for pretreatment prediction of MTM-HCC.

MATERIALS AND METHODS

A total of 93 patients with pathologically proven HCC (39 MTM-HCC and 54 non-MTM-HCC) were retrospectively evaluated with EOB-MRI at 3 T. Imaging analysis according to LI-RADS v2018 was evaluated by two readers. Univariate and multivariate analyses were performed to determine independent predictors for MTM-HCC. Different logistic regression models were built based on MRI features, including model A (enhancing capsule, blood products in mass and ascites), model B (enhancing capsule and ascites), model C (blood products in mass and ascites), and model D (blood products in mass and enhancing capsule). Diagnostic performance was assessed by receiver operating characteristic (ROC) curves.

RESULTS

After multivariate analysis, absence of enhancing capsule (odds ratio = 0.102, p = 0.010), absence of blood products in mass (odds ratio = 0.073, p = 0.030), and with ascites (odds ratio = 55.677, p = 0.028) were identified as independent differential factors for the presence of MTM-HCC. Model A yielded a sensitivity, specificity, and AUC of 35.90% (21.20,52.80), 94.44% (84.60, 98.80), and 0.731 (0.629, 0.818). Model A achieved a comparable AUC than model D (0.731 vs. 0.699, p = 0.333), but a higher AUC than model B (0.731 vs. 0.644, p = 0.048) and model C (0.731 vs. 0.650, p = 0.005).

CONCLUSION

The EOB-MRI-based model is promising for noninvasively predicting MTM-HCC and may assist clinicians in pretreatment decisions.

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.

Detection of hepatocellular carcinoma in a population at risk: iodine-enhanced multidetector CT and/or gadoxetic acid-enhanced 3.0 T MRI

OBJECTIVE

To evaluate the diagnostic performance of iodine-enhanced multidetector CT and gadoxetic acid-enhanced 3.0 Tesla (T) MRI for detection of hepatocellular carcinoma of patients.

DESIGN

Retrospective, multicentre cohort study.

SETTING

The Gong'an County People's Hospital, Gong'an County, China and the First People's Hospital of Jingzhou City, China.

PARTICIPANTS

Reports of CT, MRI and liver biopsies/histopathology data of a total of 815 patients who at risk were reviewed.

PRIMARY AND SECONDARY OUTCOME MEASURES

The lesions that possessed detection in the plain scan phase, enhanced arterial phase and/or enhanced portal phase of CT images and the lesions that possessed enhancements in the plain scan phase, enhanced arterial phase, enhanced portal phase and/or hepatobiliary phases of MRI were considered hepatocellular carcinoma. The decision of hepatocellular carcinoma was made based on the current Liver Imaging and Data Reporting System for diagnosing hepatocellular carcinoma.

RESULTS

True positive hepatocellular carcinoma (563 vs 521, p=0.0314), true negative hepatocellular carcinoma (122 vs 91, p=0.0275), false positive hepatocellular carcinoma (88 vs 123, p=0.0121), false negative hepatocellular carcinoma (42 vs 80, p=0.0005), specificity (58.10 vs 42.52, p=0.0478) and negative clinical utility (0.1 vs 0.073, p=0.0386) were superior for gadoxetic acid-enhanced 3.0 T MRI than those of iodine-enhanced multidetector CT. Sensitivity and accuracy for gadoxetic acid-enhanced 3.0 T MRI were 93.06% and 77.40 %, respectively, and those for iodine-enhanced multidetector CT were 86.69% and 75.09 %, respectively. Likelihood to detect hepatocellular carcinoma for gadoxetic acid-enhanced 3.0 T MRI was 0-0.894 diagnostic confidence/lesion, and that for iodine-enhanced multidetector CT was 0-0.887 diagnostic confidence/lesion.

CONCLUSION

Gadoxetic acid-enhanced 3.0 T MRI facilitates the confidence of initiation of treatment of hepatocellular carcinoma.

LEVEL OF EVIDENCE

III.

TECHNICAL EFFICACY STAGE

4.

Biopsy for advanced hepatocellular carcinoma: results of a multicentre UK audit

BACKGROUND

Advanced hepatocellular carcinoma (HCC) is commonly diagnosed using non-invasive radiological criteria (NIRC) defined by the European Association for the Study of the Liver or the American Association for the Study of Liver Diseases. In 2017, The National Institute for Clinical Excellence mandated histological confirmation of disease to authorise the use of sorafenib in the UK.

METHODS

This was a prospective multicentre audit in which patients suitable for sorafenib were identified at multidisciplinary meetings. The primary analysis cohort (PAC) was defined by the presence of Child-Pugh class A liver disease and performance status 0-2. Clinical, radiological and histological data were reported locally and collected on a standardised case report form.

RESULTS

Eleven centres reported 418 cases, of which 361 comprised the PAC. Overall, 76% had chronic liver disease and 66% were cirrhotic. The diagnostic imaging was computed tomography in 71%, magnetic resonance imaging in 27% and 2% had both. Pre-existing histology was available in 45 patients and 270 underwent a new biopsy, which confirmed HCC in 93.4%. Alternative histological diagnoses included cholangiocarcinoma (CC) and combined HCC-CC. In cirrhotic patients, NIRC criteria had a sensitivity of 65.4% and a positive predictive value of 91.4% to detect HCC. Two patients (0.7%) experienced mild post-biopsy bleeding.

CONCLUSION

The diagnostic biopsy is safe and feasible for most patients eligible for systemic therapy.

The Value of Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System in the Diagnosis of Hepatocellular Carcinoma:: A Meta-Analysis

OBJECTIVES

The aim of this study is to systematically evaluate the diagnostic ability of the contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system (LI-RADS) in hepatocellular carcinoma (HCC).

METHODS

We searched relevant studies from PubMed, Medline, and Embase database. After literature search, duplicate removal, and data extraction, we calculated and analyzed the pooled sensitivity, pooled specificity, pooled odds ratios of diagnostic, pooled likelihood ratio (LR) of positive and negative, and area under the curve (AUC), accuracy, and F1 score to evaluate the diagnostic value of CEUS LI-RADS for HCC.

RESULTS

Thirteen studies and 6491 patients were included in this analysis. The pooled sensitivity and pooled specificity were 0.72 (95% confidence interval [CI], 0.70-0.73) and 0.92 (95% CI, 0.91-0.93), respectively. The positive LR was 8.02 (95% CI, 4.93-13.06) and the negative LR was 0.31 (95% CI, 0.27-0.37). The pooled diagnostic odds ratio was 27.91 (95% CI, 15.39-50.63). The overall AUC was 0.8406 and the accuracy was 0.77.

CONCLUSIONS

CEUS LI-RADS is an effective and promising method to diagnose HCC.

Current and Emerging Tools for Hepatocellular Carcinoma Surveillance

Hepatocellular carcinoma (HCC) is a leading cause of cancer‐related mortality worldwide. Early detection of HCC enables patients to avail curative therapies that can improve patient survival. Current international guidelines advocate for the enrollment of patients at high risk for HCC, like those with cirrhosis, in surveillance programs that perform ultrasound every 6 months. In recent years, many studies have further characterized the utility of established screening strategies and have introduced new promising tools for HCC surveillance. In this review, we provide an overview of the most promising new imaging modalities and biomarkers for the detection of HCC. We discuss the role of imaging tools like ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) in the early detection of HCC, and describe recent innovations which can potentially enhance their applicability, including contrast enhanced ultrasound, low‐dose CT scans, and abbreviated MRI. Next, we outline the data supporting the use of three circulating biomarkers (i.e., alpha‐fetoprotein [AFP], AFP lens culinaris agglutinin‐reactive fraction, and des‐gamma‐carboxy prothrombin) in HCC surveillance, and expand on multiple emerging liquid biopsy biomarkers, including methylated cell‐free DNA (cfDNA), cfDNA mutations, extracellular vesicles, and circulating tumor cells. These promising new imaging modalities and biomarkers have the potential to improve early detection, and thus improve survival, in patients with HCC.

State of the Art in Artificial Intelligence and Radiomics in Hepatocellular Carcinoma

The most common liver malignancy is hepatocellular carcinoma (HCC), which is also associated with high mortality. Often HCC develops in a chronic liver disease setting, and early diagnosis as well as accurate screening of high-risk patients is crucial for appropriate and effective management of these patients. While imaging characteristics of HCC are well-defined in the diagnostic phase, challenging cases still occur, and current prognostic and predictive models are limited in their accuracy. Radiomics and machine learning (ML) offer new tools to address these issues and may lead to scientific breakthroughs with the potential to impact clinical practice and improve patient outcomes. In this review, we will present an overview of these technologies in the setting of HCC imaging across different modalities and a range of applications. These include lesion segmentation, diagnosis, prognostic modeling and prediction of treatment response. Finally, limitations preventing clinical application of radiomics and ML at the present time are discussed, together with necessary future developments to bring the field forward and outside of a purely academic endeavor.

Non-cirrhotic hepatocellular carcinoma in chronic viral hepatitis: Current insights and advancements

Primary liver cancers carry significant morbidity and mortality. Hepatocellular carcinoma (HCC) develops within the hepatic parenchyma and is the most common malignancy originating from the liver. Although 80% of HCCs develop within background cirrhosis, 20% may arise in a non-cirrhotic milieu and are referred to non-cirrhotic-HCC (NCHCC). NCHCC is often diagnosed late due to lack of surveillance. In addition, the rising prevalence of non-alcoholic fatty liver disease and diabetes mellitus have increased the risk of developing HCC on non-cirrhotic patients. Viral infections such as chronic Hepatitis B and less often chronic hepatitis C with advance fibrosis are associated with NCHCC. NCHCC individuals may have Hepatitis B core antibodies and occult HBV infection, signifying the role of Hepatitis B infection in NCHCC. Given the effectiveness of current antiviral therapies, surgical techniques and locoregional treatment options, nowadays such patients have more options and potential for cure. However, these lesions need early identification with diagnostic models and multiple surveillance strategies to improve overall outcomes. Better understanding of the NCHCC risk factors, tumorigenesis, diagnostic tools and treatment options are critical to improving prognosis and overall outcomes on these patients. In this review, we aim to discuss NCHCC epidemiology, risk factors, and pathogenesis, and elaborate on NCHCC diagnosis and treatment strategies.