LI-RADS Tumor in Vein at CT and Hepatobiliary MRI

Imaging prognostic biomarkers in hepatocellular carcinoma: a comprehensive review

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide with its incidence on the rise globally. This paper provides a comprehensive review of prognostic imaging markers in HCC, emphasizing their role in risk stratification and clinical decision-making. We explore quantitative and qualitative criteria derived from imaging studies, such as computed tomography and magnetic resonance imaging, which can offer valuable insights into the biological behavior of the tumor. While many of these markers are not yet widely integrated into current clinical guidelines, they represent a promising future direction for approaching this highly heterogeneous cancer. However, standardization and validation of these markers remain important challenges. We conclude by emphasizing the importance of ongoing research to enhance clinical practices and improve outcomes for patients with HCC.

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

AIM

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

ESR Essentials: diagnosis of hepatocellular carcinoma-practice recommendations by ESGAR

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy and a leading cause of cancer related death worldwide. Current guidelines for the noninvasive diagnosis of HCC are provided by the European Association for the Study of the Liver (EASL), the American Association for the Study of Liver Diseases (AASLD) which endorsed the Liver Imaging Reporting and Data System (LI-RADS) algorithm, the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC), and the Asian-Pacific Association for the Study of the Liver (APASL). These allow the diagnosis of HCC in high-risk patients in the presence of typical imaging features on contrast-enhanced CT, MRI, or contrast-enhanced ultrasound. Size, non-rim arterial phase hyperenhancement, non-peripheral washout, enhancing capsule, and growth are major imaging features and they should be combined for the diagnosis of HCC. This article provides concise and relevant practice recommendations aimed at general radiologist audience, summarizing the best practice and informing on the essential imaging criteria for the diagnosis of HCC, while also discussing the high-risk population criteria, imaging modalities, and imaging features according to the current guidelines. KEY POINTS: • Noninvasive diagnosis of hepatocellular carcinoma (HCC) can be provided only in patients at high risk. • Contrast-enhanced CT or MRI are the first-line imaging exams for the diagnosis of HCC. • Major imaging features should be combined to provide the diagnosis of definitive HCC.

[Multiparametric magnetic resonance imaging for hepatocellular carcinoma, part 1 : Morphology and dynamic perfusion imaging in primary diagnostics and treatment monitoring]

Radiology plays a key role in the diagnosis and monitoring of hepatocellular carcinoma (HCC). Ultrasound, computed tomography (CT) and magnetic resonance imaging (MRI) are used to identify HCC lesions. Multiparametric MRI provides detailed insights into the tumor biology through the analysis of morphology, perfusion and diffusion. In this way preoperative decisions can be optimized. The guidelines recommend using contrast-enhanced MRI or ultrasound for the diagnosis of HCC. The preferred method is MRI due to its superiority in the detection of small lesions The treatment response is evaluated using modified response evaluation criteria for solid tumors (RECIST) and the European Association for the Study of the Liver (EASL) criteria. The use of multiparametric MRI in conjunction with the liver imaging reporting and data system (LI-RADS) plays overall a central role in the precise diagnosis and monitoring of the treatment of HCC.

Hepatocellular Carcinoma: Optimal Radiological Evaluation before Liver Transplantation

Liver transplantation (LT) is the recommended curative-intent treatment for patients with early or intermediate-stage hepatocellular carcinoma (HCC) who are ineligible for resection. Imaging plays a central role in staging and for selecting the best LT candidates. This review will discuss recent developments in pre-LT imaging assessment, in particular LT eligibility criteria on imaging, the technical requirements and the diagnostic performance of imaging for the pre-LT diagnosis of HCC including the recent Liver Imaging Reporting and Data System (LI-RADS) criteria, the evaluation of the response to locoregional therapy, as well as the non-invasive prediction of HCC aggressiveness and its impact on the outcome of LT. We will also briefly discuss the role of nuclear medicine in the pre-LT evaluation and the emerging role of artificial intelligence models in patients with HCC.

Prognostic Factors for Patients with Proliferative Hepatocellular Carcinoma After Liver Resection

Purpose

There is a scarcity of predictive models currently accessible for prognosticating proliferative hepatocellular carcinoma (HCC), an integrated class of subtype, characterized by a dismal prognosis. Consequently, this study aimed to develop and validate a novel prognostic model capable of accurately predicting the prognosis of proliferative HCC after curative resection.

Patients and Methods

This retrospective multicenter study included patients with solitary HCC who underwent curative liver resection from August 2014 to December 2020 (n = 816). Patients were stratified into either the proliferative HCC cohort (n = 259) or the nonproliferative HCC cohort (n = 557) based on histological criteria. Disease-free survival (DFS) was compared between the two groups before and after one-to-one propensity score matching (PSM). Of all the proliferative HCC patients, 203 patients were assigned to training cohort, and 56 patients were assigned to validation cohort. Univariate and multivariate analyses were performed in training cohort to identify risk factors associated with worse DFS. Thereafter, a predictive model was constructed, subsequently validated in the validation cohort.

Results

The DFS of proliferative HCC was significantly worse than nonproliferative HCC before and after PSM. Meanwhile, multivariate regression analysis revealed that liver cirrhosis (P = 0.032) and larger tumor size (P = 0.000) were independent risk factors of worse DFS. Lastly, the discriminative abilities of the predictive model for 1, 3, 5-year DFS rates, as determined by receiver operating characteristic (ROC) curves, were 0.702, 0.720, and 0.809 in the training cohort and 0.752, 0.776, and 0.851 in the validation cohort, respectively.

Conclusion

This study developed a predictive model with satisfactory accuracy to predict the worse DFS in proliferative HCCs after liver resection. Moreover, this predictive model may serve as a valuable tool for clinicians to predict postoperative HCC recurrence, thereby enabling them to implement early preventative strategies.

Breaking down tumor thrombus: Current strategies for medical management

Tumor thrombus, the intravascular extension of tumor into adjacent blood vessels, is frequently encountered in patients with renal cell carcinoma and hepatocellular carcinoma, and often involves the abdominal vasculature including the renal vein, portal vein, and the inferior vena cava. While a bland thrombus is composed of platelets and fibrin, in contrast, a tumor thrombus refers to an organized collection of tumor cells. Though oftentimes detected incidentally on imaging, tumor thrombus may have significant clinical implications and can be challenging to differentiate from bland thrombus. Additionally, the optimal management of tumor thrombus, including the use of anticoagulation, remains poorly described. This review summarizes common causes of tumor thrombus, as well as its impact on staging, prognosis, and treatment.

Inter-observer agreement and accuracy of LI-RADS v2018 for differentiating tumor in vein from bland thrombus using gadoxetic acid-enhanced magnetic resonance imaging

PURPOSE

To assess inter-observer agreement and accuracy of LI-RADS v2018 for differentiating tumor in vein (TIV) from bland thrombus on gadoxetic acid-enhanced magnetic resonance imaging (Gx-MRI). Secondarily, to determine whether a multi-feature model improves accuracy compared to LI-RADS.

METHODS

We retrospectively identified consecutive patients at risk for hepatocellular carcinoma with venous occlusion(s) reported on Gx-MRI. Five radiologists independently classified each occlusion as TIV or bland thrombus using the LI-RADS TIV criterion (enhancing soft tissue in vein). They also evaluated imaging features suggestive of TIV or bland thrombus. Intra-class correlation coefficient (ICC) was calculated for individual features. A multi-feature model was developed based on consensus scores of features with > 5% consensus prevalence and > 0.40 ICC. Sensitivity and specificity of the LI-RADS criterion and of the cross-validated multi-feature model were compared.

RESULTS

Ninety-eight patients with 103 venous occlusions (58 TIV, 45 bland thrombus) were included. The LI-RADS criterion provided 0.63 ICC and, depending on the reader, 0.62-0.93 sensitivity and 0.87-1.00 specificity. Five other features had > 5% consensus prevalence and > 0.40 ICC, including three LI-RADS suggestive features and two non-LI-RADS features. The optimal multi-feature model incorporated the LI-RADS criterion and one LI-RADS suggestive feature (occluded or obscured vein contiguous with malignant parenchymal mass). After cross-validation, the multi-feature model did not improve sensitivity or specificity compared to the LI-RADS criterion (P = 0.23 and 0.25, respectively).

CONCLUSION

Using Gx-MRI, the LI-RADS criterion for TIV provides substantial inter-observer agreement, variable sensitivity, and high specificity for differentiating TIV from bland thrombus. A cross-validated multi-feature model did not improve diagnostic performance.

Imaging of Hepatobiliary Cancer

The liver and biliary tree are common sites of primary and secondary malignancies. MRI followed by CT is the mainstay for the imaging characterization of these malignancies with the dynamically acquired contrast enhanced phases being the most important for diagnosis. The liver imaging reporting and data system classification provides a useful framework for reporting lesions in patents with underlying cirrhosis or who are at high risk for developing hepatocellular carcinoma. Detection of metastases is improved with the use of liver specific MRI contrast agents and diffusion weighted sequences. Aside from hepatocellular carcinoma, which is often diagnosed noninvasively, other primary hepatobiliary tumors may require biopsy for definite diagnosis, especially when presenting with nonclassic imaging findings. In this review, we examine the imaging findings of common and less common hepatobiliary tumors.

Optional MRI sequences for LI-RADS: why, what, and how?

Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver worldwide. Noninvasive diagnosis of HCC is possible based on imaging features, without the need for tissue diagnosis. Liver Imaging Reporting and Data System (LI-RADS) CT/MRI diagnostic algorithm allows for standardized radiological interpretation and reporting of imaging studies for patients at high risk for HCC. Diagnostic categories of LR-1 to LR-5 designate each liver observation to reflect the probability of overall malignancy, HCC, or benignity based on imaging features, where LR-5 category has > 95% probability of HCC. Optimal imaging protocol and scanning technique as described by the technical recommendations for LI-RADS are essential for the depiction of features to accurately characterize liver observations. The LI-RADS MRI technical guidelines recommend the minimum required sequences of T1-weighted out-of-phase and in-phase Imaging, T2-weighted Imaging, and multiphase T1-weighted Imaging. Additional sequences, including diffusion-weighted imaging, subtraction imaging, and the hepatobiliary phase when using gadobenate dimeglumine as contrast, improve diagnostic confidence, but are not required by the guidelines. These optional sequences can help differentiate true lesions from pseudolesions, detect additional observations, identify parenchymal observations when other sequences are suboptimal, and improve observations conspicuity. This manuscript reviews the optional sequences, the advantages they offer, and discusses technical optimization of these sequences to obtain the highest image quality and to avoid common artifacts.

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.

Performance of LI-RADS Version 2018 on CT for Determining Eligibility for Liver Transplantation According to Milan Criteria in Patients at High Risk for Hepatocellular Carcinoma

Background: LI-RADS has been investigated primarily in terms of detection of hepatocellular carcinoma (HCC), with less attention given to its performance, particularly on CT, in determining eligibility for liver transplantation (LT). Objectives: To assess performance of LI-RADS version 2018 (v2018) on CT for diagnosis of HCC and determination of LT eligibility according to Milan criteria (MC). Methods: This retrospective study included 136 patients (mean age, 53.9±8.1 years; 110 men, 26 women) at high-risk for HCC who underwent liver-protocol CT within 3 months before LT between January 2010 and December 2018. Two radiologists independently reviewed CT examinations using LI-RADS v2018; OPTN classes were constructed from the LI-RADS interpretations. Histopathologic analysis of liver explants served as reference for determining presence of HCC and LT eligibility based on MC. Diagnostic performance was evaluated. Overall survival (OS) was assessed based on medical record review. Results: Based on histopathologic evaluation of liver explants in the 136 patients, 27 had no malignancy, 77 were eligible for LT due to HCC within MC, and 32 were unsuitable for LT (HCC beyond MC in 16, HCC with macrovascular invasion in 12, non-HCC malignancy in 4). LR-5 exhibited per-lesion sensitivity and PPV for HCC of 55.9% and 92.8% for reader 1, and 39.8% and 86.5% for reader 2. When considering LR-5 observations to represent HCC in assessing MC, LI-RADS had accuracy for determining LT eligibility of 92.7% for reader 1 and 85.3% for reader 2; OPTN had accuracy for determining LT eligibility of 89.0% for reader 1 and 84.4% for reader 2. Five-year OS for those within MC versus unsuitable for LT was 92.2 months versus 56.0 months for LI-RADS, 93.4 months versus 53.8 months for OPTN, and 93.3 months versus 55.1 months for histopathologic assessment of liver explants. Conclusions: LI-RADS v2018, as evaluated on CT in high-risk patients, demonstrates high PPV for HCC detection and high accuracy for determining LT eligibility based on MC. LT eligibility based on preoperative LI-RADS evaluation is associated with post-LT survival. Clinical Impact: These findings support the use of LI-RADS on CT in assessing eligibility in patients who are candidates for LT.