LI-RADS v2018 category and imaging features: inter-modality agreement between contrast-enhanced CT, gadoxetate disodium-enhanced MRI, and extracellular contrast-enhanced MRI

PURPOSE

To perform an intra-individual comparison of LI-RADS category and imaging features in patients at high risk of hepatocellular carcinoma (HCC) on contrast-enhanced CT, gadoxetate disodium-enhanced MRI (EOB-MRI), and extracellular agent-enhanced MRI (ECA-MRI) and to analyze the diagnostic performance of each imaging modality.

METHOD

This retrospective study included cirrhotic patients with at least one LR-3, LR-4, LR-5, LR-M or LR-TIV observation imaged with at least two imaging modalities among CT, EOB-MRI, or ECA-MRI. Two radiologists evaluated the observations using the LI-RADS v2018 diagnostic algorithm. Reference standard included pathologic confirmation and imaging criteria according to LI-RADS v2018. Imaging features were compared between different exams using the McNemar test. Inter-modality agreement was calculated by using the weighted Cohen's kappa (k) test.

RESULTS

A total of 144 observations (mean size 34.0 ± 32.4 mm) in 96 patients were included. There were no significant differences in the detection of major and ancillary imaging features between the three imaging modalities. When considering all the observations, inter-modality agreement for category assignment was substantial between CT and EOB-MRI (k 0.60; 95%CI 0.44, 0.75), moderate between CT and ECA-MRI (k 0.46; 95%CI 0.22, 0.69) and substantial between EOB-MRI and ECA-MRI (k 0.72; 95%CI 0.59, 0.85). In observations smaller than 20 mm, inter-modality agreement was fair between CT and EOB-MRI (k 0.26; 95%CI 0.05, 0.47), moderate between CT and ECA-MRI (k 0.42; 95%CI -0.02, 0.88), and substantial between EOB-MRI and ECA-MRI (k 0.65; 95%CI 0.47, 0.82). ECA-MRI demonstrated the highest sensitivity (70%) and specificity (100%) when considering LR-5 as predictor of HCC.

CONCLUSIONS

Inter-modality agreement between CT, ECA-MRI, and EOB-MRI decreases in observations smaller than 20 mm. ECA-MRI has the provided higher sensitivity for the diagnosis of HCC.

Diagnostic performance of CT/MRI LI-RADS v2018 in non-cirrhotic steatotic liver disease

OBJECTIVE

To assess the performance of computed tomography (CT)/magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS) among patients with non-cirrhotic steatotic liver disease (SLD).

MATERIALS AND METHODS

This IRB-approved, retrospective study included 119 observations from 77 adult patients (36 women, 41 men; median 64 years) who underwent liver CT or MRI from 2010 to 2023. All patients had histopathologic evidence of SLD without cirrhosis. Three board-certified abdominal radiologists blinded to tissue diagnosis and imaging follow-up assessed observations with LI-RADS. The positive predictive value (PPV), sensitivity, specificity, accuracy, and inter-reader agreement were calculated.

RESULTS

Seventy-five observations (63%) were benign and 44 (37%) were malignant. PPV for hepatocellular carcinoma (HCC) was 0-0% for LR-1, 0-0% for LR-2, 0-7% for LR-3, 11-20% for LR-4, 75-88% for LR-5, 0-8% for LR-M, and 50-75% for LR-TIV. For LR-5 in identifying HCC, sensitivity was 79-83%, specificity was 91-97%, and accuracy was 89-92%. For composite categories of LR-5, LR-M, or LR-TIV in identifying malignancy, sensitivity was 86-89%, specificity was 85-96%, and accuracy was 86-93%. The most common false positives for LR-5 were hepatocellular adenomas. Only 59-65% of HCCs showed non-peripheral washout at CT versus 67-83% at MRI, though nearly all had an enhancing capsule. PPV and accuracy of LR-5 for HCC did not differ by modality. Inter-reader agreement for major features ranged from 0.667 to 0.830 and was 0.766 for the final category.

CONCLUSION

Despite challenges such as the lower prevalence of non-peripheral washout at CT and overlapping imaging features between HCC and hepatocellular adenomas, LI-RADS may serve as an effective tool in assessing focal liver lesions in SLD.

CLINICAL RELEVANCE STATEMENT

LI-RADS in non-cirrhotic steatotic liver disease can effectively diagnose hepatocellular carcinoma and malignancy at computed tomography and magnetic resonance imaging, thereby guiding clinical management decisions and expediting patient care pathways.

KEY POINTS

Performance of LI-RADS is unknown in non-cirrhotic patients with steatotic liver disease. LI-RADS 5 category showed a high pooled specificity of 91-97% for hepatocellular carcinoma. LI-RADS can non-invasively risk stratify focal liver observations in non-cirrhotic patients with steatotic liver disease.

Quantifying the natural growth rate of hepatocellular carcinoma: A real-world retrospective study in southwestern China

BACKGROUND

In recent years, approximately half of the newly diagnosed cases and mortalities attributed to hepatocellular carcinoma (HCC) have been reported in China. Despite the high incidence of HCC, there remains a paucity of data regarding the natural growth pattern and the determination of optimal surveillance intervals specific to the Chinese population.

AIM

To quantify the natural tumor growth pattern of HCC in regional China.

METHODS

A retrospective analysis was performed on patients from a single institution in Southwest China who had undergone two or more serial dynamic computed tomography or magnetic resonance imaging scans between 2014 and 2020, without having received any anti-cancer therapy. Tumor growth was assessed using tumor volume doubling time (TVDT) and tumor growth rate (TGR), with volumes measured manually by experienced radiologists. Simple univariate linear regression and descriptive analysis were applied to explore associations between growth rates and clinical factors.

RESULTS

This study identifies the median TVDT for HCC as 163.4 d, interquartile range (IQR) 72.1 to 302.3 d, with a daily TGR of 0.42% (IQR 0.206%-0.97%). HCC growth patterns reveal that about one-third of tumors grow indolently with TVDT exceeding 270 d, another one-third of tumors exhibit rapid growth with TVDT under 90 d, and the remaining tumors show intermediate growth rates, with TVDT ranging between 3 to 9 months.

CONCLUSION

The identified TGRs support biannual surveillance and follow-up for HCC patients in certain regions of China. Given the observed heterogeneity in HCC growth, further investigation is warranted.

Congestive Hepatopathy: Pathophysiology, Workup, and Imaging Findings with Pathologic Correlation

Liver congestion is increasingly encountered in clinical practice and presents diagnostic pitfalls of which radiologists must be aware. The complex altered hemodynamics associated with liver congestion leads to diffuse parenchymal changes and the development of benign and malignant nodules. Distinguishing commonly encountered benign hypervascular lesions, such as focal nodular hyperplasia (FNH)-like nodules, from hepatocellular carcinoma (HCC) can be challenging due to overlapping imaging features. FNH-like lesions enhance during the hepatic arterial phase and remain isoenhancing relative to the background liver parenchyma but infrequently appear to wash out at delayed phase imaging, similar to what might be seen with HCC. Heterogeneity, presence of an enhancing capsule, washout during the portal venous phase, intermediate signal intensity at T2-weighted imaging, restricted diffusion, and lack of uptake at hepatobiliary phase imaging point toward the diagnosis of HCC, although these features are not sensitive individually. It is important to emphasize that the Liver Imaging Reporting and Data System (LI-RADS) algorithm cannot be applied in congested livers since major LI-RADS features lack specificity in distinguishing HCC from benign hypervascular lesions in this population. Also, the morphologic changes and increased liver stiffness caused by congestion make the imaging diagnosis of cirrhosis difficult. The authors discuss the complex liver macro- and microhemodynamics underlying liver congestion; propose a more inclusive approach to and conceptualization of liver congestion; describe the pathophysiology of liver congestion, hepatocellular injury, and the development of benign and malignant nodules; review the imaging findings and mimics of liver congestion and hypervascular lesions; and present a diagnostic algorithm for approaching hypervascular liver lesions. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand

BACKGROUND

To evaluate survival rates of hepatocellular carcinoma (HCC), the Chiang Mai Cancer Registry provided characteristics data of 6276 HCC patients diagnosed between 1998-2020 based on evolution of imaging diagnosis. Evolution can be separated into four cohorts, namely, cohort 1 (1990-2005) when we had ultrasound (US) and single-phase computed tomography (CT), cohort 2 (2006-2009) when one multi-phase CT and one magnetic resonance imaging (MRI) were added, cohort 3 (2010-2015) when MRI with LI-RADS was added, and finally, cohort 4 (2016-2020) when two upgraded MRIs with LI-RADS were added.

METHODS

Cox proportional hazard models were used to determine the relation between death and risk factors including methods of imagining diagnosis, gender, age of diagnosis, tumor stages, history of smoking and alcohol-use, while Kaplan-Meier curves were used to calculate survival rates.

RESULTS

The median age of diagnosis was 57.0 years (IQR: 50.0-65.0) and the median survival time was 5.8 months (IQR: 1.9-26.8) during the follow-up period. In the univariable analysis, all factors were all associated with a higher risk of death in HCC patients except age of diagnosis. In a multivariable analysis, elderly age at diagnosis, regional and metastatic stages and advanced methods of imagining diagnosis during cohorts 2 and 3 were independently associated with the risk of death in HCC patients. The survival rate of patients diagnosed during cohort 4 was significantly higher than the other cohorts.

CONCLUSION

As a significantly increasing survival rate of HCC patients in cohort 4, advanced methods of diagnostic imaging can be a part of the recommendation to diagnose HCC.

LI-RADS: Looking Back, Looking Forward

Since its initial release in 2011, the Liver Imaging Reporting and Data System (LI-RADS) has evolved and expanded in scope. It started as a single algorithm for hepatocellular carcinoma (HCC) diagnosis with CT or MRI with extracellular contrast agents and has grown into a multialgorithm network covering all major liver imaging modalities and contexts of use. Furthermore, it has developed its own lexicon, report templates, and supplementary materials. This article highlights the major achievements of LI-RADS in the past 11 years, including adoption in clinical care and research across the globe, and complete unification of HCC diagnostic systems in the United States. Additionally, the authors discuss current gaps in knowledge, which include challenges in surveillance, diagnostic population definition, perceived complexity, limited sensitivity of LR-5 (definite HCC) category, management implications of indeterminate observations, challenges in reporting, and treatment response assessment following radiation-based therapies and systemic treatments. Finally, the authors discuss future directions, which will focus on mitigating the current challenges and incorporating advanced technologies. Tha authors envision that LI-RADS will ultimately transform into a probability-based system for diagnosis and prognostication of liver cancers that will integrate patient characteristics and quantitative imaging features, while accounting for imaging modality and contrast agent.

Spontaneously Ruptured Hepatocellular Carcinoma: Computed Tomography-Based Assessment

Spontaneously ruptured hepatocellular carcinoma (SRHCC) is an uncommon and life-threatening complication in patients with hepatocellular carcinoma (HCC). It is usually associated with chronic liver disease and has a poor prognosis with a high mortality rate during the acute phase. SRHCC can cause a severe and urgent condition of acute abdomen disease and requires a correct diagnosis to achieve adequate treatment. Clinical presentation is related to the presence of hemoperitoneum, and abdominal pain is the most common symptom (66–100% of cases). Although the treatment approach is not unique, trans-arterial (chemo)embolization (TAE/TACE) followed by staged hepatectomy has shown better results in long-term survival. A multi-phase contrast-enhanced CT (CECT) scan is a pivotal technique in the diagnosis of SRHCC due to its diagnostic accuracy and optimal temporal resolution. The correct interpretation of the main CT findings in SRHCC, such as active contrast extravasation and the sentinel clot sign, is fundamental for a prompt and correct diagnosis. Furthermore, CT also plays a role as a post-operative control procedure, especially in patients treated with TAE/TACE. Therefore, a multi-phase CECT scan should be the diagnostic tool of choice in SRHCC since it suggests an immediate need for treatment with a consequent improvement in prognosis.

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.

Liver Imaging Reporting and Data System criteria for the diagnosis of hepatocellular carcinoma in clinical practice: A pictorial minireview

Hepatocellular carcinoma (HCC) is the sixth most common cancer. The main risk factors associated with HCC development include hepatitis B virus, hepatitis C virus, alcohol consumption, aflatoxin B1, and nonalcoholic fatty liver disease. However, hepatocarcinogenesis is a complex multistep process. Various factors lead to hepatocyte malignant transformation and HCC development. Diagnosis and surveillance of HCC can be made with the use of liver ultrasound (US) every 6 mo. However, the sensitivity of this imaging method to detect HCC in a cirrhotic liver is limited, due to the abnormal liver parenchyma. Computed tomography (CT) and magnetic resonance imaging (MRI) are considered to be most useful tools for at-risk patients or patients with inadequate US. Liver biopsy is still used for diagnosis and prognosis of HCC in specific nodules that cannot be definitely characterized as HCC by imaging. Recently the American College of Radiology designed the Liver Imaging Reporting and Data System (LI-RADS), which is a comprehensive system for standardized interpretation of CT and MRI liver examinations that was first proposed in 2011. In 2018, it was integrated into the American Association for the Study of Liver Diseases guidance statement for HCC. LI-RADS is designed to ensure high sensitivity, precise categorization, and high positive predictive value for the diagnosis of HCC and is applied to “high-risk populations” according to specific criteria. Most importantly LI-RADS criteria achieved international collaboration and consensus among liver experts around the world on the best practices for caring for patients with or at risk for HCC.

Contrast Agents for Hepatocellular Carcinoma Imaging: Value and Progression

Hepatocellular carcinoma (HCC) has the third-highest incidence in cancers and has become one of the leading threats to cancer death. With the research on the etiological reasons for cirrhosis and HCC, early diagnosis has been placed great hope to form a favorable prognosis. Non-invasive medical imaging, including the associated contrast media (CM)-based enhancement scan, is taking charge of early diagnosis as mainstream. Meanwhile, it is notable that various CM with different advantages are playing an important role in the different imaging modalities, or even combined modalities. For both physicians and radiologists, it is necessary to know more about the proper imaging approach, along with the characteristic CM, for HCC diagnosis and treatment. Therefore, a summarized navigating map of CM commonly used in the clinic, along with ongoing work of agent research and potential seeded agents in the future, could be a needed practicable aid for HCC diagnosis and prognosis.

MRI-Based Radiomic Features Help Identify Lesions and Predict Histopathological Grade of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common form of liver cancer. Radiomics is a promising tool that may increase the value of magnetic resonance imaging (MRI) in the management of HCC. The purpose of our study is to develop an MRI-based radiomics approach to preoperatively detect HCC and predict its histological grade. Thirty-eight HCC patients at staging who underwent axial T2-weighted and dynamic contrast-enhanced MRI (DCE-MRI) were considered. Three-dimensional volumes of interest (VOIs) were manually placed on HCC lesions and normal hepatic tissue (HT) on arterial phase post-contrast images. Radiomic features from T2 images and arterial, portal and tardive post-contrast images from DCE-MRI were extracted by using Pyradiomics. Feature selection was performed using correlation filter, Wilcoxon-rank sum test and mutual information. Predictive models were constructed for HCC differentiation with respect to HT and HCC histopathologic grading used at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. Promising results were obtained from radiomic prediction models, with best AUCs ranging from 71% to 96%. Radiomics MRI based on T2 and DCE-MRI revealed promising results concerning both HCC detection and grading. It may be a suitable tool for personalized treatment of HCC patients and could also be used to develop new prognostic biomarkers useful for HCC assessment without the need for invasive procedures.