Enhancement patterns of hepatocellular carcinomas on multiphasicmultidetector row CT: comparison with pathological differentiation

State-of-the-Art Imaging of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third most fatal and fifth most common cancer worldwide. The incidence of HCC is increasing, in part due to an increase in obesity and non-alcoholic fatty liver disease. This review highlights the vital role that imaging plays in managing HCC, from identifying high-risk patients to diagnosing, staging, and assessing response to treatment without the need for an invasive biopsy. Various imaging modalities including Ultrasound (US), Multidetector Computed Tomography (MDCT), and Magnetic Resonance Imaging (MRI) each offer unique advantages to detect HCC characteristics such as lesion size, appearance, and vascular changes. Ultrasound serves as a cost-effective, accessible tool for early detection, especially in patients with cirrhotic livers, while MDCT and MRI provide detailed visualization and differentiation of HCC from other liver lesions. We also highlight the role of liver-specific contrast agents and the Liver Imaging Reporting and Data System (LI-RADS) in enhancing diagnostic accuracy. Furthermore, advanced techniques like Diffusion-weighted imaging and the potential of Artificial Intelligence improve HCC detection and characterization. This comprehensive review underscores the evolution of imaging technologies and the pivotal role in advancing HCC management, offering insights into future directions for research and clinical practice. SIMPLE SUMMARY: In this study, we review the crucial role that imaging plays in the diagnosis and management of hepatocellular carcinoma (HCC). With the incidence of HCC on the rise, partly due to increasing obesity and non-alcoholic fatty liver disease, early and accurate detection is more important than ever. We herein characterize the role of different techniques such as Ultrasound, MRI, and CT scans in the treatment of HCC. Advances in imaging techniques have not only aided in the precise staging of HCC, as well as and monitoring treatment response, but also offer the potential to replace invasive biopsy to diagnose primary liver malignancies. This review highlights HCC's unique features and how imaging contributes to improving patient outcomes in the medical community.

Clinical prediction of microvascular invasion in hepatocellular carcinoma using an MRI-based graph convolutional network model integrated with nomogram

OBJECTIVES

Based on enhanced MRI, a prediction model of microvascular invasion (MVI) for hepatocellular carcinoma (HCC) was developed using graph convolutional network (GCN) combined nomogram.

METHODS

We retrospectively collected 182 HCC patients confirmed histopathologically, all of them performed enhanced MRI before surgery. The patients were randomly divided into training and validation groups. Radiomics features were extracted from the arterial phase (AP), portal venous phase (PVP), and delayed phase (DP), respectively. After removing redundant features, the graph structure by constructing the distance matrix with the feature matrix was built. Screening the superior phases and acquired GCN Score (GS). Finally, combining clinical, radiological and GS established the predicting nomogram.

RESULTS

27.5% (50/182) patients were with MVI positive. In radiological analysis, intratumoural artery (P = 0.007) was an independent predictor of MVI. GCN model with grey-level cooccurrence matrix-grey-level run length matrix features exhibited area under the curves of the training group was 0.532, 0.690, and 0.885 and the validation group was 0.583, 0.580, and 0.854 for AP, PVP, and DP, respectively. DP was selected to develop final model and got GS. Combining GS with diameter, corona enhancement, mosaic architecture, and intratumoural artery constructed a nomogram which showed a C-index of 0.884 (95% CI: 0.829-0.927).

CONCLUSIONS

The GCN model based on DP has a high predictive ability. A nomogram combining GS, clinical and radiological characteristics can be a simple and effective guiding tool for selecting HCC treatment options.

ADVANCES IN KNOWLEDGE

GCN based on MRI could predict MVI on HCC.

CT-based radiomics for predicting pathological grade in hepatocellular carcinoma

Objective

To construct and validate radiomics models for hepatocellular carcinoma (HCC) grade predictions based on contrast-enhanced CT (CECT).

Methods

Patients with pathologically confirmed HCC after surgery and underwent CECT at our institution between January 2016 and December 2020 were enrolled and randomly divided into training and validation datasets. With tumor segmentation and feature extraction, radiomic models were constructed using univariate analysis, followed by least absolute shrinkage and selection operator (LASSO) regression. In addition, combined models with clinical factors and radiomics scores (Radscore) were constructed using logistic regression. Finally, all models were evaluated using the receiver operating characteristic (ROC) curve with the area under the curve (AUC), calibration curve, and decision curve analysis (DCA).

Results

In total 242 patients were enrolled in this study, of whom 170 and 72 formed the training and validation datasets, respectively. The arterial phase and portal venous phase (AP+VP) radiomics model were evaluated as the best for predicting HCC pathological grade among all the models built in our study (AUC = 0.981 in the training dataset; AUC = 0.842 in the validation dataset) and was used to build a nomogram. Furthermore, the calibration curve and DCA indicated that the AP+VP radiomics model had a satisfactory prediction efficiency.

Conclusions

Low- and high-grade HCC can be distinguished with good diagnostic performance using a CECT-based radiomics model.

Comparison of CT and gadoxetic acid-enhanced MRI with liver imaging reporting and data system to assess liver tumors before resection

BACKGROUND/PURPOSE

Hepatocellular carcinoma (HCC) can be noninvasively diagnosed through dynamic computed tomography (CT) and magnetic resonance imaging (MRI). We compared the diagnostic performance of CT and gadoxetic acid-enhanced MRI (EOB-MRI) in categorizing tumors by using the 2018 version of the Liver Imaging Reporting And Data System (LI-RADS v2018) and assessing liver tumors before resection.

METHODS

Data from a prospective cohort from October 2011 to March 2019 on 106 hepatic tumors in 96 patients with suspected malignancy were included in this study. We performed preoperative CT and EOB-MRI, and reviewed these images retrospectively. Ninety-seven tumors from 87 patients were pathologically diagnosed as HCC, and nine tumors were non-HCC. The clinical data, imaging characteristics, diagnostic performance, and outcomes of CT and EOB-MRI were analyzed and compared.

RESULTS

EOB-MRI had more favorable diagnostic performance (area under curve: 0.920 vs. 0.868) and significantly higher sensitivity (86.87% vs. 69.70%, p = 0.005) than did CT. However, the specificity of EOB-MRI did not differ from that of CT (88.89% vs. 88.89%, p > 0.999). Fourteen (14.5%) patients with pathologically verified HCC had lesions categorized as LI-RADS 4 through CT and as LI-RADS 5 through EOB-MRI. Patients with EOB-MRI-categorized but not CT-categorized LI-RADS 5 lesions had significantly longer overall survival than did those with LI-RADS 4 lesions (p < 0.001).

CONCLUSION

EOB-MRI had higher sensitivity than did CT in diagnosing HCC. Patients with EOB-MRI-categorized LI-RADS 5 lesions had more favorable outcomes than did those with LI-RADS 4 lesions after liver resection.

CT texture features and lung shunt fraction measured using 99mTc-macroaggregated albumin SPECT/CT before trans-arterial radioembolization for hepatocellular carcinoma patients

The aim of this study is to determine whether contrast-enhanced computed tomography (CECT)-based texture parameters can predict high (> 30 Gy) expected lung dose (ELD) calculated using 99mTc macroaggregated albumin single-photon emission computed tomography/computed tomography (SPECT/CT) for pre-trans-arterial radioembolization (TARE) dosimetry. 35 patients were analyzed, with a treatable planned dose of ≥ 200 Gy for unresectable hepatocellular carcinoma (HCC). Lung shunt fraction (LSF) was obtained from planar and SPECT/CT scans. Texture features of the tumor lesion on CECT before TARE were analyzed. Univariate and multivariate linear regression analyses were performed to determine potential ELD > 30 Gy predictors. Among the 35 patients, nine (25.7%) had ELD > 30 Gy, and had a higher LSF than the ELD ≤ 30 Gy group using the planar (20.7 ± 8.0% vs. 6.3 ± 3.3%; P < 0.001) and SPECT/CT (12.4 ± 5.1% vs. 3.5 ± 2.0%; P < 0.001) scans. The tumor integral total (HU × L) value was a predictor for high LSF using SPECT/CT, with an area under the curve, sensitivity, and specificity of 0.983 (95% confidence interval: 0.869-1.000, P < 0.001), 100%, and 88.5%, respectively. The tumor integral total value is an imaging marker for predicting ELD > 30 Gy. Applying CECT texture analysis may assist in reducing time and cost in patient selection and modifying TARE treatment plans.

Liver Cancer Vascularity Driven by Extracellular Matrix Stiffness: Implications for Imaging Research

BACKGROUND

Extracellular matrix stiffness represents a barrier to effective local and systemic drug delivery. Increasing stiffness disrupts newly formed vessel architecture and integrity, leading to tumor-like vasculature. The resulting vascular phenotypes are manifested through different cross-sectional imaging features. Contrast-enhanced studies can help elucidate the interplay between liver tumor stiffness and different vascular phenotypes.

PURPOSE

This study aims to correlate extracellular matrix stiffness, dynamic contrast-enhanced computed tomography, and dynamic contrast-enhancement ultrasound imaging features of 2 rat hepatocellular carcinoma tumor models.

METHODS AND MATERIALS

Buffalo-McA-RH7777 and Sprague Dawley (SD)-N1S1 tumor models were used to evaluate tumor stiffness by 2-dimensional shear wave elastography, along with tumor perfusion by dynamic contrast-enhanced ultrasonography and contrast-enhanced computed tomography. Atomic force microscopy was used to calculate tumor stiffness at a submicron scale. Computer-aided image analyses were performed to evaluate tumor necrosis, as well as the percentage, distribution, and thickness of CD34+ blood vessels.

RESULTS

Distinct tissue signatures between models were observed according to the distribution of the stiffness values by 2-dimensional shear wave elastography and atomic force microscopy ( P < 0.05). Higher stiffness values were attributed to SD-N1S1 tumors, also associated with a scant microvascular network ( P ≤ 0.001). Opposite results were observed in the Buffalo-McA-RH7777 model, exhibiting lower stiffness values and richer tumor vasculature with predominantly peripheral distribution ( P = 0.03). Consistent with these findings, tumor enhancement was significantly greater in the Buffalo-McA-RH7777 tumor model than in the SD-N1S1 on both dynamic contrast-enhanced ultrasonography and contrast-enhanced computed tomography ( P < 0.005). A statistically significant positive correlation was observed between tumor perfusion on dynamic contrast-enhanced ultrasonography and contrast-enhanced computed tomography in terms of the total area under the curve and % microvessel tumor coverage ( P < 0.05).

CONCLUSIONS

The stiffness signatures translated into different tumor vascular phenotypes. Two-dimensional shear wave elastography and dynamic contrast-enhanced ultrasonography adequately depicted different stromal patterns, which resulted in unique imaging perfusion parameters with significantly greater contrast enhancement observed in softer tumors.

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.

PET Imaging of Hepatocellular Carcinoma Using ZD2-(68Ga-NOTA)

Purpose

We tested a recently developed short peptide radioligand for PET imaging of hepatocellular carcinoma (HCC) by targeting an oncoprotein, extra-domain B fibronectin (EDB-FN) in the tumor microenvironment.

Methods

The radioligand consists of a small linear peptide ZD2 with 68Ga-NOTA chelator, and specifically binds to EDB-FN. PET images were acquired dynamically for 1 hour after intravenously (i.v.) injecting 37 MBq (1.0 mCi) of the radioligand into the woodchuck model of naturally occurring HCC. Woodchuck HCC originated from chronic viral hepatitis infection, which recapitulates the corresponding human primary liver cancer. The animals were euthanized post-imaging for tissue collection and validation.

Results

For ZD2 avid liver tumors, the radioligand accumulation plateaued a few minutes after injection, while the liver background uptake stabilized 20 min post-injection. The status of EDB-FN in woodchuck HCC was confirmed by histology and validated by PCR and western blocking.

Conclusion

We have showed the viability of using the ZD2 short peptide radioligand targeting EDB-FN in liver tumor tissue for PET imaging of HCC, which can potentially impact the clinical care for HCC patients.

Preoperative differentiation of hepatocellular carcinoma with peripheral rim-like enhancement from intrahepatic mass-forming cholangiocarcinoma on contrast-enhanced MRI

Purpose

The present study aimed to determine the reliable imaging features to distinguish atypical hepatocellular carcinoma (HCC) with peripheral rim-like enhancement from intrahepatic mass-forming cholangiocarcinoma (IMCC) on contrast-enhanced magnetic resonance imaging (MRI).

Methods

A total of 168 patients (130 male, 57.10 ± 10.53 years) pathological confirmed HCC or IMCC who underwent contrast-enhanced MRI between July 2019 and February 2022 were retrospectively included. Univariate and multivariate logistic regression analyses were used to determine independent differential factors for distinguishing HCC from IMCC, and the model was established. Bootstrap resampling 1000 times was used to verify the model, which was visualized by nomograms. The predictive performance of the model was evaluated based on discrimination, calibration, and clinical utility.

Results

Radiological capsule (OR 0.024, 95% CI: 0.006, 0.095, P<0.001), heterogeneous signal intensity (SI) on T1WI (OR 0.009, 95%CI: 0.001,0.056, P<0.001) were independent differential factors for predicting HCC over IMCC. A lobulated contour (OR 11.732, 95%CI: 2.928,47.007, P = 0.001), target sign on DP (OR 14.269, 95%CI: 2.849,82.106, P = 0.007), bile duct dilatation (OR 12.856, 95%CI: 2.013, P = 0.001) were independent differential factors for predicting IMCCs over HCCs. The independent differential factors constituted a model to distinguish atypical HCCs and IMCCs. The area under receiver operating characteristic (ROC) curve, sensitivity, and specificity values of the model were 0.964(0.940,0.987), 0.88, and 0.906, indicating that the model had an excellent differential diagnostic performance. The decision curve analysis (DCA) curve showed that the model obtained a better net clinical benefit.

Conclusion

The present study identified reliable imaging features for distinguishing atypical HCCs with peripheral rim-like enhancement from IMCCs on contrast-enhanced MRI. Our findings may help radiologists provide clinicians with more accurate preoperative imaging diagnoses to select appropriate treatment options.

Contrast-enhanced ultrasound for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease

BACKGROUND

Hepatocellular carcinoma occurs mostly in people with chronic liver disease. Worldwide, it ranks sixth in terms of incidence of cancer, and fourth in terms of cancer-related deaths. Contrast-enhanced ultrasound (CEUS) is used as an add-on test to confirm the presence of focal liver lesions suspected as hepatocellular carcinoma after prior diagnostic tests such as abdominal ultrasound or measurement of alpha-foetoprotein, or both. According to guidelines, a single contrast-enhanced imaging investigation, with either computed tomography (CT) or magnetic resonance imaging (MRI), may show the typical hepatocellular carcinoma hallmarks in people with cirrhosis, which will be sufficient to diagnose hepatocellular carcinoma. However, a significant number of hepatocellular carcinomas show atypical imaging features, and therefore, are missed at imaging. Dynamic CEUS images are obtained similarly to CT and MRI images. CEUS differentiates between arterial and portal venous phases, in which sonographic hepatocellular carcinoma hallmarks, such as arterial hyperenhancement and subsequent washout appearance, are investigated. The advantages of CEUS over CT and MRI include real-time imaging, use of contrast agents that do not contain iodine and are not nephrotoxic, and quick image acquisition. Despite the advantages, the use of CEUS in the diagnostic algorithm for HCC remains controversial, with disagreement on relevant guidelines. There is no clear evidence of the benefit of surveillance programmes in terms of overall survival as the conflicting results can be a consequence of an inaccurate detection, ineffective treatment, or both. Therefore, assessing the diagnostic accuracy of CEUS may clarify whether the absence of benefit could be related to underdiagnosis. Furthermore, an assessment of the accuracy of CEUS for the diagnosis of hepatocellular carcinoma is needed for either diagnosing hepatocellular carcinoma or ruling it out in people with chronic liver disease who are not included in surveillance programmes.

OBJECTIVES

1. To assess the diagnostic accuracy of contrast-enhanced ultrasound (CEUS) for the diagnosis of hepatocellular carcinoma of any size and at any stage in adults with chronic liver disease, in a surveillance programme or in a clinical setting. 2. To assess the diagnostic accuracy of CEUS for the diagnosis of resectable hepatocellular carcinoma in people with chronic liver disease and identify potential sources of heterogeneity in the results.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The last date of search was 5 November 2021.

SELECTION CRITERIA

We included studies assessing the diagnostic accuracy of CEUS for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease, with cross-sectional designs, using one of the acceptable reference standards, such as pathology of the explanted liver, and histology of resected or biopsied focal liver lesion with at least a six-month follow-up.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods to screen studies, extract data, and assess the risk of bias and applicability concerns, using the QUADAS-2 checklist. We used the bivariate model and provided estimates of summary sensitivity and specificity. We assessed the certainty of the evidence using GRADE. We presented uncertainty-of-the-accuracy estimates using 95% confidence intervals (CIs).

MAIN RESULTS

We included 23 studies with 6546 participants. Studies were published between 2001 and 2021. We judged all 23 studies at high-risk of bias in at least one domain, and 13/23 studies at high concern for applicability. Most studies used different reference standards to exclude the presence of the target condition. The time interval between the index test and the reference standard was rarely defined. We also had major concerns on their applicability due to the characteristics of the participants. - CEUS for hepatocellular carcinoma of any size and stage: sensitivity 77.8% (95% CI 69.4% to 84.4%) and specificity 93.8% (95% CI 89.1% to 96.6%) (23 studies, 6546 participants; very low-certainty evidence). - CEUS for resectable hepatocellular carcinoma: sensitivity 77.5% (95% CI 62.9% to 87.6%) and specificity 92.7% (95% CI 86.8% to 96.1%) (13 studies, 1257 participants; low-certainty evidence). The observed heterogeneity in the results remains unexplained. The sensitivity analyses, including only studies with clearly prespecified positivity criteria and only studies in which the reference standard results were interpreted with no knowledge of the results about the index test, showed no differences in the results.

AUTHORS' CONCLUSIONS

We found that by using CEUS, as an add-on test following abdominal ultrasound, to diagnose hepatocellular carcinoma of any size and stage, 22% of people with hepatocellular carcinoma would be missed, and 6% of people without hepatocellular carcinoma would unnecessarily undergo further testing or inappropriate treatment. As to resectable hepatocellular carcinoma, we found that 23% of people with resectable hepatocellular carcinoma would incorrectly be unresected, while 8% of people without hepatocellular carcinoma would undergo further inappropriate testing or treatment. The uncertainty resulting from the high risk of bias of the included studies, heterogeneity, and imprecision of the results and concerns on their applicability limit our ability to draw confident conclusions.

Association of dysmorphic intratumoral vessel with high lung shunt fraction in patients with hepatocellular carcinoma

To evaluate the role of dysmorphic intratumoral vessels as imaging marker for the prediction of high lung shunt fraction (LSF) in patients with hepatocellular carcinoma (HCC). This retrospective study included 403 patients with HCC who underwent a planning arteriography for transarterial radioembolization with administration of 99mTc-macroaggregated albumin to calculate LSF. The LSF was measured by using planar body scans. Two radiologists evaluated the pre-treatment contrast-enhanced CT findings, including tumor number, size, margin, distribution, tumor burden, portal and hepatic vein invasion, early hepatic vein enhancement, and dysmorphic intratumoral vessels. The logistic regression analysis was performed to determine significant predictors for high LSF > 20%. Using the identified predictors, diagnostic criteria for high LSF were proposed. Among 403 patients, 52 (13%) patients had high LSF > 20%, and dysmorphic tumor vessels were present in 115 (28.5%) patients. Predictors for LSF > 20% were tumor size > 11 cm, hepatic vein invasion, early hepatic vein enhancement, and dysmorphic intratumoral vessel. If the patient had three or more of the four predictors for LSF > 20% on imaging, the accuracy and specificity for diagnosing LSF > 20% were 88.8% and 96.3% respectively. Dysmorphic intratumoral vessel in HCC is an imaging marker suggesting a high LSF, which may be applicable to treatment modification or patient exclusion for radioembolization with combined interpretation of tumor size and hepatic vein abnormality.

Development and validation of multivariate models integrating preoperative clinicopathological and radiographic findings to predict HER2 status in gastric cancer

The combination of trastuzumab and chemotherapy is recommended as first-line therapy for patients with human epidermal growth factor receptor 2 (HER2) positive advanced gastric cancers (GCs). Successful trastuzumab-induced targeted therapy should be based on the assessment of HER2 overexpression. This study aimed to evaluate the feasibility of multivariate models based on hematological parameters, endoscopic biopsy, and computed tomography (CT) findings for assessing HER2 overexpression in GC. This retrospective study included 183 patients with GC, and they were divided into primary (n = 137) and validation (n = 46) cohorts at a ratio of 3:1. Hematological parameters, endoscopic biopsy, CT morphological characteristics, and CT value-related and texture parameters of all patients were collected and analyzed. The mean corpuscular hemoglobin concentration value, morphological type, 3 CT value-related parameters, and 22 texture parameters in three contrast-enhanced phases differed significantly between the two groups (all p < 0.05). Multivariate models based on the regression analysis and support vector machine algorithm achieved areas under the curve of 0.818 and 0.879 in the primary cohort, respectively. The combination of hematological parameters, CT morphological characteristics, CT value-related and texture parameters could predict HER2 overexpression in GCs with satisfactory diagnostic efficiency. The decision curve analysis confirmed the clinical utility.

Current Imaging Diagnosis of Hepatocellular Carcinoma

Simple Summary

The role of imaging in the management of hepatocellular carcinoma (HCC) has significantly evolved and expanded beyond the plain radiological confirmation of the tumor based on the typical appearance in a multiphase contrast-enhanced CT or MRI examination. The introduction of hepatobiliary contrast agents has enabled the diagnosis of hepatocarcinogenesis at earlier stages, while the application of ultrasound contrast agents has drastically upgraded the role of ultrasound in the diagnostic algorithms. Newer quantitative techniques assessing blood perfusion on CT and MRI not only allow earlier diagnosis and confident differentiation from other lesions, but they also provide biomarkers for the evaluation of treatment response. As distinct HCC subtypes are identified, their correlation with specific imaging features holds great promise for estimating tumor aggressiveness and prognosis. This review presents the current role of imaging and underlines its critical role in the successful management of patients with HCC.

Abstract

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer related death worldwide. Radiology has traditionally played a central role in HCC management, ranging from screening of high-risk patients to non-invasive diagnosis, as well as the evaluation of treatment response and post-treatment follow-up. From liver ultrasonography with or without contrast to dynamic multiple phased CT and dynamic MRI with diffusion protocols, great progress has been achieved in the last decade. Throughout the last few years, pathological, biological, genetic, and immune-chemical analyses have revealed several tumoral subtypes with diverse biological behavior, highlighting the need for the re-evaluation of established radiological methods. Considering these changes, novel methods that provide functional and quantitative parameters in addition to morphological information are increasingly incorporated into modern diagnostic protocols for HCC. In this way, differential diagnosis became even more challenging throughout the last few years. Use of liver specific contrast agents, as well as CT/MRI perfusion techniques, seem to not only allow earlier detection and more accurate characterization of HCC lesions, but also make it possible to predict response to treatment and survival. Nevertheless, several limitations and technical considerations still exist. This review will describe and discuss all these imaging modalities and their advances in the imaging of HCC lesions in cirrhotic and non-cirrhotic livers. Sensitivity and specificity rates, method limitations, and technical considerations will be discussed.

The Prognostic Value of Baseline Clinical and Radiologic Imaging Features in Patients with Unresectable Hepatocellular Carcinoma Treated with Atezolizumab Plus Bevacizumab

Purpose

To identify prognostic clinical and radiologic features in patients with unresectable hepatocellular carcinoma (HCC) treated with atezolizumab plus bevacizumab.

Patients and Methods

Clinical and imaging records of patients with unresectable HCC were retrospectively reviewed, and baseline features were recorded. Patients’ records and imaging studies were used to determine the patients’ overall survival (OS) and progression-free survival (PFS). Univariate and multivariate analyses were performed to determine prognostic features. Subanalyses of treatment-naïve patients (who never received local or systemic therapy) and previously treated patients were also performed.

Results

Fifty-five patients were included in the final analysis, 23 (41.8%) of whom were treatment naïve. The median PFS and OS for the entire cohort were 3.0 months and 7.9 months. The 3-, 6- and 12-month OS rates were 85.5%, 79.8% and 45.7%, respectively. The 3-, 6- and 12-month PFS rates were 50.1%, 41.2% and 20.1%, respectively. On multivariate analysis, independent prognostic features for poor PFS of the entire cohort were pleural effusions (p = 0.047, HR: 6.3; CI: 1.03–38.90) and hepatic vein tumor thrombus (p = 0.005; HR: 23.37; CI: 2.63–207.67); independent prognostic features for poor OS were ascites (p = 0.008; HR: 37.37; CI: 2.53–467.64), pleural effusion (p = 0.003; HR: 110.17; CI: 5.00–2426.54), and low (<40HU) pre-contrast attenuation on CT images (p = 0.007; HR: 0.09; CI: 0.02–0.53). On subanalysis of treatment-naïve patients, the median OS and PFS were 7.4 months and 2.8 months, respectively. The 3-, 6- and 12-month PFS rates were 43.5%, 38.6% and 24.8%, respectively. Pleural effusion was the only independent poor prognostic feature (p = 0.036; HR: 206.34; CI: 1.41–30,167.58).

Conclusion

Independent prognostic features for survival outcomes include the presence of ascites, pleural effusions, hepatic vein tumor thrombus, and HCC with low attenuation (<40 HU) on unenhanced CT images. Although several biochemical variables were significant on univariate analysis, none were independent predictors of OS or PFS.

Atypical Manifestation of Primary Hepatocellular Carcinoma and Hepatic Malignancy Mimicking Lesions

Hepatocellular carcinoma (HCC) can be diagnosed noninvasively on multiphasic CT and MRI based on its distinctive imaging findings. These features include arterial phase hyperenhancement and washout on portal or delayed phase images. However, radiologists face significant diagnostic challenges because some HCCs exhibit atypical imaging characteristics. In addition to many HCC-mimicking lesions, such as arterioportal shunts, combined HCC-cholangiocarcinoma, intrahepatic cholangiocarcinoma, and hemangioma present a challenge for radiologists in actual clinical practice. The ability to distinguish HCCs from mimickers on initial imaging examinations is crucial for appropriate management and treatment decisions. Therefore, this pictorial review presents the imaging findings of atypical HCCs and HCCs mimicking malignant and benign lesions and discusses important clues that may help narrow down the differential diagnosis.

Preoperative gadoxetic acid-enhanced MRI predicts aggressive pathological features in LI-RADS category 5 hepatocellular carcinoma

AIM

To investigate whether Liver Imaging Reporting and Data System (LI-RADS) imaging features and non-LI-RADS imaging features can predict aggressive pathological features in adult patients with hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

From February 2018 to September 2021, 236 adult patients with cirrhosis or hepatitis B virus infection in which liver cancer was suspected underwent MRI within 1 month before surgery. Significant MRI findings and alpha-fetoprotein (AFP) level predicted high-grade HCC and microvascular invasion (MVI) by univariate and multivariate logistic regression models.

RESULTS

The study included 112 patients with histopathologically confirmed liver cancer (≤5 cm), 35 of whom (31.3%) high-grade HCC and 42 of 112 (37.5%) patients had MVI. Mosaic architecture (odds ratio [OR] = 6.031; 95% confidence interval [CI]: 1.366, 26.626; p=0.018), coronal enhancement (OR=5.878; 95% CI: 1.471, 23.489; p=0.012), and intratumoural vessels (OR=5.278; 95% CI: 1.325, 21.020; p=0.018) were significant independent predictors of high-grade HCC. A non-smooth tumour margin (OR=10.237; 95% CI: 1.547, 67.760; p=0.016), coronal enhancement (OR=3.800; 95% CI: 1.152, 12.531; p=0.028), and peritumoural hypointensity on the hepatobiliary phase (HBP; OR=10.322; 95% CI: 2.733, 38.986; p=0.001) were significant independent predictors of MVI.

CONCLUSION

In high-risk adult patients with single LR-5 HCC (≤5 cm), mosaic architecture, coronal enhancement, and intratumoural vessels are independent predictors of high-grade HCC. Non-smooth tumour margin, coronal enhancement, and peritumoural hypointensity on HBP independently predicted MVI.

Magnetic resonance imaging for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease

BACKGROUND

Hepatocellular carcinoma occurs mostly in people with chronic liver disease and ranks sixth in terms of global incidence of cancer, and third in terms of cancer deaths. In clinical practice, magnetic resonance imaging (MRI) is used as a second-line diagnostic imaging modality to confirm the presence of focal liver lesions suspected as hepatocellular carcinoma on prior diagnostic test such as abdominal ultrasound or alpha-fetoprotein, or both, either in surveillance programmes or in clinical settings. According to current guidelines, a single contrast-enhanced imaging study (computed tomography (CT) or MRI) showing typical hallmarks of hepatocellular carcinoma in people with cirrhosis is considered valid to diagnose hepatocellular carcinoma. The detection of hepatocellular carcinoma amenable to surgical resection could improve the prognosis. However, a significant number of hepatocellular carcinomas do not show typical hallmarks on imaging modalities, and hepatocellular carcinoma may, therefore, be missed. There is no clear evidence of the benefit of surveillance programmes in terms of overall survival: the conflicting results can be a consequence of inaccurate detection, ineffective treatment, or both. Assessing the diagnostic accuracy of MRI may clarify whether the absence of benefit could be related to underdiagnosis. Furthermore, an assessment of the accuracy of MRI in people with chronic liver disease who are not included in surveillance programmes is needed for either ruling out or diagnosing hepatocellular carcinoma.

OBJECTIVES

Primary: to assess the diagnostic accuracy of MRI for the diagnosis of hepatocellular carcinoma of any size and at any stage in adults with chronic liver disease. Secondary: to assess the diagnostic accuracy of MRI for the diagnosis of resectable hepatocellular carcinoma in adults with chronic liver disease, and to identify potential sources of heterogeneity in the results.

SEARCH METHODS

We searched the Cochrane Hepato-Biliary Group Controlled Trials Register, the Cochrane Hepato-Biliary Group Diagnostic Test of Accuracy Studies Register, the Cochrane Library, MEDLINE, Embase, and three other databases to 9 November 2021. We manually searched articles retrieved, contacted experts, handsearched abstract books from meetings held during the last 10 years, and searched for literature in OpenGrey (9 November 2021). Further information was requested by e-mails, but no additional information was provided. No data was obtained through correspondence with investigators. We applied no language or document-type restrictions.

SELECTION CRITERIA

Studies assessing the diagnostic accuracy of MRI for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease, with cross-sectional designs, using one of the acceptable reference standards, such as pathology of the explanted liver and histology of resected or biopsied focal liver lesion with at least a six-month follow-up.

DATA COLLECTION AND ANALYSIS

At least two review authors independently screened studies, extracted data, and assessed the risk of bias and applicability concerns, using the QUADAS-2 checklist. We presented the results of sensitivity and specificity, using paired forest plots, and we tabulated the results. We used a hierarchical meta-analysis model where appropriate. We presented uncertainty of the accuracy estimates using 95% confidence intervals (CIs). We double-checked all data extractions and analyses.

MAIN RESULTS

We included 34 studies, with 4841 participants. We judged all studies to be at high risk of bias in at least one domain because most studies used different reference standards, often inappropriate to exclude the presence of the target condition, and the time interval between the index test and the reference standard was rarely defined. Regarding applicability, we judged 15% (5/34) of studies to be at low concern and 85% (29/34) of studies to be at high concern mostly owing to characteristics of the participants, most of whom were on waiting lists for orthotopic liver transplantation, and due to pathology of the explanted liver being the only reference standard. MRI for hepatocellular carcinoma of any size and stage: sensitivity 84.4% (95% CI 80.1% to 87.9%) and specificity 93.8% (95% CI 90.1% to 96.1%) (34 studies, 4841 participants; low-certainty evidence). MRI for resectable hepatocellular carcinoma: sensitivity 84.3% (95% CI 77.6% to 89.3%) and specificity 92.9% (95% CI 88.3% to 95.9%) (16 studies, 2150 participants; low-certainty evidence). The observed heterogeneity in the results remains mostly unexplained. The sensitivity analyses, which included only studies with clearly prespecified positivity criteria and only studies in which the reference standard results were interpreted without knowledge of the results of the index test, showed no variation in the results.

AUTHORS' CONCLUSIONS

We found that using MRI as a second-line imaging modality to diagnose hepatocellular carcinoma of any size and stage, 16% of people with hepatocellular carcinoma would be missed, and 6% of people without hepatocellular carcinoma would be unnecessarily treated. For resectable hepatocellular carcinoma, we found that 16% of people with resectable hepatocellular carcinoma would improperly not be resected, while 7% of people without hepatocellular carcinoma would undergo inappropriate surgery. The uncertainty resulting from the high risk of bias in the included studies and concerns regarding their applicability limit our ability to confidently draw conclusions based on our results.

Imaging of Tumor-Associated Vascular Prostate-Specific Membrane Antigen in Woodchuck Model of Hepatocellular Carcinoma

BACKGROUND AND AIMS

Radiolabeled short peptide ligands targeting prostate-specific membrane antigen (PSMA) were developed initially for imaging and treatment of prostate cancers. While many nonprostate solid tumors including hepatocellular carcinoma (HCC) express little PSMA, their neovasculature expresses a high level of PSMA, which is avid for Gallium-68-labeled PSMA-targeting radio-ligand (⁶⁸Ga-PSMA-11) for positron emission tomography (PET). However, the lack of a spontaneous animal model of tumor-associated vascular PSMA overexpression has hindered the development and assessment of PSMA-targeting radioligands for imaging and therapy of the nonprostatic cancers. We identified detectable indigenous PSMA expression on tumor neovascular endothelia in a naturally occurring woodchuck model of HCC.

METHODS

Molecular docking was performed with 3 bait PSMA ligands and compared between human and woodchuck PSMA. Initially, PET images were acquired dynamically after intravenously injecting 37 MBq (1.0 mCi) of ⁶⁸Ga-PSMA-11 into woodchuck models of HCC. Subsequently, 10-minute static PET scans were conducted for other animals 1-hour after injection due to HCC and liver background uptake stabilization at 30-45 minutes after injection. Liver tissue samples were harvested after imaging, fresh-frozen for quantitative reverse transcription polymerase chain reaction and western blot for validation, or fixed for histology for correlation.

RESULTS

Our preclinical studies confirmed the initial clinical findings of ⁶⁸Ga-PSMA-11 uptake in HCC. The agents (ligands and antibodies) developed against human PSMA were found to be reactive against the woodchuck PSMA.

CONCLUSION

This animal model offers a unique opportunity for investigating the biogenesis of tumor-associated vascular PSMA, its functional role(s), and potentials for future treatment strategies targeting tumor vascular PSMA using already developed PSMA-targeting agents.

Imaging mimickers of cholangiocarcinoma: a pictorial review

Cholangiocarcinoma (CCA) is the second most common primary hepatobiliary malignancy and presents as three separate morphological subtypes; namely mass-forming, periductal-infiltrating, and intraductal-growing patterns. Each of these subtypes have distinct imaging characteristics, as well as a variety of benign and malignant mimics, making accurate diagnosis of CCA on imaging challenging. Whilst histopathological examination is required to arrive at a definitive diagnosis, it is still important for radiologists to be cognizant of these entities and provide reasonable differential diagnoses, as these potentially have a large impact on patient management. This pictorial essay illustrates the three morphological subtypes of CCA, as well as some important mimics for each subtype, that are encountered in clinical practice.

Inter-observer agreement using the LI-RADS version 2018 CT treatment response algorithm in patients with hepatocellular carcinoma treated with conventional transarterial chemoembolization

Aim

To determine inter-reader agreement in categorization of imaging features using the Liver Imaging Reporting and Data System (LI-RADS) treatment response (LR-TR) algorithm in patients with hepatocellular carcinoma (HCC) treated with conventional transarterial chemoembolization (cTACE).

Methods

Two radiologists used the LR-TR algorithm to assess 112 computed tomography (CT) examinations of 102 patients treated with cTACE. The inter-observer agreement in categorization of LR-TR features was assessed using kappa (κ) statistics.

Results

There was substantial inter-observer agreement between the two reviewers using the LR-TR algorithm (κ = 0.70; 95% CI 0.58–0.81). The two reviewers categorized tumors as non-viable in 37 (33.0%) and 39 (34.8%) of 112 examinations, viable in 58 (51.8%) and 62 (55.4%) examinations, and equivocal in 18 (16.1%) and 11 (9.8%) examinations, respectively. There was almost perfect inter-observer agreement for the LR-TR non-viable category (κ = 0.80; 95% CI 0.68–0.92), substantial agreement for the viable category (κ = 0.78 95% CI 0.67–0.90), and fair agreement for the equivocal category (κ = 0.25; 95% CI 0.02–0.49).

Conclusion

The LR-TR algorithm conveys high degrees of inter-observer agreement for the assessment of CT imaging features in the viable and non-viable categories. Further refinement of indeterminate features may be necessary to improve the correct categorization of equivocal lesions.

Graphic abstract

Association between contrast enhancement on contrast-enhanced CT and lenvatinib effectiveness in hepatocellular carcinoma

The aim of the present study was to investigate whether the degree of contrast enhancement on contrast-enhanced (CE)-CT can predict the prognosis of patients with hepatocellular carcinoma (HCC) treated with lenvatinib (LEN). A total of 67 consecutive patients with LEN-treated HCC were retrospectively analysed. In the pretreatment CE-CT, the CT values were measured using a region of interest within the main nodule and the liver parenchyma in the arterial phase, and the macroscopic degree of contrast enhancement of the tumour area was quantified by calculating the enhancement ratio (ER) of the liver parenchyma. The associations of pretreatment ER with progression-free survival (PFS) and overall survival (OS) were then investigated. There were 20, 27 and 20 patients in the ER ≥1.5, 1.0≤ ER <1.5 and ER <1.0 groups, respectively. There was no significant difference in the PFS and OS among the three ER groups (PFS, P=0.63; OS, P=0.455). The ER <1.0 group had significantly more patients with larger tumour diameters, Barcelona Clinic Liver Cancer (BCLC) stage C with extrahepatic metastases, and higher des-γ-carboxy prothrombin values compared with the ER ≥1.0 group, suggesting that ER <1.0 reflected more aggressive types of HCC. The multivariate analysis revealed tumour size and α-fetoprotein as independent predictors of shorter PFS. Albumin-bilirubin grade 2 and BCLC stage C were significant predictors of poor OS, whereas the ER was confirmed as a non-significant predictor of both PFS and OS. Only non-alternating LEN and transarterial therapy (AT) were identified as independent predictors of unfavourable OS in patients with BCLC stage B HCC. Therefore, LEN has a strong therapeutic effect on HCC, regardless of the degree of contrast enhancement. Furthermore, AT may prolong the OS of LEN-treated patients with BCLC stage B HCC, regardless of tumour vascularity.

Liver MRI and clinical findings to predict response after drug eluting bead transarterial chemoembolization in hepatocellular carcinoma

To identify the gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) and laboratory findings that enable prediction of treatment response and disease-free survival (DFS) after the first session of drug eluting bead transarterial chemoembolization (DEB-TACE) in patients with hepatocellular carcinoma (HCC). A total of 55 patients who underwent GA-enhanced MRI and DEB-TACE from January 2014 to December 2018 were included. All MRI features were reviewed by two radiologists. Treatment response was evaluated according to the modified Response Evaluation Criteria in Solid Tumors. Univariate and multivariate logistic regression analyses were used to determine predictive factors of treatment response and DFS, respectively. A total of 27 patients (49.1%) achieved complete response (CR) after one session of treatment. There were no significant differences between the two groups in terms of clinical and laboratory characteristics. Heterogeneous signal intensity in the hepatobiliary phase (HBP) was the only independent predictor of non-CR (odds ratio, 4.807; p = 0.048). Recurrent HCC was detected in 19 patients (70.4%) after CR. In the multivariate analysis, elevated serum alpha-fetoprotein (AFP) level (≥ 30 ng/mL) was the only significant parameter associated with DFS (hazard ratio, 2.916; p = 0.040). This preliminary study demonstrated that heterogeneous signal intensity in the HBP and high serum AFP were useful predictive factors for poor treatment response and short DFS after DEB-TACE, respectively.

Computed tomography for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease

BACKGROUND

Hepatocellular carcinoma occurs mostly in people with chronic liver disease and ranks sixth in terms of global incidence of cancer, and fourth in terms of cancer deaths. In clinical practice, computed tomography (CT) is used as a second-line diagnostic imaging modality to confirm the presence of focal liver lesions suspected as hepatocellular carcinoma on prior diagnostic test such as abdominal ultrasound or alpha-foetoprotein, or both, either in surveillance programmes or in clinical settings. According to current guidelines, a single contrast-enhanced imaging study CT or magnetic resonance imaging (MRI) showing typical hallmarks of hepatocellular carcinoma in people with cirrhosis is valid to diagnose hepatocellular carcinoma. However, a significant number of hepatocellular carcinomas do not show typical hallmarks on imaging modalities, and hepatocellular carcinoma is, therefore, missed. There is no clear evidence of the benefit of surveillance programmes in terms of overall survival: the conflicting results can be a consequence of inaccurate detection, ineffective treatment, or both. Assessing the diagnostic accuracy of CT may clarify whether the absence of benefit could be related to underdiagnosis. Furthermore, an assessment of the accuracy of CT in people with chronic liver disease, who are not included in surveillance programmes is needed for either ruling out or diagnosing hepatocellular carcinoma.

OBJECTIVES

Primary: to assess the diagnostic accuracy of multidetector, multiphasic contrast-enhanced CT for the diagnosis of hepatocellular carcinoma of any size and at any stage in adults with chronic liver disease, either in a surveillance programme or in a clinical setting. Secondary: to assess the diagnostic accuracy of CT for the diagnosis of resectable hepatocellular carcinoma in adults with chronic liver disease.

SEARCH METHODS

We searched the Cochrane Hepato-Biliary Trials Register, Cochrane Hepato-Biliary Diagnostic-Test-Accuracy Studies Register, the Cochrane Library, MEDLINE, Embase, LILACS, Science Citation Index Expanded, and Conference Proceedings Citation Index - Science until 4 May 2021. We applied no language or document-type restrictions.

SELECTION CRITERIA

Studies assessing the diagnostic accuracy of CT for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease, with cross-sectional designs, using one of the acceptable reference standards, such as pathology of the explanted liver and histology of resected or biopsied focal liver lesion with at least a six-month follow-up.

DATA COLLECTION AND ANALYSIS

At least two review authors independently screened studies, extracted data, and assessed the risk of bias and applicability concerns, using the QUADAS-2 checklist. We presented the results of sensitivity and specificity, using paired forest plots, and tabulated the results. We used a hierarchical meta-analysis model where appropriate. We presented uncertainty of the accuracy estimates using 95% confidence intervals (CIs). We double-checked all data extractions and analyses.

MAIN RESULTS

We included 21 studies, with a total of 3101 participants. We judged all studies to be at high risk of bias in at least one domain because most studies used different reference standards, often inappropriate to exclude the presence of the target condition, and the time-interval between the index test and the reference standard was rarely defined. Regarding applicability in the patient selection domain, we judged 14% (3/21) of studies to be at low concern and 86% (18/21) of studies to be at high concern owing to characteristics of the participants who were on waiting lists for orthotopic liver transplantation. CT for hepatocellular carcinoma of any size and stage: sensitivity 77.5% (95% CI 70.9% to 82.9%) and specificity 91.3% (95% CI 86.5% to 94.5%) (21 studies, 3101 participants; low-certainty evidence). CT for resectable hepatocellular carcinoma: sensitivity 71.4% (95% CI 60.3% to 80.4%) and specificity 92.0% (95% CI 86.3% to 95.5%) (10 studies, 1854 participants; low-certainty evidence). In the three studies at low concern for applicability (861 participants), we found sensitivity 76.9% (95% CI 50.8% to 91.5%) and specificity 89.2% (95% CI 57.0% to 98.1%). The observed heterogeneity in the results remains mostly unexplained. The sensitivity analyses, which included only studies with clearly prespecified positivity criteria and only studies in which the reference standard results were interpreted without knowledge of the results of the index test, showed no variation in the results.

AUTHORS' CONCLUSIONS

In the clinical pathway for the diagnosis of hepatocellular carcinoma in adults with chronic liver disease, CT has roles as a confirmatory test for hepatocellular carcinoma lesions, and for staging assessment. We found that using CT in detecting hepatocellular carcinoma of any size and stage, 22.5% of people with hepatocellular carcinoma would be missed, and 8.7% of people without hepatocellular carcinoma would be unnecessarily treated. For resectable hepatocellular carcinoma, we found that 28.6% of people with resectable hepatocellular carcinoma would improperly not be resected, while 8% of people without hepatocellular carcinoma would undergo inappropriate surgery. The uncertainty resulting from the high risk of bias in the included studies and concerns regarding their applicability limit our ability to confidently draw conclusions based on our results.

Value of precontrast and portal venous phases for evaluating atypical hepatocellular carcinoma mimicking arterioportal shunt

PURPOSE

To evaluate the value of precontrast phase (PP) and portal venous phase (PVP) for differentiation of small hypervascular hepatocellular carcinomas (HCCs) without delayed washout from arterioportal (AP) shunts in high-risk patients of HCC.

METHODS

A total of 122 lesions (73 AP shunts and 49 HCCs) detected on quadriphasic CT in 101 patients with chronic liver disease were analyzed. All lesions (≤2 cm) showed arterial enhancement and isodensity on delayed phase (DP) with exclusion of typical features of AP shunts. Lesion morphologic features (size, location, shape, margin) on biphasic CT (arterial phase and DP), Alpha-fetoprotein (AFP) values and coexistent HCC were evaluated. The qualitative and quantitative analyses of lesion attenuation on quadriphasic CT were performed. Diagnostic performances for prediction of AP shunts over HCC were compared among the biphasic CT, triphasic CT (adding PP or PVP) and quadriphasic CT.

RESULTS

In multivariate analysis, the presence of concomitant HCC (p = 0.0005, odds ratio [OR] = 0.11), visual hypodensity on PP (p = 0.0004, OR = 17.72) and visual hyperdensity on PVP (p = 0.0003, OR = 0.051) were independent predictors for HCCs rather than AP shunts. Additional review of PP and PVP revealed significantly improved diagnostic performance yielding the highest diagnostic performance.

CONCLUSIONS

Hypodensity on PP and hyperdensity on PVP are significant predictive features in differentiating atypical small hypervascular HCC from AP shunts in patients with high-risk of HCC. Careful evaluation of the PP and PVP may reduce underdiagnosis and lead to earlier diagnosis of atypical small HCCs.

Clinical application of mask region-based convolutional neural network for the automatic detection and segmentation of abnormal liver density based on hepatocellular carcinoma computed tomography datasets

The aim of the study was to use a previously proposed mask region–based convolutional neural network (Mask R-CNN) for automatic abnormal liver density detection and segmentation based on hepatocellular carcinoma (HCC) computed tomography (CT) datasets from a radiological perspective. Training and testing datasets were acquired retrospectively from two hospitals of Taiwan. The training dataset contained 10,130 images of liver tumor densities of 11,258 regions of interest (ROIs). The positive testing dataset contained 1,833 images of liver tumor densities with 1,874 ROIs, and negative testing data comprised 20,283 images without abnormal densities in liver parenchyma. The Mask R-CNN was used to generate a medical model, and areas under the curve, true positive rates, false positive rates, and Dice coefficients were evaluated. For abnormal liver CT density detection, in each image, we identified the mean area under the curve, true positive rate, and false positive rate, which were 0.9490, 91.99%, and 13.68%, respectively. For segmentation ability, the highest mean Dice coefficient obtained was 0.8041. This study trained a Mask R-CNN on various HCC images to construct a medical model that serves as an auxiliary tool for alerting radiologists to abnormal CT density in liver scans; this model can simultaneously detect liver lesions and perform automatic instance segmentation.

Hepatocellular Carcinoma with Macroscopic Fat Metamorphosis: A Case Series

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related deaths in the world, with hepatitis B and C as its main causes. HCC can have fat metamorphosis which leads to a better prognosis, though this is more commonly found in lesions smaller than 3 cm in diameter, and usually contains intravoxel fat. In this case series, we present three cases of HCC with macroscopic fat metamorphosis as examined using CT scan and MRI. Macroscopic fat is seen using CT as a hypodense mass with attenuation of −10 to −100 HU, or MRI using fat-saturation technique. Intravoxel fat can be seen on MRI using fat saturation chemical shift technique, appearing as signal loss during opposed phase and increased signal during in-phase. The differential diagnoses of HCC with fat metamorphosis are angiomyolipoma, hepatic adenoma, nodular steatosis, focal nodular hyperplasia, dysplastic nodule, liposarcoma, and hepatic metastasis. Enhancement patterns of the fat and non-fat component; intra-tumoral fat distribution; the presence of cirrhosis; the presence of atoll sign; and history of viral hepatitis are useful clues for differentiation of HCC with other differential diagnoses.

Differentiation of Hepatocellular Carcinoma from Hepatic Hemangioma and Focal Nodular Hyperplasia using Computed Tomographic Spectral Imaging

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. This study was designed to investigate the value of computed tomography (CT) spectral imaging in differentiating HCC from hepatic hemangioma (HH) and focal nodular hyperplasia (FNH).

METHODS

This was a retrospective study of 51 patients who underwent spectral multiple-phase CT at 40-140 keV during the arterial phase (AP) and portal venous phase (PP). Slopes of the spectral curves, iodine density, water density derived from iodine- and water-based material decomposition images, iodine uptake ratio (IUR), normalized iodine concentration, and the ratio of iodine concentration in liver lesions between AP and PP were measured or calculated.

RESULTS

As energy level decreased, the CT values of HCC (n=31), HH (n=17), and FNH (n=7) increased in both AP and PP. There were significant differences in IUR in the AP, IUR in the PP, normalized iodine concentration in the AP, slope in the AP, and slope in the PP among HCC, HH, and FNH. The CT values in AP, IUR in the AP and PP, normalized iodine concentration in the AP, slope in the AP and PP had high sensitivity and specificity in differentiating HH and HCC from FNH. Quantitative CT spectral data had higher sensitivity and specificity than conventional qualitative CT image analysis during the combined phases.

CONCLUSIONS

Mean CT values at low energy (40-90 keV) and quantitative analysis of CT spectral data (IUR in the AP) could be helpful in the differentiation of HCC, HH, and FNH.

A radiomics nomogram for predicting transcatheter arterial chemoembolization refractoriness of hepatocellular carcinoma without extrahepatic metastasis or macrovascular invasion

OBJECTIVE

A radiomics nomogram for pretreatment prediction of TACE refractoriness was developed and validated for hepatocellular carcinoma (HCC) without extrahepatic metastasis or macrovascular invasion.

MATERIALS AND METHODS

This study included 80 patients with HCC without extrahepatic metastasis or macrovascular involvement treated with TACE between July 2016 and November 2018. The datasets were divided into a training set (80%) and a test set (20%) for feature selection and tenfold cross-validation. Forty radiomic features were extracted from arterial-phase computed tomography (CT) using the Local Image Features Extraction software. The Lasso regression model was used for radiomics signature selection. The Lasso regression model was used for radiomics signature selection and the selected signatures were validated using the Mann-Whitney U-test. The radiomics nomogram was developed based on a multivariate logistic regression model incorporating the Rad-score, CT imaging factors, and clinical factors, and it was validated.

RESULTS

The Rad-score, which consists of the Gray-Level Zone Length Matrix (GLZLM)-Long-Zone Low Gray-Level Emphasis (LZLGE) and GLZLM-Gray-Level Non-Uniformity (GLNU), T-stage, log α-fetoprotein (AFP), and bilobar distribution were significantly associated with TACE refractoriness (p < 0.05). Predictors in the radiomics nomogram were the Rad-score and T-stage (Rad-score + T-stage), Rad-score and bilobar distribution (Rad-score + bilobar distribution), or Rad-score and logAFP (Rad-score + logAFP). The multivariate logistic regression model showed a good predictive performance (Rad-score + T-stage, AUC, 0.95; Rad-score + bilobar distribution, AUC 0.91; and Rad-score + logAFP, AUC, 0.91).

CONCLUSION

The radiomics nomogram could be used for the pretreatment prediction of TACE refractoriness.

Assessment of factors affecting washout appearance of hepatocellular carcinoma on CT

OBJECTIVES

To identify independent imaging and histopathologic factors that affect washout appearance of hepatocellular carcinoma (HCC) in CT images.

METHODS

This retrospective study included 264 patients who had undergone surgical resection for treatment-naïve single HCC between January 2014 and December 2015 and had available preoperative multiphasic CT images. Two reviewers evaluated the CT imaging features of HCC using LI-RADS v2018. The "washout" was visually assessed in portal venous or equilibrium phases. Depending on the presence of washout appearance of HCC, all patients were divided into "washout" (n = 228) and "no washout" (n = 36) groups. Multivariable logistic regression analysis was used to identify factors associated with the absence of washout appearance of HCC.

RESULTS

A total of 264 HCCs (median size, 2.6 cm) were analyzed. Histologically proven hepatic steatosis (macrovesicular steatosis ≥ 5%) (odds ratio [OR], 2.65; 95% confidence interval [CI], 1.05-6.74; p = 0.040), tumor capsule on histopathology (OR, 0.17; 95% CI, 0.06-0.50; p = 0.001), and mosaic appearance on CT image (OR, 0.34; 95% CI, 0.14-0.85; p = 0.021) were independent factors associated with the absence of washout appearance of HCC. In 189 patients with available unenhanced CT images, CT-diagnosed hepatic steatosis was also an independent factor for the absence of washout appearance of HCC (OR, 9.26; 95% CI, 3.06-28.02; p < 0.001).

CONCLUSIONS

Washout appearance of HCC in CT images could be obscured in both histologically proven hepatic steatosis and CT-diagnosed hepatic steatosis, and could be enhanced with tumor capsule on histopathology and mosaic appearance on CT image.

KEY POINTS

• Hepatic steatosis is an independent factor related to the absence of washout appearance of hepatocellular carcinoma in CT images, in both histologically proven hepatic steatosis and CT-diagnosed hepatic steatosis. • Both histologically proven hepatic steatosis and CT-diagnosed hepatic steatosis have higher odds of absence of washout appearance of hepatocellular carcinoma compared to non-steatotic liver. • Tumor capsule on histopathology and mosaic appearance on CT image are independent factors that enhance the probability that washout appearance of hepatocellular carcinoma is visible.

Convolutional neural network for classifying primary liver cancer based on triple-phase CT and tumor marker information: a pilot study

PURPOSE

To develop convolutional neural network (CNN) models for differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) and predicting histopathological grade of HCC.

MATERIALS AND METHODS

Preoperative computed tomography and tumor marker information of 617 primary liver cancer patients were retrospectively collected to develop CNN models categorizing tumors into three categories: moderately differentiated HCC (mHCC), poorly differentiated HCC (pHCC), and ICC, where the histopathological diagnoses were considered as ground truths. The models processed manually cropped tumor with and without tumor marker information (two-input and one-input models, respectively). Overall accuracy was assessed using a held-out dataset (10%). Area under the curve, sensitivity, and specificity for differentiating ICC from HCCs (mHCC + pHCC), and pHCC from mHCC were also evaluated. We assessed two radiologists' performance without tumor marker information as references (overall accuracy, sensitivity, and specificity). The two-input model was compared with the one-input model and radiologists using permutation tests.

RESULTS

The overall accuracy was 0.61, 0.60, 0.55, 0.53 for the two-input model, one-input model, radiologist 1, and radiologist 2, respectively. For differentiating pHCC from mHCC, the two-input model showed significantly higher specificity than radiologist 1 (0.68 [95% confidence interval: 0.50-0.83] vs 0.45 [95% confidence interval: 0.27-0.63]; p = 0.04).

CONCLUSION

Our CNN model with tumor marker information showed feasibility and potential for three-class classification within primary liver cancer.

A Pre-TACE Radiomics Model to Predict HCC Progression and Recurrence in Liver Transplantation. A Pilot Study on a Novel Biomarker

BACKGROUND

Despite Trans-Arterial Chemo Embolization (TACE) for hepatocellular carcinoma (HCC), a significant number of patients will develop progression on the liver transplant (LT) waiting list or disease recurrence post-LT. We sought to evaluate the feasibility of a pre-TACE radiomic model, an imaging-based tool to predict these adverse outcomes.

METHODS

We analyzed the pre-TACE computed tomography images of patients waiting for a LT. The primary endpoint was a combined event that included waitlist dropout for tumor progression or tumor recurrence post-LT. The radiomic features were extracted from the largest HCC volume from the arterial and portal venous phase. A third set of features was created, combining the features from these 2 contrast phases. We applied a LASSO feature selection method and a support vector machine classifier. Three prognostic models were built using each feature set. The models' performance was compared using 5-fold cross-validated Area Under the Receiver Operating Characteristic curves (AUC).

RESULTS

88 patients were included, of whom 33 experienced the combined event (37.5%). The median time to dropout was 5.6 months (IQR:3.6-9.3), and the median time for post-LT recurrence was 19.2 months (IQR:6.1-34.0). Twenty-four patients (27.3%) dropped out, and 64 (72.7%) patients were transplanted. Of these, 14 (21.9%) had recurrence post-LT. Model performance yielded a mean AUC of 0.70(±0.07), 0.87(±0.06) and 0.81(±0.06) for the arterial, venous and the combined models, respectively.

CONCLUSION

A pre-TACE radiomics model for HCC patients undergoing LT may be a useful tool for outcome prediction. Further external model validation with a larger sample size is required.

Concomitant hepatic tuberculosis and hepatocellular carcinoma: a case report and review of the literature

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy that is strongly associated with chronic liver disease. Isolated hepatic tuberculosis is an uncommon type of tuberculosis. Concomitant occurrence of both conditions is extremely rare.

CASE PRESENTATION

We report the case of a 47-year-old man who presented with fever and abdominal pain for 3 months prior to presentation. He reported a history of anorexia and significant weight loss. Abdominal examination revealed a tender, enlarged liver. Abdominal computed tomography (CT) demonstrated a solid heterogeneous hepatic mass with peripheral arterial enhancement, but no venous washout, conferring a radiological impression of suspected cholangiocarcinoma. However, a CT-guided biopsy of the lesion resulted in the diagnosis of concomitant HCC and isolated hepatic tuberculosis.

CONCLUSION

A rapid increase in tumor size should draw attention to the possibility of a concomitant infectious process. Clinicians must have a high index of suspicion for tuberculosis, especially in patients from endemic areas, in order to initiate early and proper treatment.

Automated feature quantification of Lipiodol as imaging biomarker to predict therapeutic efficacy of conventional transarterial chemoembolization of liver cancer

Conventional transarterial chemoembolization (cTACE) is a guideline-approved image-guided therapy option for liver cancer using the radiopaque drug-carrier and micro-embolic agent Lipiodol, which has been previously established as an imaging biomarker for tumor response. To establish automated quantitative and pattern-based image analysis techniques of Lipiodol deposition on 24 h post-cTACE CT as biomarker for treatment response. The density of Lipiodol deposits in 65 liver lesions was automatically quantified using Hounsfield Unit thresholds. Lipiodol deposition within the tumor was automatically assessed for patterns including homogeneity, sparsity, rim, and peripheral deposition. Lipiodol deposition was correlated with enhancing tumor volume (ETV) on baseline and follow-up MRI. ETV on baseline MRI strongly correlated with Lipiodol deposition on 24 h CT (p < 0.0001), with 8.22% ± 14.59 more Lipiodol in viable than necrotic tumor areas. On follow-up, tumor regions with Lipiodol showed higher rates of ETV reduction than areas without Lipiodol (p = 0.0475) and increasing densities of Lipiodol enhanced this effect. Also, homogeneous (p = 0.0006), non-sparse (p < 0.0001), rim deposition within sparse tumors (p = 0.045), and peripheral deposition (p < 0.0001) of Lipiodol showed improved response. This technical innovation study showed that an automated threshold-based volumetric feature characterization of Lipiodol deposits is feasible and enables practical use of Lipiodol as imaging biomarker for therapeutic efficacy after cTACE.

Retrospective CT/MRI Texture Analysis of Rapidly Progressive Hepatocellular Carcinoma

Rapidly progressive hepatocellular carcinoma (RPHCC) is a subset of hepatocellular carcinoma that demonstrates accelerated growth, and the radiographic features of RPHCC versus non-RPHCC have not been determined. The purpose of this retrospective study was to use baseline radiologic features and texture analysis for the accurate detection of RPHCC and subsequent improvement of clinical outcomes. We conducted a qualitative visual analysis and texture analysis, which selectively extracted and enhanced imaging features of different sizes and intensity variation including mean gray-level intensity (mean), standard deviation (SD), entropy, mean of the positive pixels (MPP), skewness, and kurtosis at each spatial scaling factor (SSF) value of RPHCC and non-RPHCC tumors in a computed tomography (CT) cohort of n = 11 RPHCC and n = 11 non-RPHCC and a magnetic resonance imaging (MRI) cohort of n = 13 RPHCC and n = 10 non-RPHCC. There was a statistically significant difference across visual CT irregular margins p = 0.030 and CT texture features in SSF between RPHCC and non-RPHCC for SSF-6, coarse-texture scale, mean p = 0.023, SD p = 0.053, MPP p = 0.023. A composite score of mean SSF-6 binarized + SD SSF-6 binarized + MPP SSF-6 binarized + irregular margins was significantly different between RPHCC and non-RPHCC (p = 0.001). A composite score ≥3 identified RPHCC with a sensitivity of 81.8% and specificity of 81.8% (AUC = 0.884, p = 0.002). CT coarse-texture-scale features in combination with visually detected irregular margins were able to statistically differentiate between RPHCC and non-RPHCC. By developing an image-based, non-invasive diagnostic criterion, we created a composite score that can identify RPHCC patients at their early stages when they are still eligible for transplantation, improving the clinical course of patient care.

Intra-individual comparison of dual portal venous phases for non-invasive diagnosis of hepatocellular carcinoma at gadoxetic acid-enhanced liver MRI

OBJECTIVES

To compare the diagnostic performances of first and second portal venous phases (PVP1 and PVP2) in revealing washout and capsule appearance for non-invasive HCC diagnoses in gadoxetic acid-enhanced MRI (Gd-EOB-MRI).

METHODS

This retrospective study included 123 at-risk patients with 160 hepatic observations (HCCs, n = 116; non-HCC malignancies, n = 18; benign, n = 26) showing arterial phase hyper-enhancement (APHE) ≥ 1 cm at Gd-EOB-MRI. The mean time intervals from gadoxetic acid injection to PVP1 and PVP2 acquisitions were 53 ± 2 s and 73 ± 3 s, respectively. After evaluating image findings independently, imaging findings and diagnoses were finalized by a consensus of two radiologists using either PVP1 or PVP2 image sets according to the LI-RADS v2018 or EASL criteria. Sensitivity, specificity, and accuracy were compared.

RESULTS

Among HCCs, more washout and enhancing capsule were observed in PVP2 (83.6% and 27.6%) than in PVP1 (50.9% and 19.8%) (p < 0.001, both). The PVP2 set presented significantly higher sensitivity (83.6% vs. 53.5%, LI-RADS; 82.8% vs. 50.0%, EASL; p < 0.001, both) and accuracy (0.88 vs. 0.73, LI-RADS; 0.88 vs. 0.72, EASL; p < 0.001, both) than the PVP1 set without significant specificity loss (93.2% vs. 93.2%, by LI-RADS or EASL; p = 0.32, both). None of the non-HCC malignancy was non-invasively diagnosed as HCC in both PVP image sets.

CONCLUSION

Late acquisition of PVP detected washout and enhancing capsule of HCC more sensitively than early acquisition, enabling accurate diagnoses of HCC, according to LI-RADS or EASL criteria.

KEY POINTS

• Among HCCs, more washout and enhancing capsules were observed in PVP2 than PVP1, quantitatively and qualitatively. • The portal venous phase acquired at around 70 s after contrast media administration (PVP2) provided significantly higher sensitivity and AUC value than PVP1 by using LI-RADS v2018 or EASL criteria. • More HCCs were categorized as LR-5 in PVP2 than in PVP1 images, and the specificity of PVP2 (93.5%) was comparable with PVP1 (93.5%).

Evaluation of Primary Liver Cancers Using Hepatocyte-Specific Contrast-Enhanced MRI: Pitfalls and Potential Tips

When radiologists interpret hepatic focal lesions seen on dynamic magnetic resonance imaging (MRI) scans, it is important not only to distinguish malignant lesions from benign ones but also to distinguish nonhepatocellular carcinoma (HCC) malignancies from HCCs. In addition, most major guidelines, including those of the American Association for the Study of Liver Disease, European Association for the Study of the Liver, and Korean Liver Cancer Association and National Cancer Center, allow for the noninvasive imaging diagnosis of HCC in at-risk patients. However, ~40% of HCC cases show atypical imaging features mimicking non-HCC malignancies. Furthermore, several benign and malignant lesions, such as flash-filling hemangioma and intrahepatic mass-forming cholangiocarcinoma, frequently look like HCC. In contrast, although multiparametric MRI options, including hepatobiliary phase and diffusion-weighted imaging, provide useful information that could help address these challenges, there remain several unresolved issues with regard to the noninvasive diagnostic criteria characterizing HCC. In this article, we discuss the typical imaging features and challenging situations related to primary liver cancers in MRI, while considering how to make a correct diagnosis. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

Texture analysis of MR images to identify the differentiated degree in hepatocellular carcinoma: a retrospective study

Background

To explore the clinical value of texture analysis of MR images (multiphase Gd-EOB-DTPA-enhanced MRI and T2 weighted imaging (T2WI) to identify the differentiated degree of hepatocellular carcinoma (HCC).

Method

One hundred four participants were enrolled in this retrospective study. Each participant performed preoperative Gd-EOB-DTPA-enhanced MR scanning. Texture features were analyzed by MaZda, and B11 program was used for data analysis and classification. The diagnosis efficiencies of texture features and conventional imaging features in identifying the differentiated degree of HCC were assessed by receiver operating characteristic analysis. The relationship between texture features and differentiated degree of HCC was evaluated by Spearman’s correlation coefficient.

Results

The grey-level co-occurrence matrix -based texture features were most frequently extracted and the nonlinear discriminant analysis was excellent with the misclassification rate ranging from 3.33 to 14.93%. The area under the curve (AUC) of the combined texture features between poorly- and well-differentiated HCC, poorly- and moderately-differentiated HCC, moderately- and well-differentiated HCC was 0.812, 0.879 and 0.808 respectively, while the AUC of tumor size was 0.649, 0.660 and 0.517 respectively. The tumor size was significantly different between poorly- and moderately-HCC (p = 0.014). The COMBINE AUC values were not increased with tumor size combined.

Conclusions

Texture analysis of Gd-EOB-DTPA-enhanced MRI and T2WI was valuable and might be a promising method in identifying the differentiated degree of HCC. The poorly-differentiated HCC was more heterogeneous than well- and moderately-differentiated HCC.

Atypical Appearance of Hepatocellular Carcinoma and Its Mimickers: How to Solve Challenging Cases Using Gadoxetic Acid-Enhanced Liver Magnetic Resonance Imaging

Hepatocellular carcinoma (HCC) can be diagnosed noninvasively with contrast-enhanced dynamic computed tomography, magnetic resonance imaging, or ultrasonography on the basis of its hallmark imaging features of arterial phase hyperenhancement and washout on portal or delayed phase images. However, approximately 40% of HCCs show atypical imaging features, posing a significant diagnostic challenge for radiologists. Another challenge for radiologists in clinical practice is the presentation of many HCC mimickers such as intrahepatic cholangiocarcinoma, combined HCC-cholangiocarcinoma, arterioportal shunt, and hemangioma in the cirrhotic liver. The differentiation of HCCs from these mimickers on preoperative imaging studies is of critical importance. Hence, we will review the typical and atypical imaging features of HCCs and the imaging features of its common mimickers. In addition, we will discuss how to solve these challenges in practice.

LI-RADS to categorize liver nodules in patients at risk of HCC: tool or a gadget in daily practice?

PURPOSE

To determine the effectiveness of liver reporting and data system (LI-RADS) to diagnose hepatocellular carcinoma (HCC) and to retrospectively evaluate its impact on the adopted therapeutic strategy.

MATERIALS AND METHODS

Preoperative imaging of 40 of 350 patients (median age 66, 31 M/9 F) submitted to liver resection for suspected HCC, between January 2008 and August 2019, has been retrospectively analyzed by two radiologists with different expertise, according to CT/MRI LI-RADS^® v2018, both blinded to clinical and pathological results and untrained to using aforementioned scoring system.

RESULTS

The perfect agreement between the readers was about 62.5% (25/40) (Cohen k: 0.41), better for LR-5 category (16/25) and higher in magnetic resonance imaging (MRI) investigations (68%; 13/19), which has been demonstrated the modality of choice for diagnosis of high probable and certain HCC, with arterial phase hyperenhancement as the most sensitive and accurate major feature. Compared to final histology, LR4 and LR5 scores assigned by senior radiologist reached sensitivity, specificity, positive and negative predictive values (PPV, PNV) and diagnostic accuracy of 90,9%, 29,0%, 93,8%, 62,5% and 87,5%, respectively, slightly higher than junior's ones. Misdiagnosis of HCC was done by both radiologists in the same two patients: 1 primary hepatic lymphoma (PHL) and 1 regenerative liver nodule (RLN). If LI-RADS would have been applied at the time of pre-surgical imaging, treatment planning would be modified in 10% of patients (4/40); the patient scheduled as LR-3 and finally resulted a focal nodular hyperplasia would have avoided liver resection.

CONCLUSIONS

Application of LI-RADS, especially on MRI, may provide a more accurate evaluation of suspected HCC. PHL and RLN are the Achille's heels according to our experience.

Comparison of hepatic epithelioid angiomyolipoma and non-hepatitis B, non-hepatitis C hepatocellular carcinoma on contrast-enhanced ultrasound

PURPOSE

The purpose of this study was to retrospectively compare the imaging features of hepatic epithelioid angiomyolipoma (HEAML) to those of hepatocellular carcinoma negative for hepatitis B surface antigen and hepatitis C antibody (NBNC-HCC) on contrast-enhanced ultrasound (CEUS) with sulphur hexafluoride microbubbles.

MATERIAL AND METHODS

Twenty-two patients (4 men, 18 women) with a mean age of 42.6±10.2 (SD) years (range: 22-63 years) with histopathologically confirmed HEMAL were included in the study. Forty-four patients (30 men, 14 women) with a mean age of 57.3±15.9 years (range: 19-85 years) with histopathologically confirmed NBNC-HCC were randomly selected from our institution's database as a control group. The CEUS characteristics of the two groups were compared.

RESULTS

On conventional ultrasound, significant differences in tumor diameter were found between HEAML (4.0±2.0 [SD] cm; range: 1.3-8.9cm) and NBNC-HCC (8.4±4.4 [SD] cm; range: 1.6-18cm) (P<0.001) as well as in degrees of enhancement during the portal (P=0.001) and late phases (P=0.003), contrast distribution (P<0.001) and absence of pseudocaspule (P<0.001). On CEUS, hyperenhancement during the arterial phase was observed in 21/22 (95.5%) HEAMLs and in 43/44 (97.7%) NBNC-HCCs (P>0.999). Homogeneous enhancement was more frequent in HEAMLs (20/22; 90.9%) than in NBNC-HCCs (13/44; 29.6%) (P<0.001). Pseudocapsule was observed in 0/22 HEAMLs (0.0%) and in 36/44 NBNC-HCCs (81.8%) (P=0.017). A prolonged enhancement was observed in 5/22 HEAMLs (22.7%) and in 0/44 NBNC-HCCs (0.0%) (P<0.001) during the late phase.

CONCLUSION

CEUS with sulphur hexafluoride microbubbles is helpful in discriminating between HEAML and NBNC-HCC. Homogeneous enhancement and lack of pseudocapsule are suggestive features for the diagnosis of HEAML.

Dynamic CT angiography for therapy evaluation after transarterial chemoembolization of hepatocellular carcinoma

Background

Liver dynamic computed tomography (CT) is an established method for pre- and post-interventional evaluation of hepatocellular carcinoma. To date only the liver parenchyma and perfusion information of dynamic CT has been evaluated widely.

Purpose

To evaluate the vascular information contained in dynamic CT datasets.

Material and Methods

Dynamic CT performed one day after transarterial chemoembolization (60 mL of contrast medium, 6 mL/s, 40 s scan duration) were retrospectively evaluated. Conventional slice and angiographic maximum-intensity-projection reconstructions were calculated on a multi-modality post-processing platform. Datasets were evaluated for viable tumor, anatomy of the vasculature, and potential tumor-feeding vessels. The results were compared to digital subtraction angiography images.

Results

In total, 94 treated hepatocellular carcinoma nodules were evaluated (62 dynamic CT scans, 46 patients [34 men; mean age = 69 years]). Forty-six partially viable tumors were diagnosed after transarterial chemoembolization. In all of these, tumor-feeding vessels were found in dynamic CT. Seventeen suspected extra-hepatic tumor feeders were reported, of which 14 had not been found during previous transarterial chemoembolization.

Conclusion

Dynamic CT is useful in post-interventional imaging of hepatocellular carcinoma after transarterial chemoembolization due to its ability to detect residual viable tumor parts and to show previously unknown intra- and extra-hepatic tumor-feeding vessels.

Nomogram to Assist in Surgical Plan for Hepatocellular Carcinoma: a Prediction Model for Microvascular Invasion

BACKGROUND

Microvascular invasion (MVI) relates to poor survival in hepatocellular carcinoma (HCC) patients. In this study, we aim at developing a nomogram for MVI prediction and potential assistance in surgical planning.

METHODS

A total of 357 patients were assigned to training (n = 257) and validation (n = 100) cohort. Univariate and multivariate analyses were used to reveal preoperative predictors for MVI. A nomogram incorporating independent predictors was constructed and validated. Disease-free survival was compared between patients, and the potential of the predicted MVI in making surgical procedure was also explored.

RESULTS

Pathological examination confirmed MVI in 140 (39.2%) patients. Imaging features including larger tumor, intra-tumoral artery, tumor type, and higher serum AFP independently correlated with MVI. The nomogram showed desirable performance with an AUROC of 0.803 (95% CI, 0.746-0.860) and 0.814 (95% CI, 0.720-0.908) in the training and validation cohorts, respectively. Good calibration were also revealed by calibration curve in both cohorts. The decision curve analysis indicated that the prediction nomogram was of promising usefulness in clinical work. In addition, survival analysis revealed that patients with positive-predicted MVI suffered a higher risk of early recurrence (P < 0.01). There was no difference in disease-free survival between anatomic or non-anatomic resection in large HCC or small HCC without nomogram-predicted MVI. However, anatomic resection improved disease-free survival in small HCC with nomogram-predicted MVI.

CONCLUSIONS

The nomogram obtained desirable results in predicting MVI. Patients with predicted MVI were associated with early recurrence and anatomic resection was recommended for small HCC patients with predicted MVI.

Radiological appearance of hepatocellular carcinoma predicts the response to trans-arterial chemoembolization in patients undergoing liver transplantation

Background

The ultimate goal of locoregional therapy (LRT) to the liver is to induce total tumor necrosis. Trans-arterial chemoembolization (TACE) is the mainstay bridging therapy for patients with hepatocellular carcinoma (HCC) waiting for liver transplantation (LT). However, tumor response rate is variable. The purpose of this study was to correlate HCC radiological appearance with level of tumor necrosis during explant analysis from patients undergoing LT who received pre-LT TACE.

Methods

From January 2000 to December 2018, a total of 66 patients with HCC who had been treated prior to LT by means of TACE were analyzed. Diagnosis of HCC was made based on AASLD guidelines and confirmed via histopathology explant analysis. Radiologic tumor response after TACE was based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Degree of tumor necrosis was determined by histopathology analysis of liver explants. HCC radiological appearances on CT before TACE were assessed and correlated with histological findings after LT.

Results

Eighty nine TACE procedures (1.35 ± 0.67; 1–4) were performed, of which 18 were repeated TACE (27.3%) procedures. In 56.1% of the patients, ≥90% (near-complete) tumor necrosis was achieved. Concordance between mRECIST criteria and pathology was observed in 63% of the patients, with an underestimation of tumor response in 18 (27%) patients and an overestimation in 6 (9.1%). Near-complete tumor necrosis upon pathological analysis was associated with tumor hyper-enhancement in the arterial phase (P = 0.002), “typical tumor enhancement” (P = 0.010) and smooth tumor margins (p = 0.011). The multivariate analysis showed that well circumscribed HCCs with smooth margins and arterial hyper-enhancement independently correlated with post-TACE near-complete histological tumor necrosis.

Conclusions

The well circumscribed HCC lesions with arterial hyper-enhancement are more susceptible to TACE than lesions with arterial phase iso or hypo-enhancement and lesions with infiltrative appearance. Pre-TACE CT imaging may ease the selection of an optimal treatment strategy for bridging patients with HCC to liver transplantation.

Computer-aided diagnosis of cirrhosis and hepatocellular carcinoma using multi-phase abdomen CT

PURPOSE

High mortality rate due to liver cirrhosis has been reported over the globe in the previous years. Early detection of cirrhosis may help in controlling the disease progression toward hepatocellular carcinoma (HCC). The lack of trained CT radiologists and increased patient population delays the diagnosis and further management. This study proposes a computer-aided diagnosis system for detecting cirrhosis and HCC in a very efficient and less time-consuming approach.

METHODS

Contrast-enhanced CT dataset of 40 patients (n = 40; M:F = 5:3; age = 25-55 years) with three groups of subjects: healthy (n = 14), cirrhosis (n = 12) and cirrhosis with HCC (n = 14), were retrospectively analyzed in this study. A novel method for the automatic 3D segmentation of liver using modified region-growing segmentation technique was developed and compared with the state-of-the-art deep learning-based technique. Further, histogram parameters were calculated from segmented CT liver volume for classification between healthy and diseased (cirrhosis and HCC) liver using logistic regression. Multi-phase analysis of CT images was performed to extract 24 temporal features for detecting cirrhosis and HCC liver using support vector machine (SVM).

RESULTS

The proposed method produced improved 3D segmentation with Dice coefficient 90% for healthy liver, 86% for cirrhosis and 81% for HCC subjects compared to the deep learning algorithm (healthy: 82%; cirrhosis: 78%; HCC: 70%). Standard deviation and kurtosis were found to be statistically different (p < 0.05) among healthy and diseased liver, and using logistic regression, classification accuracy obtained was 92.5%. For detecting cirrhosis and HCC liver, SVM with RBF kernel obtained highest slice-wise and patient-wise prediction accuracy of 86.9% (precision = 0.93, recall = 0.7) and 80% (precision = 0.86, recall = 0.75), respectively, than that of linear kernel (slice-wise: accuracy = 85.4%, precision = 0.92, recall = 0.67; patient-wise: accuracy = 73.33%, precision = 0.75, recall = 0.75).

CONCLUSIONS

The proposed computer-aided diagnosis system for detecting cirrhosis and hepatocellular carcinoma (HCC) showed promising results and can be used as effective screening tool in medical image analysis.

Imaging biomarkers for well and moderate hepatocellular carcinoma: preoperative magnetic resonance image and histopathological correlation

Background

Our aim of the study is to investigate the feasibility of preoperative prediction for hepatocellular carcinoma (HCC) histological grading using gadoxetic acid-enhanced magnetic resonance imaging (MRI).

Methods

This study included one hundred and fifty-six patients with solitary HCC. Preoperative gadoxetic acid-enhanced MRI findings were retrospectively analyzed. MRI qualitative features such as tumor size, margin, capsule status, signal homogeneity, intratumoral vessels, peritumoral enhancement during mid-arterial phase, peritumoral hypointensity during the hepatobiliary phase (HBP) were investigated. Apparent diffusion coefficients (ADCs), T1 reduction ratio of pre- and post-contrast enhanced images of the tumors were calculated. HCC histological grading in surgical specimens were confirmed by Edmonson’s criteria. Correlations between these MRI features and HCC histological grading were analyzed using multivariate logistic regression. The receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of the model.

Results

Univariate analysis showed that maximum tumor diameter (p = 0.004), tumor margin (p = 0.006), intratumoral vessels (p = 0.001) and peritumoral hypointensity during HBP (p = 0.000), were significantly correlated with HCC histological grading. There was no relationship between capsule, tumor signal, venous thrombosis, peritumoral enhancement during mid-arterial phase, ADC value, T1 reduction ratio, and HCC histological grading. Multivariate logistic regression analysis demonstrated that the maximum tumor diameter (p = 0.012, odds ratio = 1.002, 95% confidence interval: 1.007–1.046)) was an independent risk factor for high grade HCC.

Conclusions

Greater tumor size, a more irregular margin, presence of intratumoral vessels, and peritumoral hypointensity during HBP were indicators for high grade HCC. The maximum tumor diameter was an independent risk factor for high grade HCC.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5574-8) contains supplementary material, which is available to authorized users.

Hepatocellular Carcinoma with Irregular Rim-Like Arterial Phase Hyperenhancement: More Aggressive Pathologic Features

BACKGROUND AND AIMS

The purpose of our study was to examine the histopathologic characteristics of hepatocellular carcinoma (HCC) with irregular rim-like arterial phase enhancement (IRE), which has been reported to be associated with more aggressive tumor behavior.

METHODS

We investigated 84 pathologically confirmed HCCs in 84 patients who underwent curative hepatic resection after gadoxetate-enhanced magnetic resonance imaging between January 2008 and February 2013. Two abdominal radiologists independently reviewed these images and classified HCCs into two categories: HCC showing IRE (IRE-HCC) and HCC showing hypoenhancement or diffuse arterial enhancement (non-IRE-HCC). Twenty-two HCCs were classified as IRE-HCCs, and 51 were classified as non-IRE-HCCs concordantly by both reviewers. The remaining 11 HCCs, on whose radiologic classifications the reviewers disagreed, were classified as HCCs with intermediate enhancement patterns. The HCC clinicopathologic characteristics and patient outcomes were then compared.

RESULTS

IRE-HCCs showed more frequent microvascular invasion (91 vs. 35%), lower microvascular density (246.5 vs. 426.5/mm²), higher proportions of sinusoid-like microvascular pattern (55 vs. 0%) and macrotrabecular pattern (45 vs. 0%), and larger areas of tumor necrosis (15 vs. 0%) and fibrous stroma (8.3 vs. 2.1%) than non-IRE-HCCs. IRE-HCCs also expressed higher levels of immunomarkers of hypoxia (carbonic anhydrase IX, 64 vs. 8%) and stemness (EpCAM, 50 vs. 20%). p values were < 0.001 for all comparisons except for EpCAM (p = 0.026). HCCs with intermediate enhancement patterns showed mixed/intermediate pathologic features from both IRE- and non-IRE-HCCs. IRE-HCC patients showed poorer 5-year disease-free survival after curative resection than non-IRE-HCC patients (p = 0.005).

CONCLUSIONS

IRE-HCCs demonstrate aggressive histopathologic features, including more hypoxic and fibrotic tumor microenvironments and increased stemness, compared to non-IRE-HCCs. IRE might therefore serve as a noninvasive imaging biomarker for aggressive HCC.

Diagnostic value of imaging examinations in patients with primary hepatocellular carcinoma

Primary hepatocellular carcinoma (PHC) includes hepatocellular carcinoma, intrahepatic cholangiocarcinoma and other pathological types and is characterized by rapid progression. Most of the clinical diagnoses are made at late stage or when distant metastasis occurs, increasing the difficulty of treatment and resulting in a poor prognosis. Therefore, the early diagnosis of PHC plays an important role in timely treatment and the improvement of prognosis. The gold standard for the diagnosis of primary liver cancer is liver biopsy, but it has limitations as an invasive examination. Presently, imaging has become the first choice for the diagnosis of liver cancer. We here summarize the new methods and techniques of imaging in diagnosis and evaluation of primary liver cancer in recent years, including ultrasonography, computed tomography perfusion imaging, diffusion-weighted imaging technology-voxel incoherent motion, diffusion tensor imaging, iterative decomposition of water and fat with echo asymmetry and least squares estimation-iron quantification, dynamic enhanced magnetic resonance imaging and hepatocyte-specific contrast medium imaging. Imaging diagnosis can not only evaluate the degree of differentiation, blood supply and perfusion, and invasiveness of the lesion, but also predict the prognosis, evaluate liver function, and provide references for clinical diagnosis and treatment.

Pitfalls and problems to be solved in the diagnostic CT/MRI Liver Imaging Reporting and Data System (LI-RADS)

The 2017 Core of the computed tomography (CT)/magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS) provides clear definitions and concise explanations of the CT/MRI diagnostic algorithm. Nevertheless, there remain some practical and controversial issues that radiologists should be aware of when using the system. This article discusses pitfalls and problems which may be encountered when the version 2017 diagnostic algorithm is used for CT and MRI. The pitfalls include challenges in applying major features and assigning the LR-M category, as well as categorisation discrepancy between CT and MRI. The problems include imprecision of category codes, application of ancillary features, and regional practice variations in hepatocellular carcinoma (HCC) diagnosis. Potential solutions are presented along with these pitfalls and problems. KEY POINTS: • Although the diagnostic algorithm provides clear and detailed explanations, major feature evaluation can be subject to pitfalls and differentiation of HCC and non-HCC malignancy remains challenging. • Ancillary features are optional and equally weighted. However, features such as hepatobiliary phase hypointensity and restricted diffusion have greater impact on HCC diagnosis than other ancillary features and may merit greater emphasis or weighting. • LI-RADS was initially developed from a Western paradigm, which may limit its applicability in the East due to regional practice variations. In Eastern Asia, high sensitivity is prioritised over near-perfect specificity for HCC diagnosis in order to detect tumours at early stages.

[Differential diagnosis of hepatocellular carcinoma and hepatic hemangiomas based on radiomic features of gadoxetate disodium-enhanced magnetic resonance imaging]

OBJECTIVE

To evaluate the feasibility of using radiomic features for differential diagnosis of hepatocellular carcinoma (HCC) and hepatic cavernous hemangioma (HHE).

METHODS

Gadoxetate disodium-enhanced magnetic resonance imaging data were collected from a total of 135 HCC and HHE lesions. The radiomic texture features of each lesion were extracted on the hepatobiliary phase images, and the performance of each feature was assessed in differentiation and classification of HCC and HHE. In multivariate analysis, the performance of 3 feature selection algorithms (namely minimum redundancy-maximum relevance, mRmR; neighborhood component analysis, NCA; and sequence forward selection, SFS) was compared. The optimal feature subset was determined according to the optimal feature selection algorithm and used for testing the 3 classifier algorithms (namely the support vector machine, RBF-SVM; linear discriminant analysis, LDA; and logistic regression). All the tests were repeated 5 times with 10-fold cross validation experiments.

RESULTS

More than 50% of the radiomic features exhibited strong distinguishing ability, among which gray level co-occurrence matrix feature S (3, -3) SumEntrp showed a good classification performance with an AUC of 0.72 (P<0.01), a sensitivity of 0.83 and a specificity of 0.57. For the multivariate analysis, 15 features were selected based on the SFS algorithm, which produced better results than the other two algorithms. Testing of these 15 selected features for their average cross-validation performance with RBF-SVM classifier yielded a test accuracy of 0.82∓0.09, an AUC of 0.86∓0.12, a sensitivity of 0.88∓0.11, and a specificity of 0.76∓0.18.

CONCLUSION

The radiomic features based on gadoxetate disodium-enhanced magnetic resonance images allow efficient differential diagnosis of HCC and HHE, and can potentially provide important assistance in clinical diagnosis of the two diseases.