MRI features of combined hepatocellular- cholangiocarcinoma versus mass forming intrahepatic cholangiocarcinoma

MRI features of combined hepatocellular-cholangiocarcinoma

Combined hepatocellular cholangiocarcinoma (cHCC-CCA) is a rare liver tumor which has a more aggressive behavior and worse survival outcome than hepatocellular carcinoma (HCC), with a prognosis similar to that of intrahepatic cholangiocarcinoma (iCCA). With limited literature on the appearance of this tumor on MRI, it remains a diagnostic challenge. In this review, we looked at the currently described MRI findings in this uncommon entity. Based on studies conducted to date, a mixed pattern at imaging has demonstrated the highest specificity, seen as a combination of areas showing progressive enhancement of the lesion, arterial enhancement with washout, and areas of arterial enhancement without washout and/or hypovascularity. Tumor markers may aid in identification, particularly in cases where the imaging appearance mimics that of isolated HCC or iCCA. Intratumoral heterogeneity leads to difficulties with pathologic diagnosis from sampling due to the possibility of an incorrect diagnosis if the biopsy specimen does not contain adequate tissue comprising both histologic components.

Imaged periductal infiltration: Diagnostic and prognostic role in intrahepatic mass-forming cholangiocarcinoma

Purpose

This study examines periductal infiltration in intrahepatic mass-forming cholangiocarcinoma (IMCC), focusing on its importance for differentiating hepatic tumors and its influence on post-surgical survival in IMCC patients.

Methods

Eighty-three consecutive patients with IMCC (n = 43) and liver cancer whose preoperative images showed intrahepatic bile duct dilatation adjacent to the tumor for differential diagnosis from hepatocellular carcinoma (HCC) [n = 21], metastatic liver cancer (MLC) [n = 16] and combined hepatocellular-cholangiocarcinoma (cHCC-CC) [n = 3] were enrolled. CT and MRI findings of simple bile duct compression, imaged periductal infiltration, and imaged intrabiliary growth adjacent to the main tumor were reviewed. Clinicopathological and imaging features were compared in each group. The sensitivity, specificity, and odds ratio were calculated for each imaging finding of IMCC versus the other tumor groups. Overall survival was compared between cases of IMCC with and without imaged periductal infiltration.

Results

Simple bile duct compression and imaged intrabiliary growth were more frequently observed in HCC than in the others (p < 0.0001 and 0.040, respectively). Imaged periductal infiltration was observed more often in histopathologically confirmed large-duct type IMCC than in the small-duct type IMCC (p = 0.034). Multivariable analysis demonstrated that only imaged periductal infiltration (odds ratio, 50.67) was independently correlated with IMCC. Patients with IMCC who had imaged periductal infiltration experienced a poorer prognosis than those without imaged periductal infiltration (p = 0.0034).

Conclusion

Imaged periductal infiltration may serve as a significant marker for differentiating IMCC from other liver cancers. It may also have the potential to predict post-surgical outcomes in patients with IMCC.

Implications of ultrasound-based deep learning model for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma

OBJECTIVES

The current study developed an ultrasound-based deep learning model to make preoperative differentiation among hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and combined hepatocellular-cholangiocarcinoma (cHCC-ICC).

METHODS

The B-mode ultrasound images of 465 patients with primary liver cancer were enrolled in model construction, comprising 264 HCCs, 105 ICCs, and 96 cHCC-ICCs, of which 50 cases were randomly selected to form an independent test cohort, and the rest of study population was assigned to a training and validation cohorts at the ratio of 4:1. Four deep learning models (Resnet18, MobileNet, DenseNet121, and Inception V3) were constructed, and the fivefold cross-validation was adopted to train and validate the performance of these models. The following indexes were calculated to determine the differential diagnosis performance of the models, including sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), F-1 score, and area under the receiver operating characteristic curve (AUC) based on images in the independent test cohort.

RESULTS

Based on the fivefold cross-validation, the Resnet18 outperformed other models in terms of accuracy and robustness, with the overall training and validation accuracy as 99.73% (± 0.07%) and 99.35% (± 0.53%), respectively. Furthers validation based on the independent test cohort suggested that Resnet 18 yielded the best diagnostic performance in identifying HCC, ICC, and cHCC-ICC, with the sensitivity, specificity, accuracy, PPV, NPV, F1-score, and AUC of 84.59%, 92.65%, 86.00%, 85.82%, 92.99%, 92.37%, 85.07%, and 0.9237 (95% CI 0.8633, 0.9840).

CONCLUSION

Ultrasound-based deep learning algorithm appeared a promising diagnostic method for identifying cHCC-ICC, HCC, and ICC, which might play a role in clinical decision making and evaluation of prognosis.

A convenient scoring system to distinguish intrahepatic mass-forming cholangiocarcinoma from solitary colorectal liver metastasis based on magnetic resonance imaging features

OBJECTIVES

To develop and validate a diagnostic scoring system to differentiate intrahepatic mass-forming cholangiocarcinoma (IMCC) from solitary colorectal liver metastasis (CRLM).

METHODS

A total of 366 patients (263 in the training cohort, 103 in the validation cohort) who underwent MRI examination with pathologically proven either IMCC or CRLM from two centers were included. Twenty-eight MRI features were collected. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors for distinguishing IMCC from solitary CRLM. The independent predictors were weighted over based on regression coefficients to build a scoring system. The overall score distribution was divided into three groups to show the diagnostic probability of CRLM.

RESULTS

Six independent predictors, including hepatic capsular retraction, peripheral hepatic enhancement, vessel penetrating the tumor, upper abdominal lymphadenopathy, peripheral washout at the portal venous phase, and rim enhancement at the portal venous phase were included in the system. All predictors were assigned 1 point. At a cutoff of 3 points, AUCs for this score model were 0.948 and 0.903 with sensitivities of 96.5% and 92.0%, specificities of 84.4% and 71.7%, positive predictive values of 87.7% and 75.4%, negative predictive values of 95.4% and 90.5%, and accuracies of 90.9% and 81.6% for the training and validation cohorts, respectively. An increasing trend was shown in the diagnostic probability of CRLM among the three groups based on the score.

CONCLUSIONS

The established scoring system is reliable and convenient for distinguishing IMCC from solitary CRLM using six MRI features.

CLINICAL RELEVANCE STATEMENT

A reliable and convenient scoring system was developed to differentiate between intrahepatic mass-forming cholangiocarcinoma from solitary colorectal liver metastasis using six MRI features.

KEY POINTS

• Characteristic MRI features were identified to distinguish intrahepatic mass-forming cholangiocarcinoma (IMCC) from solitary colorectal liver metastasis (CRLM). • A model to distinguish IMCC from solitary CRLM was created based on 6 features, including hepatic capsular retraction, upper abdominal lymphadenopathy, peripheral washout at the portal venous phase, rim enhancement at the portal venous phase, peripheral hepatic enhancement, and vessel penetrating the tumor.

The significance of the predominant component in combined hepatocellular-cholangiocarcinoma: MRI manifestation and prognostic value

PURPOSE

To investigate the significance of the predominant component of combined hepatocellular-cholangiocarcinoma (cHCC-CC) in terms of MRI manifestation and its potential prognostic value compared to hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC).

MATERIALS AND METHODS

A total of 300 patients with chronic liver disease from two centers were retrospectively enrolled, including 100 surgically proven cases of cHCC-CC, HCC, and ICC each. Univariate and multivariate regression analyses were performed to identify independent predictors for distinguishing HCC-predominant cHCC-CC and ICC-predominant cHCC-CC from HCC and ICC, respectively. Diagnostic models were constructed based on the independent features. Recurrence-free survival (RFS) was estimated and compared between groups.

RESULTS

The predominant component was an independent predictor for RFS in cHCC-CC (hazard ratio = 1.957, P = 0.044). The presence of targetoid appearance (odds ratio(OR) = 10.907, P = 0.001), lack of enhancing capsule (OR = 0.072, P = 0.001) and arterial peritumoral enhancement (OR = 0.091, P = 0.003) were independent predictors suggestive of HCC-predominant cHCC-CC over HCC; their combination yielded an area under the curve of 0.756. No significant differences were observed in RFS between HCC-predominant cHCC-CC and HCC (P = 0.864). Male gender (OR = 4.049, P = 0.015), higher alpha fetoprotein (OR = 16.789, P < 0.001) and normal carbohydrate antigen 19-9 (OR = 0.343, P = 0.036) levels, presence of enhancing capsule (OR = 7.819, P < 0.001) and hemorrhage (OR = 23.526, P = 0.004), and lack of targetoid appearance (OR = 0.129, P = 0.005) and liver surface retraction (OR = 0.190, P = 0.021) were independent predictors suggestive of ICC-predominant cHCC-CC over ICC; their combination yielded an area under the curve value of 0.898. ICC-predominant cHCC-CC exhibited poorer survival with shorter RFS than ICC (P = 0.009).

CONCLUSION

The predominant histopathological component is closely related to the imaging manifestation of cHCC-CC; and more importantly, it plays a significant prognostic role, which may alter the RFS prognosis of cHCC-CC.

Update on the Applications of Radiomics in Diagnosis, Staging, and Recurrence of Intrahepatic Cholangiocarcinoma

BACKGROUND

This paper offers an assessment of radiomics tools in the evaluation of intrahepatic cholangiocarcinoma.

METHODS

The PubMed database was searched for papers published in the English language no earlier than October 2022.

RESULTS

We found 236 studies, and 37 satisfied our research criteria. Several studies addressed multidisciplinary topics, especially diagnosis, prognosis, response to therapy, and prediction of staging (TNM) or pathomorphological patterns. In this review, we have covered diagnostic tools developed through machine learning, deep learning, and neural network for the recurrence and prediction of biological characteristics. The majority of the studies were retrospective.

CONCLUSIONS

It is possible to conclude that many performing models have been developed to make differential diagnosis easier for radiologists to predict recurrence and genomic patterns. However, all the studies were retrospective, lacking further external validation in prospective and multicentric cohorts. Furthermore, the radiomics models and the expression of results should be standardized and automatized to be applicable in clinical practice.

Targetoid Primary Liver Malignancy in Chronic Liver Disease: Prediction of Postoperative Survival Using Preoperative MRI Findings and Clinical Factors

OBJECTIVE

We aimed to assess and validate the radiologic and clinical factors that were associated with recurrence and survival after curative surgery for heterogeneous targetoid primary liver malignancies in patients with chronic liver disease and to develop scoring systems for risk stratification.

MATERIALS AND METHODS

This multicenter retrospective study included 197 consecutive patients with chronic liver disease who had a single targetoid primary liver malignancy (142 hepatocellular carcinomas, 37 cholangiocarcinomas, 17 combined hepatocellular carcinoma-cholangiocarcinomas, and one neuroendocrine carcinoma) identified on preoperative gadoxetic acid-enhanced MRI and subsequently surgically removed between 2010 and 2017. Of these, 120 patients constituted the development cohort, and 77 patients from separate institution served as an external validation cohort. Factors associated with recurrence-free survival (RFS) and overall survival (OS) were identified using a Cox proportional hazards analysis, and risk scores were developed. The discriminatory power of the risk scores in the external validation cohort was evaluated using the Harrell C-index. The Kaplan-Meier curves were used to estimate RFS and OS for the different risk-score groups.

RESULTS

In RFS model 1, which eliminated features exclusively accessible on the hepatobiliary phase (HBP), tumor size of 2-5 cm or > 5 cm, and thin-rim arterial phase hyperenhancement (APHE) were included. In RFS model 2, tumors with a size of > 5 cm, tumor in vein (TIV), and HBP hypointense nodules without APHE were included. The OS model included a tumor size of > 5 cm, thin-rim APHE, TIV, and tumor vascular involvement other than TIV. The risk scores of the models showed good discriminatory performance in the external validation set (C-index, 0.62-0.76). The scoring system categorized the patients into three risk groups: favorable, intermediate, and poor, each with a distinct survival outcome (all log-rank p < 0.05).

CONCLUSION

Risk scores based on rim arterial enhancement pattern, tumor size, HBP findings, and radiologic vascular invasion status may help predict postoperative RFS and OS in patients with targetoid primary liver malignancies.

Quantitative Assessment of Hypovascular Component in Arterial Phase to Help the Discrimination of Combined Hepatocellular-Cholangiocarcinoma and Hepatocellular Carcinoma

Purpose

To explore the imaging performance for discrimination of combined hepatocellular- cholangiocarcinoma (cHCC-CCA) and hepatocellular carcinoma (HCC).

Methods

In total, 35 patients with cHCC-CCA and a matched control group of HCC patients (n = 35) were included retrospectively. We quantitatively evaluated the hypovascular component in tumor and qualitatively assessed LI-RADS features and other aggressive features to develop model for cHCC-CCA diagnose. Subgroup analyses were performed by tumor size and LI-RADS category.

Results

cHCC-CCA frequently showed a larger proportion (≥50%) of hypovascular areas followed by HCC (P = 0.000). Among those patients with ≥50% hypovascular areas, 8 patients did not present rim enhancement in atrial phase. The LI-RADS major features were more commonly observed in HCC (82.9-45.7%,), than cHCC-CCA (P = 0.003-0.022). The targetoid appearances and non-smooth margin frequently appeared in cHCC-CCA (34.3-63.9%), compared with HCC (P = 0.000-0.023). We developed a radiologic model based on ≥50% hypovascular component and delayed enhancement, which presented AUC of 0.821, accuracy of 80%. We also obtained good performance by radiologic model in LR-M group and tumor size <50mm group (AUC: 0.841 and 0.866, respectively). Combined group which included CA 19-9 and ≥50% hypovascular component and delayed enhancement did not improve the distinction performance between cHCC-CCA and HCC, which presented good performance of identifying cHCC-CCA in the LR-4/5 subgroup and tumor size ≥50 mm subgroup (AUC: 0.717, 0.730, respectively). cHCC-CCA group presented heterogeneous dominant pathology involving 15 of HCC, 7 of intrahepatic cholangiocarcinoma (iCCA) or cholangiolocellular carcinoma (CLC), 13 of intermediate cells component. Macrotrabecular appearances were higher in cHCC-CCA than that in HCC. The proportion of Hepa-1 was significantly higher in true negative (TN) patients (29 [93.5%]) and false negative (FN) patients (10 [100%]) than in true positive (TP) patients (16 [64%]; P = 0.036).

Conclusion

Quantitative assessment of hypovascular component could help the discrimination of cHCC-CCA. Macrotrabecular appearances were more exhibited in cHCC-CCA than that in HCC.

A Deep Learning Workflow for Mass-Forming Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma Classification Based on MRI

OBJECTIVE

Precise classification of mass-forming intrahepatic cholangiocarcinoma (MF-ICC) and hepatocellular carcinoma (HCC) based on magnetic resonance imaging (MRI) is crucial for personalized treatment strategy. The purpose of the present study was to differentiate MF-ICC from HCC applying a novel deep-learning-based workflow with stronger feature extraction ability and fusion capability to improve the classification performance of deep learning on small datasets.

METHODS

To retain more effective lesion features, we propose a preprocessing method called semi-segmented preprocessing (Semi-SP) to select the region of interest (ROI). Then, the ROIs were sent to the strided feature fusion residual network (SFFNet) for training and classification. The SFFNet model is composed of three parts: the multilayer feature fusion module (MFF) was proposed to extract discriminative features of MF-ICC/HCC and integrate features of different levels; a new stationary residual block (SRB) was proposed to solve the problem of information loss and network instability during training; the attention mechanism convolutional block attention module (CBAM) was adopted in the middle layer of the network to extract the correlation of multi-spatial feature information, so as to filter the irrelevant feature information in pixels.

RESULTS

The SFFNet model achieved an overall accuracy of 92.26% and an AUC of 0.9680, with high sensitivity (86.21%) and specificity (94.70%) for MF-ICC.

CONCLUSION

In this paper, we proposed a specifically designed Semi-SP method and SFFNet model to differentiate MF-ICC from HCC. This workflow achieves good MF-ICC/HCC classification performance due to stronger feature extraction and fusion capabilities, which provide complementary information for personalized treatment strategy.

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.

DCE-MRI based radiomics nomogram for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from mass-forming intrahepatic cholangiocarcinoma

OBJECTIVE

To establish a radiomics nomogram based on dynamic contrast-enhanced (DCE) MR images to preoperatively differentiate combined hepatocellular-cholangiocarcinoma (cHCC-CC) from mass-forming intrahepatic cholangiocarcinoma (IMCC).

METHODS

A total of 151 training cohort patients (45 cHCC-CC and 106 IMCC) and 65 validation cohort patients (19 cHCC-CC and 46 IMCC) were enrolled. Findings of clinical characteristics and MR features were analyzed. Radiomics features were extracted from the DCE-MR images. A radiomics signature was built based on radiomics features by the least absolute shrinkage and selection operator algorithm. Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and construct a clinical model. The radiomics signature and significant clinicoradiological variables were then incorporated into the radiomics nomogram by multivariate logistic regression analysis. Performance of the radiomics nomogram, radiomics signature, and clinical model was assessed by receiver operating characteristic and area under the curve (AUC) was compared.

RESULTS

Eleven radiomics features were selected to develop the radiomics signature. The radiomics nomogram integrating the alpha fetoprotein, background liver disease (cirrhosis or chronic hepatitis), and radiomics signature showed favorable calibration and discrimination performance with an AUC value of 0.945 in training cohort and 0.897 in validation cohort. The AUCs for the radiomics signature and clinical model were 0.848 and 0.856 in training cohort and 0.792 and 0.809 in validation cohort, respectively. The radiomics nomogram outperformed both the radiomics signature and clinical model alone (p < 0.05).

CONCLUSION

The radiomics nomogram based on DCE-MRI may provide an effective and noninvasive tool to differentiate cHCC-CC from IMCC, which could help guide treatment strategies.

KEY POINTS

• The radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging is useful to preoperatively differentiate cHCC-CC from IMCC. • The radiomics nomogram showed the best performance in both training and validation cohorts for differentiating cHCC-CC from IMCC.

Imaging Spectrum of Intrahepatic Mass-Forming Cholangiocarcinoma and Its Mimickers: How to Differentiate Them Using MRI

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary hepatic malignancy, with mass-forming growth pattern being the most common. The typical imaging appearance of mass-forming ICC (mICC) consists of irregular ring enhancement in the arterial phase followed by the progressive central enhancement on portal venous and delayed phases. However, atypical imaging presentation in the form of hypervascular mICC might also be seen, which can be attributed to distinct pathological characteristics. Ancillary imaging features such as lobular shape, capsular retraction, segmental biliary dilatation, and vascular encasement favor the diagnosis of mICC. Nevertheless, these radiological findings may also be present in certain benign conditions such as focal confluent fibrosis, sclerosing hemangioma, organizing hepatic abscess, or the pseudosolid form of hydatid disease. In addition, a few malignant lesions including primary liver lymphoma, hemangioendothelioma, solitary hypovascular liver metastases, and atypical forms of hepatocellular carcinoma (HCC), such as scirrhous HCC, infiltrative HCC, and poorly differentiated HCC, may also pose a diagnostic dilemma by simulating mICC in imaging studies. Diffusion-weighted imaging and the use of hepatobiliary contrast agents might be helpful for differential diagnosis in certain cases. The aim of this manuscript is to provide a comprehensive overview of mICC imaging features and to describe useful tips for differential diagnosis with its potential mimickers.

A fat containing combined neuroendocrine carcinoma and hepatocellular carcinoma in the liver: A case report

A 79-year-old man was admitted to our hospital because of increased hepatobiliary enzyme levels. Dynamic computed tomography and magnetic resonance imaging showed a liver tumor measuring 60mm containing fat foci at the cranial aspect of the tumor. We diagnosed the patient with hypovascular hepatocellular carcinoma (HCC) and fat deposition, and performed a caudate lobe resection. Pathology examination revealed two intermingled components: moderately differentiated HCC with fat deposition and neuroendocrine carcinoma (NEC). Primary combined NEC and HCC is extremely rare. To our knowledge, this is the first report of combined NEC and HCC including a fat component. HCC is the most common primary hepatic malignancy with fat. HCC might include fat, even if HCC coexists with another type of cancer. The imaging characteristics of and HCC with another type of cancer vary depending on the amount of each component. We should not simply diagnose such tumors as HCC, but think about the possibilities of HCC with another type of cancer, because there is a fat component.

Liver Transplantation in Malignancies: A Comprehensive and Systematic Review on Oncological Outcome

Introduction

Liver transplantation (LT) is today's standard treatment for both end-stage liver disease and tumors; however, suitable grafts for LT are a scarce resource and outcome after LT is highly dependent on its underlying indication. Thus, patients must be carefully selected to optimize the number of life years gained per graft. This comprehensive and systematic review critically reflects the most recently published oncological outcome data after LT in malignancies based on the preoperative radiological findings.

Methods

A systematic literature search was conducted to detect preferentially most recent high-volume series or large database analysis on oncological outcomes after LT for both primary liver cancer and liver metastases between January 1, 2019, and November 14, 2020. A comprehensive review on the radiological assessment of the reviewed liver malignancies is included and its preoperative value for an outcome-driven indication reflected.

Results

Twenty most recent high-volume or relevant studies including a total number of 2,521 patients were identified including 4, 4, 4, 4, 3, and 1 publications on oncological outcome after LT for hepatocellular carcinoma, cholangiocellular carcinoma, hepatic epitheloid hemangioendothelioma, hepatoblastoma, and both metastatic neuroendocrine tumors and colorectal cancer, respectively. The overall survival is comparable to patients without tumors if patients with malignancies are well selected for LT; however, this is highly dependent on tumor entity, tumor stage, and both neoadjuvant and concomitant treatment.

Discussion/Conclusion

LT is a promising option for better survival in patients with malignant liver tumors in selected patients; however, the indication must be critically discussed prior to LT in every single case in the context of organ shortage.

Update on Pathologic and Radiologic Diagnosis of Combined Hepatocellular-Cholangiocarcinoma

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a malignant primary liver carcinoma characterized by the unequivocal presence of both hepatocytic and cholangiocytic differentiation within the same tumor. Recent research has highlighted that cHCC-CCAs are more heterogeneous than previously expected. In the updated consensus terminology and WHO 2019 classification, "classical type" and "subtypes with stem-cell features" of the WHO 2010 classification are no longer recommended. Instead, it is recommended that the presence and percentages of various histopathologic components and stem-cell features be mentioned in the pathologic report. The new terminology and classification enable the exchange of clearer and more objective information about cHCC-CCAs, facilitating multi-center and multi-national research. However, there are limitations to the diagnosis of cHCC-CCA by imaging and biopsy. cHCC-CCAs showing typical imaging findings of HCC could be misdiagnosed as HCC and subjected to inappropriate treatment, if other clinical findings are not sufficiently considered. cHCC-CCAs showing at least one of the CCA-like imaging features or unusual clinical features should be subjected to biopsy. There may be a sampling error for the biopsy diagnosis of cHCC-CCA. An optimized diagnostic algorithm integrating clinical, radiological, and histopathologic information of biopsy is required to resolve these diagnostic pitfalls.

Cholangiocarcinoma - Part 2, Tumoral and Nontumoral Mimics and Imaging Features Helpful in Differentiation

Each of the 3 morphological subtypes of cholangiocarcinoma has a different set of imaging differentials. Emulators of mass-forming cholangiocarcinoma include other primary and secondary hepatic malignancies, benign tumors and tumor-like mimics such as abscess, hemangioma and confluent hepatic fibrosis. Benign inflammatory biliary strictures constitute the major differential of periductal-infiltrative type and intraductal calculi are the main consideration for intraductal-growth type. CT and MRI are the standard imaging tools for characterization of cholangiocarcinoma and differentiating it from close mimics. Here we will describe the various tumoral and non-tumoral mimics of cholangiocarcinoma and discuss specific imaging features useful in differentiation.

Combined hepatocellular-cholangiocarcinoma: can we use contrast-enhanced ultrasound Liver Imaging Reporting and Data System (LI-RADS) to predict the patient's survival?

OBJECTIVES

To evaluate the relationship between contrast-enhanced (CE) ultrasound Liver Reporting and Data System (LI-RADS) classification of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and their histopathological component predominance, and to determine if the CEUS LI-RADS category can be used to predict the patient's survival after surgical resection.

METHODS

Between January 2011 and December 2018, medical records and CEUS of patients with pathologically proven cHCC-CCA were studied. The predominance of hepatocellular carcinoma (HCC)/intrahepatic cholangiocarcinoma (ICC) component of cHCC-CCA was analyzed by histopathology. The proportion of HCC-predominant cHCC-CCA in different LI-RADS category was compared by using Fisher's exact test. Factors affecting tumor recurrence were analyzed by Cox proportional hazard model. Disease-free survival (DFS) was estimated by using Kaplan-Meier survival curve and compared by log-rank test.

RESULTS

The study included 37 cHCC-CCA patients (33 men, 4 women; average age, 50.4 ± 11.0 years) and 37 nodules (mean diameter, 6.1 ± 3.9 cm). According to CEUS LI-RADS, 62.2% (23/37), 18.9% (7/37), and 18.9% (7/37) of cHCC-CCA were classified as LR-M, LR-5, and LR-TIV, respectively. The ratio of HCC predominance in LR-5 was 100% (10/10) vs 81.5% (22/27) in the LR-M group (p = 0.591). In our population, LR-5 patients had longer DFS than LR-M and LR-TIV patients combined (median DFS: 18.0 vs 6.4 months, p = 0.016). Multiple lesions (hazard ratio, 3.1; p = 0.007), tumor size (≥ 5 cm, hazard ratio, 4.1; p = 0.003), and CEUS LI-RADS category (LR-M and LR-TIV, hazard ratio, 4.7; p = 0.011) showed independent association with shorter DFS.

CONCLUSION

cHCC-CCA characterized as LR-5 on CEUS tend to represent HCC-predominant tumors with significantly longer disease-free survival compared to cHCC-CCA categorized as LR-M and LR-TIV.

KEY POINTS

• By using the American College of Radiology contrast-enhanced ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS), majority (30/37, 81.1%) of cHCC-CCA tumors were classified as LR-M or LR-TIV and only 18.9% (7/30) of cHCC-CCA were categorized as LR-5. • Patients with CEUS LR-5 cHCC-CCA had statistically significant longer disease-free time than those with LR-M and TIV cHCC-CCA (median DFS: 18.0 vs 6.4 months, p = 0.016). • Multiple lesions (hazard ratio, 3.1; p = 0.007), tumor size (≥ 5 cm, hazard ratio, 4.1; p = 0.003), and CEUS LI-RADS category (LR-M and LR-TIV, hazard ratio, 4.7; p = 0.011) showed independent association with shorter DFS.

Contrast-enhanced ultrasound in association with serum biomarkers for differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma

BACKGROUND

Combined hepatocellular-cholangiocarcinoma (CHC) is a rare type of primary liver cancer. Due to its complex histopathological characteristics, the imaging features of CHC can overlap with those of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC).

AIM

To investigate the possibility and efficacy of differentiating CHC from HCC and ICC by using contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) and tumor biomarkers.

METHODS

Between January 2016 and December 2019, patients with histologically confirmed CHC, ICC and HCC with chronic liver disease were enrolled. The diagnostic formula for CHC was as follows: (1) LR-5 or LR-M with elevated alpha-fetoprotein (AFP) and carbohydrate antigen 19-9 (CA19-9); (2) LR-M with elevated AFP and normal CA19-9; or (3) LR-5 with elevated CA19-9 and normal AFP. The sensitivity, specificity, accuracy and area under the receiver operating characteristic curve were calculated to determine the diagnostic value of the criteria.

RESULTS

After propensity score matching, 134 patients (mean age of 51.4 ± 9.4 years, 108 men) were enrolled, including 35 CHC, 29 ICC and 70 HCC patients. Based on CEUS LI-RADS classification, 74.3% (26/35) and 25.7% (9/35) of CHC lesions were assessed as LR-M and LR-5, respectively. The rates of elevated AFP and CA19-9 in CHC patients were 51.4% and 11.4%, respectively, and simultaneous elevations of AFP and CA19-9 were found in 8.6% (3/35) of CHC patients. The sensitivity, specificity, positive predictive value, negative predictive value, accuracy and area under the receiver operating characteristic curve of the aforementioned diagnostic criteria for discriminating CHC from HCC and ICC were 40.0%, 89.9%, 58.3%, 80.9%, 76.9% and 0.649, respectively. When considering the reported prevalence of CHC (0.4%-14.2%), the positive predictive value and NPV were revised to 1.6%-39.6% and 90.1%-99.7%, respectively.

CONCLUSION

CHCs are more likely to be classified as LR-M than LR-5 by CEUS LI-RADS. The combination of the CEUS LI-RADS classification with serum tumor markers shows high specificity but low sensitivity for the diagnosis of CHC. Moreover, CHC could be confidently excluded with high NPV.

Development and Validation of a Nomogram for Differentiating Combined Hepatocellular Cholangiocarcinoma From Intrahepatic Cholangiocarcinoma

Objectives

To establish a nomogram based on preoperative laboratory study variables using least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular cholangiocarcinoma (cHCC) from intrahepatic cholangiocarcinoma (iCCA).

Methods

We performed a retrospective analysis of iCCA and cHCC patients who underwent liver resection. Blood signatures were established using LASSO regression, and then, the clinical risk factors based on the multivariate logistic regression and blood signatures were combined to establish a nomogram for a differential preoperative diagnosis between iCCA and cHCC. The differential accuracy ability of the nomogram was determined by Harrell’s index (C-index) and decision curve analysis, and the results were validated using a validation set. Furthermore, patients were categorized into two groups according to the optimal cut-off values of the nomogram-based scores, and their survival differences were assessed using Kaplan-Meier curves.

Results

A total of 587 patients who underwent curative liver resection for iCCA or cHCC between January 2008 and December 2017 at West China Hospital were enrolled in this study. The cHCC score was based on the personalized levels of the seven laboratory study variables. On multivariate logistic analysis, the independent factors for distinguishing cHCC were age, sex, biliary duct stones, and portal hypertension, all of which were incorporated into the nomogram combined with the cHCC-score. The nomogram had a good discriminating capability, with a C-index of 0.796 (95% CI, 0.752–0.840). The calibration plot for distinguishing cHCC from iCCA showed optimal agreement between the nomogram prediction and actual observation in the training and validation sets. The decision curves indicated significant clinical usefulness.

Conclusion

The nomogram showed good accuracy for the differential diagnosis between iCCA and cHCC preoperatively, and therapeutic decisions would improve if it was applied in clinical practice.

Unusual Primary Neoplasms of the Adult Liver: Review of Imaging Appearances and Differential Diagnosis

The radiological appearance of common primary hepatic tumors such as hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) is widely recognized. Hepatic masses with unusual histology are occasionally encountered, but seldom suspected on imaging. However, many possess characteristic imaging findings, which when assessed along with the clinical and demographic background and serum tumor markers, may enable a prospective diagnosis. This review attempts to familiarize the reader with the clinicopathological characteristics, imaging manifestations, and differential diagnosis of these unusual liver tumors in adults. Biphenotypic primary liver carcinoma is suspected in masses showing distinct areas of HCC and CCA-type enhancement pattern in cirrhotic livers. Fibrolamellar carcinoma occurs in young individuals without underlying chronic liver disease and shows a characteristic T2-hypointense scar frequently showing calcification. Perivascular epithelioid cell tumors are differentials for any arterial hyperenhancing mass in the noncirrhotic liver, particularly in patients with tuberous sclerosis. Multifocal subcapsular tumors showing target-like morphology, capsular retraction and "lollipop" sign are suspicious for epithelioid hemangioendothelioma. On the other hand, multiple hemorrhagic lesions showing patchy areas of bizarre-shaped arterial phase hyperenhancement are suspicious for angiosarcoma. Primary hepatic lymphoma (PHL) is suspected when patients with immunosuppression present with solitary or multifocal masses that insinuate around vessels and bile ducts without causing luminal narrowing. Intense diffusion restriction and low-level homogeneous or target-like enhancement are also ancillary features of PHL. Primary hepatic neuroendocrine tumor shows uptake on Ga-68 DOTANOC PET/CT. Although a straightforward diagnosis may be difficult in these cases, awareness of the characteristic imaging appearances is helpful in suspecting the diagnosis.

Diagnostic performance of the LR-M criteria and spectrum of LI-RADS imaging features among primary hepatic carcinomas

PURPOSE

To evaluate the diagnostic performance of LR-M criteria for differentiating hepatocellular carcinoma, intrahepatic mass-forming cholangiocarcinoma, and combined hepatocellular-cholangiocarcinoma and to compare the imaging features of each type.

METHODS

In this retrospective study, 110 patients were surgically diagnosed with cholangiocarcinoma (n = 67) and combined hepatocellular-cholangiocarcinoma (n = 43) at a single tertiary hospital between 2013 and 2018. Among them, those with risk factors were enrolled (16 cholangiocarcinomas and 33 combined hepatocellular-cholangiocarcinomas). Forty-nine other patients with size-matched hepatocellular carcinoma were selected as a control group. Two independent readers evaluated the imaging findings of the preoperative MRIs based on LI-RADS version 2018 and assigned an LI-RADS category. The diagnostic performance of the LR-M criteria for diagnosing cholangiocarcinoma or combined hepatocellular-cholangiocarcinoma was evaluated, and the imaging features were compared. The imaging findings of the tumors in patients without risk factors (51 cholangiocarcinomas and 10 combined hepatocellular-cholangiocarcinomas) were evaluated for subgroup analysis.

RESULTS

In the non-hepatocellular carcinoma group, 33 patients were categorized into LR-M and 14 patients into LR-5 (67.3% and 28.6%, respectively), while 5 patients with hepatocellular carcinoma were categorized into LR-M and 38 patients into LR-5 (10.2% and 77.6%, respectively). Sensitivity and specificity of the LR-M criteria were 67.3% and 89.8%, respectively. When more than two LR-M features were present, cholangiocarcinoma or combined hepatocellular-cholangiocarcinoma were suggested with a specificity of 95.9%.

CONCLUSION

The diagnostic performance of the LR-M criteria is acceptable with moderate sensitivity and high specificity for both cholangiocarcinoma and combined hepatocellular-cholangiocarcinoma. Imaging findings of primary hepatic carcinomas should be understood as a spectrum.

Integrated nomograms to predict overall survival and recurrence-free survival in patients with combined hepatocellular cholangiocarcinoma (cHCC) after liver resection

The current clinical classification of primary liver cancer is unable to efficiently predict the prognosis of combined hepatocellular cholangiocarcinoma (cHCC). Accurate satellite nodules (SAT) and microvascular invasion (MVI) prediction in cHCC patients is very important for treatment decision making and prognostic evaluation. The aim of this work was to explore important factors affecting the prognosis of cHCC patients after liver resection and to develop preoperative nomograms to predict SAT and MVI in cHCC patients. The nomogram was developed using the data from 148 patients who underwent liver resection for cHCC patients at our hospital between January 2006 and December 2014. Based on the results of the multivariate analysis, a nomogram integrating all significant independent factors affecting overall survival and recurrence-free survival was constructed to predict the prognosis of cHCC. Next, risk factors for SAT and MVI were evaluated with logistic regression. Blood signatures were established using the LASSO regression, and then, we combined the clinical risk factors and blood signatures of the patients to establish predictive models for SAT and MVI. The C-index of the nomogram for predicting survival was 0.685 (95% CI, 0.638 to 0.732), which was significantly higher than the C-index for other liver cancer classification systems.

Can machine learning radiomics provide pre-operative differentiation of combined hepatocellular cholangiocarcinoma from hepatocellular carcinoma and cholangiocarcinoma to inform optimal treatment planning?

OBJECTIVE

To differentiate combined hepatocellular cholangiocarcinoma (cHCC-CC) from cholangiocarcinoma (CC) and hepatocellular carcinoma (HCC) using machine learning on MRI and CT radiomics features.

METHODS

This retrospective study included 85 patients aged 32 to 86 years with 86 histopathology-proven liver cancers: 24 cHCC-CC, 24 CC, and 38 HCC who had MRI and CT between 2004 and 2018. Initial CT reports and morphological evaluation of MRI features were used to assess the performance of radiologists read. Following tumor segmentation, 1419 radiomics features were extracted using PyRadiomics library and reduced to 20 principle components by principal component analysis. Support vector machine classifier was utilized to evaluate MRI and CT radiomics features for the prediction of cHCC-CC vs. non-cHCC-CC and HCC vs. non-HCC. Histopathology was the reference standard for all tumors.

RESULTS

Radiomics MRI features demonstrated the best performance for differentiation of cHCC-CC from non-cHCC-CC with the highest AUC of 0.77 (SD 0.19) while CT was of limited value. Contrast-enhanced MRI phases and pre-contrast and portal-phase CT showed excellent performance for the differentiation of HCC from non-HCC (AUC of 0.79 (SD 0.07) to 0.81 (SD 0.13) for MRI and AUC of 0.81 (SD 0.06) and 0.71 (SD 0.15) for CT phases, respectively). The misdiagnosis of cHCC-CC as HCC or CC using radiologists read was 69% for CT and 58% for MRI.

CONCLUSIONS

Our results demonstrate promising predictive performance of MRI and CT radiomics features using machine learning analysis for differentiation of cHCC-CC from HCC and CC with potential implications for treatment decisions.

KEY POINTS

• Retrospective study demonstrated promising predictive performance of MRI radiomics features in the differentiation of cHCC-CC from HCC and CC and of CT radiomics features in the differentiation of HCC from cHCC-CC and CC. • With future validation, radiomics analysis has the potential to inform current clinical practice for the pre-operative diagnosis of cHCC-CC and to enable optimal treatment decisions regards liver resection and transplantation.

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.

Major and ancillary features according to LI-RADS in the assessment of combined hepatocellular-cholangiocarcinoma

Background

The aim of the study was to investigate the performance of the Liver Imaging Reporting and Data System (LI-RADS) v2018 for combined hepatocellular-cholangiocarcinoma (cHCC-CCA) identifying the features that allow an accurate characterization.

Patients and methods

Sixty-two patients (median age, 63 years; range, 38–80 years), with pre-surgical biopsy diagnosis of hepatocellular carcinoma (HCC) that underwent hepatic resection, comprised our retrospective study. All patients were subject to multidetector computed tomography (MDCT); 23 patients underwent to magnetic resonance (MR) study. The radiologist reported the presence of the HCC by using LIRADS v2018 assessing major and ancillary features.

Results

Final histological diagnosis was HCC for 51 patients and cHCC-CCA for 11 patients. The median nodule size was 46.0 mm (range 10–190 mm). For cHCC-CCA the median size was 33.5 mm (range 20–80 mm), for true HCC the median size was 47.5 mm (range 10–190 mm). According to LIRADS categories: 54 (87.1%) nodules as defined as LR-5, 1 (1.6%) as LR-3, and 7 (11.3%) as LR-M. Thirty-nine nodules (63%) showed hyper-enhancement in arterial phase; among them 4 were cHCC-CCA (36.4% of cHCC-CCA) and 35 (68.6%) true HCC. Forty-three nodules (69.3%) showed washout appearance; 6 cHCC-CCAs (54.5% of cHCC-CCA) and 37 true HCC (72.5%) had this feature. Only two cHCC-CCA patients (18.2% of cHCC-CCA) showed capsule appearance. Five cHCC-CCA (71.4% of cHCC-CCA) showed hyperintensity on T2-W sequences while two (28.6%) showed inhomogeneous signal in T2-W. All cHCC-CCA showed restricted diffusion. Seven cHCC-CCA patients showed a progressive contrast enhancement and satellite nodules.

Conclusions

The presence of satellite nodules, hyperintense signal on T2-W, restricted diffusion, the absence of capsule appearance in nodule that shows peripheral and progressive contrast enhancement are suggestive features of cHCC-CCA.

Differentiation combined hepatocellular and cholangiocarcinoma from intrahepatic cholangiocarcinoma based on radiomics machine learning

BACKGROUND

Combined hepatocellular and cholangiocarcinoma (CHC) and intrahepatic cholangiocarcinoma (ICC) are hard to identify in clinical practice preoperatively. This study looked to develop and confirm a radiomics-based model for preoperative differentiation CHC from ICC.

METHODS

The model was developed in 86 patients with ICC and 46 CHC, confirmed in 37 ICC and 20 CHC, and data were collected from January 2014 to December 2018. The radiomics scores (Radscores) were built from radiomics features of contrast-enhanced computed tomography in 12 regions of interest (ROI). The Radscore and clinical-radiologic factors were integrated into the combined model using multivariable logistic regression. The best-combined model constructed the radiomics-based nomogram, and the performance was assessed concerning its calibration, discrimination, and clinical usefulness.

RESULTS

The radiomics features extracted from tumor ROI in the arterial phase (AP) with preprocessing were selected to build Radscore and yielded an area under the curve (AUC) of 0.800 and 0.789 in training and validation cohorts, respectively. The radiomics-based model contained Radscore and 4 clinical-radiologic factors showed the best performance (training cohort, AUC =0.942; validation cohort, AUC =0.942) and good calibration (training cohort, AUC =0.935; validation cohort, AUC =0.931).

CONCLUSIONS

The proposed radiomics-based model may be used conveniently to the preoperatively differentiate CHC from ICC.

Combined Hepatocellular Cholangiocarcinoma: A Population-Based Retrospective Study

OBJECTIVES

Combined hepatocellular cholangiocarcinoma (CHC) is a rare form of primary liver cancer with features of hepatocellular carcinoma and cholangiocarcinoma. The objective of this study was to investigate the incidence, demographics, tumor characteristics, treatment, and survival of patients with CHC.

METHODS

Data on CHC between 2004 and 2014 were extracted from the Surveillance, Epidemiology, and End Results Registry and analyzed.

RESULTS

Five hundred twenty-nine patients with CHC were identified; 367 were male. Median age at diagnosis was 62.5 ± 12 years. The overall incidence of CHC between 2004 and 2014 was 0.05 per 100,000 per year. Incidence increased with age, with the highest incidence in men occurring between 60 and 64 years and 75-79 years for women. Women had a higher incidence of CHC compared to men (0.08 vs 0.03 per 100,000 per year). Most tumors were poorly differentiated (30.8%) while the most common stage at presentation was stage 4 (26.8%). 39.5% of these tumors were resected while 6.8% received radiation and 34% received chemotherapy. One- and 5-year cause-specific survival for CHC was 41.9% and 17.7%, respectively, with a median survival of 8 months. Worse outcomes were noted among patients with tumor stage 3 (hazard ratio [HR] 2.03, 95% confidence interval [CI] 1.44-2.87, P = 0.000), stage 4 (HR 1.71, 95% CI 1.06-2.75, P = 0.027), those not treated with surgery (HR 4.94, 95% CI 3.64-6.68, P = 0.000), those who did not receive radiation (HR 1.71, 95% CI 1.08-2.70, P = 0.021), those who did not receive chemotherapy (HR 1.54, 95% CI 1.20-1.99, P = 0.001), and those with increasing tumor size on chemotherapy (HR 1.00, 95% CI 1.00-1.00, P = 0.013).

DISCUSSION

CHC is the combined presentation of 2 malignancies. Incidence appears to be increasing and is associated with age and male gender. While surgery, radiation, and chemotherapy are associated with improved outcomes, patients who did not undergo surgery are at highest risk for death.

Combined hepatocellular-cholangiocarcinoma successfully treated with sorafenib: case report and review of the literature

Sorafenib, a multiple kinase inhibitor, has been established as first-line standard systemic chemotherapy for patients with advanced hepatocellular carcinoma (HCC). We encountered a patient with combined hepatocellular and cholangiocarcinoma (CHC) who achieved complete remission in response to sorafenib treatment. A 58-year old man with hepatitis C virus (HCV)-induced liver cirrhosis was diagnosed with CHC in segments 6th and 7th of the liver and underwent partial surgical resection. Three months later, CHC recurred as metastases at multiple intrahepatic sites, lymph nodes, and bones, making surgery impossible. Treatment with sorafenib was initiated at 400 mg b.i.d., later reduced to 400 mg/day. After 6 months of sorafenib administration, he no longer showed abnormal uptake on fluorodeoxyglucose positron emission tomography. He was continued on sorafenib for 2.5 years, but later discontinued due to adverse events. He has shown no evidence of tumor recurrence more than 1 year after sorafenib discontinuation. His HCV was eradicated by direct-acting antivirals, and he remains in good health.

Pathological variants of hepatocellular carcinoma on MRI: emphasis on histopathologic correlation

Hepatocellular carcinoma (HCC) is a unique tumor because it is one of the few cancers which can be treated based on imaging alone. Magnetic resonance imaging (MRI) carries higher sensitivity and specificity for the diagnosis of HCC than either computed tomography (CT) or ultrasound. MRI is imaging modality of choice for the evaluation of complex liver lesions and HCC because of its inherent ability to depict cellularity, fat, and hepatocyte composition with high soft tissue contrast. The imaging features of progressed HCC are well described. However, many HCC tumors do not demonstrate classical imaging features, posing a diagnostic dilemma to radiologists. Some of these can be attributed to variations in tumor biology and histology, which result in radiological features that differ from the typical progressed HCC. This pictorial review seeks to demonstrate the appearance of different variants of HCC on MRI imaging, in relation to their histopathologic features.

Combined hepatocellular cholangiocarcinoma (cHCC-CC): an update of genetics, molecular biology, and therapeutic interventions

Combined hepatocellular cholangiocarcinoma (CC) is a rare and aggressive primary hepatic malignancy with significant histological and biological heterogeneity. It presents with more aggressive behavior and worse survival outcomes than either hepatocellular carcinoma or CC and remains a diagnostic challenge. An accurate diagnosis is crucial for its optimal management. Major hepatectomy with hilar node resection remains the mainstay of treatment in operable cases. Advances in the genetic and molecular characterization of this tumor will contribute to the better understanding of its pathogenesis and shape its future management.