Combined Hepatocellular Cholangiocarcinoma (Biphenotypic) Tumors: Potential Role of Contrast-Enhanced Ultrasound in Diagnosis

Current advances and future directions in combined hepatocellular and cholangiocarcinoma

The low incidence of combined hepatocellular cholangiocarcinoma (cHCC-CCA) is an important factor limiting research progression. Our study extensively included nearly three decades of relevant literature and assembled the most comprehensive database comprising 5,742 patients with cHCC-CCA. We summarized the characteristics, tumor markers, and clinical features of these patients. Additionally, we present the evolution of cHCC-CCA classification and explain the underlying rationale for these classification standards. We reviewed cHCC-CCA diagnostic advances using imaging features, tumor markers, and postoperative pathology, as well as treatment options such as surgical, adjuvant, and immune-targeted therapies. In addition, recent advances in more effective chemotherapeutic regimens and immune-targeted therapies were explored. Furthermore, we described the molecular mutation features and potential specific markers of cHCC-CCA. The prognostic value of Nestin has been proven, and we speculate that Nestin will also play a role in classification and diagnosis. However, further research is needed. Moreover, we believe that the possibility of using machine learning liquid biopsy for preoperative diagnosis and establishing a scoring system are directions for future research.

Non-invasive imaging in the diagnosis of combined hepatocellular carcinoma and cholangiocarcinoma

Combined hepatocellular-cholangiocarcinoma (cHCC-CC) is a rare type of primary liver cancer. It is a complex "biphenotypic" tumor type consisting of bipotential hepatic progenitor cells that can differentiate into cholangiocytes subtype and hepatocytes subtype. The prognosis of patients with cHCC-CC is quite poor with its specific and more aggressive nature. Furthermore, there are no definite demographic or clinical features of cHCC-CC, thus a clear preoperative identification and accurate non-invasive imaging diagnostic analysis of cHCC-CC are of great value. In this review, we first summarized the epidemiological features, pathological findings, molecular biological information and serological indicators of cHCC-CC disease. Then we reviewed the important applications of non-invasive imaging modalities-particularly ultrasound (US)-in cHCC-CC, covering both diagnostic and prognostic assessment of patients with cHCC-CC. Finally, we presented the shortcomings and potential outlooks for imaging studies in cHCC-CC.

Contrast-Enhanced Ultrasound-Based Nomogram: A Potential Predictor of Individually Postoperative Early Recurrence for Patients With Combined Hepatocellular-Cholangiocarcinoma

PURPOSES

To evaluate the postsurgical prognostic implication of contrast-enhanced ultrasound (CEUS) for combined hepatocellular-cholangiocarcinoma (CHC). To build a CEUS-based early recurrence prediction classifier for CHC, in comparison with tumor-node-metastasis (TNM) staging.

METHODS

The CEUS features and clinicopathological findings of each case were analyzed, and the Liver Imaging Reporting and Data System categories were assigned. The recurrence-free survival associated factors were evaluated by Cox proportional hazard model. Incorporating the independent factors, nomograms were built to estimate the possibilities of 3-month, 6-month, and 1-year recurrence and whose prognostic value was determined by time-dependent receiver operating characteristics, calibration curves, and hazard layering efficiency validation, comparing with TNM staging system.

RESULTS

In the multivariable analysis, the levels of carbohydrate antigen 19-9, prothrombin time and total bilirubin, and tumor shape, the Liver Imaging Reporting and Data System category were independent factors for recurrence-free survival. The LR-M category showed longer recurrence-free survival than did the LR-4/5 category. The 3-month, 6-month, and 1-year area under the curves of the CEUS-clinical nomogram, clinical nomogram, and TNM staging system were 0.518, 0.552, and 0.843 versus 0.354, 0.240, and 0.624 (P = .048, .049, and .471) vs. 0.562, 0.545, and 0.843 (P = .630, .564, and .007), respectively. The calibration curves of the CEUS-clinical model at different prediction time pionts were all close to the ideal line. The CEUS-clinical model effectively stratified patients into groups of high and low risk of recurrence in both training and validation set, while the TNM staging system only works on the training set.

CONCLUSIONS

Our CEUS-clinical nomogram is a reliable early recurrence prediction tool for hepatocellular-cholangiocarcinoma and helps postoperative risk stratification.

CEUS and CT/MRI LI-RADS in Association With Serum Biomarkers for Differentiation of Combined Hepatocellular-Cholangiocarcinoma From Hepatocellular Carcinoma

Background

Combined Hepatocellular-cholangiocarcinoma (cHCC-CCAs) are with both unambiguously differentiated hepatocellular and biliary components. cHCC-CCAs show various imaging features similar to hepatocellular carcinoma (HCCs) and intrahepatic cholangiocarcinoma (ICCs), which makes the differential diagnosis between them challenging. The accurate diagnosis of cHCC-CCAs is of great importance in selecting treatment methods and performing patient management.

Purpose

To investigate the diagnostic efficacy of CEUS and CT/MRI LI-RADS in association with tumor biomarkers for differentiation of cHCC-CCAs from HCCs.

Methods

A total of 54 cHCC-CCAs and 55 HCCs in two centers were retrospectively collected. The diagnostic criteria for cHCC-CCAs if one or more of the following conditions were satisfied: (1) arterial phase hyperenhancement (APHE) on CEUS and LR-M on CT/MRI; (2) LR-5 on both CEUS and CT/MRI with elevated carbohydrate antigen 19-9 (CA19-9); (3) LR-M on both CEUS and CT/MRI with elevated alphafetoprotein (AFP). The sensitivity, specificity, accuracy and area under the receiver operating characteristic curve (AUC) were calculated.

Results

The rates of APHE and Rim-APHE on CEUS in cHCC-CCAs were 81.5% and 9.3%, respectively. The rate of early and marked washout on CEUS in cHCC-CCAs were 59.3% and 27.8%, respectively. 64.8% and 25.9% of cHCC-CCAs showed APHE and Rim-APHE on CT/MRI, respectively. 46.3% and 35.2% of cHCC-CCAs showed washout and delay enhancement on CT/MRI, respectively. The kappa value of LI-RADS categories of cHCC-CCAs on CEUS and CT/MRI was 0.319 (P=0.008). The sensitivity, specificity, accuracy and AUC of the aforementioned diagnostic criteria for cHCC-CCAs were 64.8%, 84.4%, 76.1% and 0.746, respectively.

Conclusion

The combination of the CEUS and CT/MRI LI-RADS with serum tumor markers shows promising diagnostic performance of cHCC-CCAs.

Ultrasound-Based Radiomics Analysis for Preoperatively Predicting Different Histopathological Subtypes of Primary Liver Cancer

Background

Preoperative identification of hepatocellular carcinoma (HCC), combined hepatocellular–cholangiocarcinoma (cHCC-ICC), and intrahepatic cholangiocarcinoma (ICC) is essential for treatment decision making. We aimed to use ultrasound-based radiomics analysis to non-invasively distinguish histopathological subtypes of primary liver cancer (PLC) before surgery.

Methods

We retrospectively analyzed ultrasound images of 668 PLC patients, comprising 531 HCC patients, 48 cHCC-ICC patients, and 89 ICC patients. The boundary of a tumor was manually determined on the largest imaging slice of the ultrasound medicine image by ITK-SNAP software (version 3.8.0), and then, the high-throughput radiomics features were extracted from the obtained region of interest (ROI) of the tumor. The combination of different dimension-reduction technologies and machine learning approaches was used to identify important features and develop the moderate radiomics model. The comprehensive ability of the radiomics model can be evaluated by the area under the receiver operating characteristic curve (AUC).

Results

After digitally processing tumor ultrasound images, 5,234 high-throughput radiomics features were obtained. We used the Spearman + least absolute shrinkage and selection operator (LASSO) regression method for feature selection and logistics regression for modeling to develop the HCC-vs-non-HCC radiomics model (composed of 16 features). The Spearman + statistical test + random forest methods were used for feature selection, and logistics regression was applied for modeling to develop the ICC-vs-cHCC-ICC radiomics model (composed of 19 features). The overall performance of the radiomics model in identifying different histopathological types of PLC was moderate, with AUC values of 0.854 (training cohort) and 0.775 (test cohort) in the HCC-vs-non-HCC radiomics model and 0.920 (training cohort) and 0.728 (test cohort) in the ICC-vs-cHCC-ICC radiomics model.

Conclusion

Ultrasound-based radiomics models can help distinguish histopathological subtypes of PLC and provide effective clinical decision making for the accurate diagnosis and treatment of PLC.

Contrast-enhanced ultrasound imaging features and clinical characteristics of combined hepatocellular cholangiocarcinoma: comparison with hepatocellular carcinoma and cholangiocarcinoma

Purpose

The purpose of this study was to retrospectively compare the clinical characteristics and imaging features on (CEUS) of combined hepatocellular cholangiocarcinoma (CHC) with those of hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC).

Methods

The clinical information and CEUS features of 45 patients with CHC from 2015 to 2019 and 1-to-1-matched control subjects with HCC and CC (45 each) were compared.

Results

Simultaneous elevation of α-fetoprotein (AFP) and cancer antigen (CA) 19-9 was more common in CHC than in HCC and CC. In the arterial phase, hyperenhancement (homogeneous and heterogeneous) was more common in CHC (73.3%) and HCC (100%), while peripheral rim-like enhancement was more common in CC (55.6%). In the portal phase, marked washout was significantly more frequent in CHC and CC than in HCC (42.2% and 53.3% vs. 6.7%). In the delayed phase, marked washout was more common in CHC (82.2%) and CC (93.3%) than in HCC (40.0%). The washout time (WT) was much shorter in CHC and CC than in HCC (33.8±13.1 seconds and 30.1±11.6 seconds vs. 58.4±23.5 seconds). Using the combination of simultaneous elevation of AFP and CA 19-9 with marked washout in the delayed phase and a WT <38 seconds or arterial hyperenhancement to differentiate CHC from HCC or CC, the accuracy, sensitivity, and specificity were 74.4%, 93.3%, and 55.6% and 71.1%, 80.0%, and 62.2%, respectively.

Conclusion

Although some CEUS imaging features of CHC, HCC, and CC overlap, the combination of tumor markers and CEUS features can be helpful in differentiating CHC from HCC and CC.

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.

Value of ultrasonography in the diagnosis of primary hepatic carcinoma and thyroid carcinoma

The present study explored the value of ultrasonography in the diagnosis of primary hepatic carcinoma (PHC) and thyroid carcinoma (TC) by assessing their sonographic features. A total of 426 patients diagnosed with liver space-occupying lesions by ultrasonic examination admitted to Liaocheng People's Hospital from March 2014 to October 2017 were enrolled in this study. These patients were divided into two groups: A total of 226 patients with 237 foci in the PHC group and 200 patients with 216 foci in the benign liver lesion group. During the same period, 367 patients diagnosed with thyroid nodules (382 nodules) by ultrasonic examination were also enrolled in this study. These patients were divided into further two groups: A total of 193 patients with 203 nodules in the TC group and 174 patients with 179 nodules in the benign thyroid nodule group. Two-dimensional and color Doppler ultrasonography were performed on all the patients in the four groups. Differences in the sonographic features such as focus morphology, focus size, internal echo, halo and blood flow distribution were statistically significant between patients in the PHC and the benign liver lesion group (p<0.001). Differences in the sonographic features such as nodule boundary, nodule size, internal echo, microcalcification, lymph node status and blood flow were statistically significant between patients in the TC and the benign thyroid nodule group (p<0.01). PHC can be differentiated from benign liver lesions by evaluation of focus morphology, focus size, internal echo, halo, and blood flow. TC can be differentiated from benign thyroid nodules by evaluation of nodule boundary, nodule size, internal echo, microcalcification, lymph node status, and blood flow. Ultrasonic diagnosis of PHC and TC is not only accurate, but also convenient, fast, cost-efficient and non-invasive. Thus, application of ultrasonography in the diagnosis of PHC and TC should be expanded for the benefits of patients.

Intrahepatic cholangiocarcinoma in the setting of HBV-related cirrhosis: Differentiation with hepatocellular carcinoma by using Intravoxel incoherent motion diffusion-weighted MR imaging

Accurate preoperative differentiation of intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) in the setting of cirrhotic liver is of great clinical significance because the treatment and prognosis of these entities differ markedly. Through a retrospectively research, we sought to determine the diagnostic performances of intravoxel incoherent motion (IVIM) and diffusion weighted imaging (DWI) parameters in the differentiating of ICC and HCC. According to the results, we found that apparent diffusion coefficient (ADC) derived from mono-exponential model and true ADC (ADC^slow) derived from bi-exponential model can be used to distinguish the ICC and HCC, and ADC^slowentailed the higher diagnostic performance than ADC. However, pseudo-ADC (ADC^fast) and perfusion fraction (f) can not be used to differentiate ICC and HCC. These results suggested that IVIM and DWI parameters can be useful in differentiating ICC and HCC and might be helpful in selecting the treatment plan and predicting prognosis.