Tumors of the liver and intrahepatic bile ducts: radiologic-pathologic correlation

Focal Lesions of the Liver and Radiomics: What Do We Know?

Despite differences in pathological analysis, focal liver lesions are not always distinguishable in contrast-enhanced magnetic resonance imaging (MRI), contrast-enhanced computed tomography (CT), and positron emission tomography (PET). This issue can cause problems of differential diagnosis, treatment, and follow-up, especially in patients affected by HBV/HCV chronic liver disease or fatty liver disease. Radiomics is an innovative imaging approach that extracts and analyzes non-visible quantitative imaging features, supporting the radiologist in the most challenging differential diagnosis when the best-known methods are not conclusive. The purpose of this review is to evaluate the most significant CT and MRI texture features, which can discriminate between the main benign and malignant focal liver lesions and can be helpful to predict the response to pharmacological or surgical therapy and the patient's prognosis.

An MR-based radiomics model for differentiation between hepatocellular carcinoma and focal nodular hyperplasia in non-cirrhotic liver

Purpose

We aimed to develop and validate a radiomics model for differentiating hepatocellular carcinoma (HCC) from focal nodular hyperplasia (FNH) in non-cirrhotic livers using Gd-DTPA contrast-enhanced magnetic resonance imaging (MRI).

Methods

We retrospectively enrolled 149 HCC and 75 FNH patients treated between May 2015 and May 2019 at our center. Patients were randomly allocated to a training (n=156) and validation set (n=68). In total, 2260 radiomics features were extracted from the arterial phase and portal venous phase of Gd-DTPA contrast-enhanced MRI. Using Max-Relevance and Min-Redundancy, random forest, least absolute shrinkage, and selection operator algorithm for dimensionality reduction, multivariable logistic regression was used to build the radiomics model. A clinical model and combined model were also established. The diagnostic performance of the models was compared.

Results

Eight radiomics features were chosen for the radiomics model, and four clinical factors (age, sex, HbsAg, and enhancement pattern) were chosen for the clinical model. A combined model was built using the factors from the previous models. The classification accuracy of the combined model differentiated HCC from FNH in both the training and validation sets (0.956 and 0.941, respectively). The area under the receiver operating characteristic curve of the combined model was significantly better than that of the clinical model for both the training (0.984 vs. 0.937, p=0.002) and validation (0.972 vs. 0.903, p=0.032) sets.

Conclusions

The combined model provided a non-invasive quantitative method for differentiating HCC from FNH in non-cirrhotic liver with high accuracy. Our model may assist clinicians in the clinical decision-making process.

Case Report: Review of CT Findings and Histopathological Characteristics of Primary Liver Carcinosarcoma

Objectives: The aim of the present study was to describe the computed tomography (CT) characteristics of primary liver carcinosarcoma (PLCS) and to explore the pathological basis for the diagnosis of primary hepatocellular carcinoma sarcoma.

Methods: Three male patients with PLCS were included in the present retrospective research, and the age was ranged from 52 to 63 years. The plain CT scan and third-stage enhancement scan were performed on patients. The pathological characteristics were analyzed. Stomachache was the main clinical symptoms of the three patients. Cirrhosis background was confirmed in one patients, and chronic Hepatitis B background was confirmed in other two patients.

Results: According to the results of CT, the inner diameter of the tumors ranged from 8.6 to 27.0 cm. The fibrous pseudocapsule around the tumor tissues was observed in two patients. Tumor tissues from all three patients were composed of sarcomatous and carcinomatous components. For carcinomatous components, hepatocellular carcinoma was observed in one patient and cholangiocarcinoma was observed in the other two patients. For sarcomatous components, angiosarcoma was observed in two patients and malignant fibrous histiocytoma was observed in another one patient. The tumor tissues were visualized as heterogeneous low density with large sheets of necrotic cystic lesions or thick-walled areas of multilocular cystic lesions using the plain CT scan. Edge-to-center filling and strengthening lesions, mild to moderate enhanced parenchyma at the arterial phase, and isodensity between the tumor parenchyma and the surrounding liver parenchyma at the portal vein phase or delayed phase were observed using the third-stage enhancement scan.

Conclusions: CT characteristics observed in the present study were of great benefit for the diagnosis of PLCS.

Preoperative diagnosis and prediction of hepatocellular carcinoma: Radiomics analysis based on multi-modal ultrasound images

BACKGROUND

This study aims to establish a radiomics analysis system for the diagnosis and clinical behaviour prediction of hepatocellular carcinoma (HCC) based on multi-parametric ultrasound imaging.

METHODS

A total of 177 patients with focal liver lesions (FLLs) were included in the study. Every patient underwent multi-modal ultrasound examination, including B-mode ultrasound (BMUS), shear wave elastography (SWE), and shear wave viscosity (SWV) imaging. The radiomics analysis system was built on sparse representation theory (SRT) and support vector machine (SVM) for asymmetric data. Through the sparse regulation from the SRT, the proposed radiomics system can effectively avoid over-fitting issues that occur in regular radiomics analysis. The purpose of the proposed system includes differential diagnosis between benign and malignant FLLs, pathologic diagnosis of HCC, and clinical prognostic prediction. Three biomarkers, including programmed cell death protein 1 (PD-1), antigen Ki-67 (Ki-67) and microvascular invasion (MVI), were included and analysed. We calculated the accuracy (ACC), sensitivity (SENS), specificity (SPEC) and area under the receiver operating characteristic curve (AUC) to evaluate the performance of the radiomics models.

RESULTS

A total of 2560 features were extracted from the multi-modal ultrasound images for each patient. Five radiomics models were built, and leave-one-out cross-validation (LOOCV) was used to evaluate the models. In LOOCV, the AUC was 0.94 for benign and malignant classification (95% confidence interval [CI]: 0.88 to 0.98), 0.97 for malignant subtyping (95% CI: 0.93 to 0.99), 0.97 for PD-1 prediction (95% CI: 0.89 to 0.98), 0.94 for Ki-67 prediction (95% CI: 0.87 to 0.97), and 0.98 for MVI prediction (95% CI: 0.93 to 0.99). The performance of each model improved when the viscosity modality was included.

CONCLUSIONS

Radiomics analysis based on multi-modal ultrasound images could aid in comprehensive liver tumor evaluations, including diagnosis, differential diagnosis, and clinical prognosis.

Primary carcinosarcoma of the liver: imaging features and clinical findings in six cases and a review of the literature

Background

Carcinosarcoma of the liver is a very rare tumor composed of a mixture of carcinomatous and sarcomatous elements. Less than 25 adequately documented cases have been reported, with inadequate description of imaging features. In order to improve the awareness of this rare tumor, this study aimed to analyze the clinicopathologic and imaging features of six cases of hepatic carcinosarcoma (HCS) confirmed by surgical pathologic evaluation.

Methods

We retrospectively studied the clinicopathologic and imaging features of six cases of HCS (matching the World Health Organization definition) and discussed the differential diagnosis on the basis of imaging findings. The patients, including five men and one woman, were 38 to 69 years of age. Five patients underwent CT scans, one underwent MRI scans.

Results

While 3 patients were positive for hepatitis-B surface antigen, 2 had cirrhosis. The largest tumor diameter ranged from 5.0 to 21.0 cm. Satellite nodules, venous thrombi, and organ invasion (gastric wall, gallbladder, and right adrenal gland) were identified. Pathologically, the carcinomatous components corresponded to hepatocellular carcinoma in three cases, cholangiocellular carcinoma in one case, and adenocarcinoma in two cases. The sarcomatous components exhibited complex features, with undifferentiated spindle cells in five cases and a leiomyosarcoma in one. All tumors showed heterogeneous density/intensity with extensive cystic change and necrosis; spot calcification was observed in one case. Capsule was not identified. While four tumors showed heterogeneous hypervascular enhancement, two showed hypovascular enhancement. All patients underwent surgical resection. The follow-up period ranged from 2 to 18 months. Four patients died from recurrence and metastasis.

Conclusions

The clinical and imaging features of HCS are heterogeneous. Due to the heterogenous nature and very low morbidity of HCS, combination of careful analysis of imaging findings and clinical features might be useful for a more accurate diagnosis of HCS.

MR imaging of the biliary system

Although ultrasound, computed tomography, and cholescintigraphy play essential roles in the evaluation of suspected biliary abnormalities, magnetic resonance (MR) imaging and MR cholangiopancreatography can be used to evaluate inconclusive findings and provide a comprehensive noninvasive assessment of the biliary tract and gallbladder. This article reviews standard MR and MR cholangiopancreatography techniques, clinical applications, and pitfalls. Normal biliary anatomy and variants are discussed, particularly as they pertain to preoperative planning. A spectrum of benign and malignant biliary processes is reviewed, emphasizing MR findings that aid in characterization.

Primary Hepatic Neuroendocrine Tumor: What Do We Know Now?

Primary hepatic neuroendocrine tumors (PHNETs) are rear neoplasm. Diagnosis is an evolution, and requires a systematic clinical exclusion with histological confirmation. Treatment is surgical with excellent prognosis, and a long-term follow-up is required due to high tumor recurring rate. Knowledge from this species of tumor remains limited due to paucity of cases. This article elaborates the key features, diagnosis algorithm, current management, other treatment options and extensive review of literature on this rear tumor.