Contribution of virtual biopsy to the screening of microvascular invasion in hepatocellular carcinoma: A pilot study

Advances in multi-omics studies of microvascular invasion in hepatocellular carcinoma

Microvascular invasion (MVI) represents a pivotal independent prognostic factor for the recurrence of hepatocellular carcinoma (HCC) after surgery. It contributes to early intervention for potentially recurrent HCC to enhance patient outcomes and increase survival rates. Traditionally, the diagnosis of MVI has relied on postoperative pathological analysis, and accurate preoperative detection methodologies are lacking. Recent research suggests that multi-omics strategies play a role in definitively diagnosing MVI before surgery and offering personalized selection for clinical decision-making in HCC management. This review meticulously examines a multi-omics approach for the preoperative prediction of MVI in HCC patients, aiming to innovate diagnostic paradigms to anticipate postsurgical recurrence, thereby facilitating earlier and more personalized therapeutic strategies.

Predictive machine learning model for microvascular invasion identification in hepatocellular carcinoma based on the LI-RADS system

Purposes

This study aimed to establish a predictive model of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) by contrast-enhanced computed tomography (CT), which relied on a combination of machine learning approach and imaging features covering Liver Imaging and Reporting and Data System (LI-RADS) features.

Methods

The retrospective study included 279 patients with surgery who underwent preoperative enhanced CT. They were randomly allocated to training set, validation set, and test set (167 patients vs. 56 patients vs. 56 patients, respectively). Significant imaging findings for predicting MVI were identified through the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression method. Predictive models were performed by machine learning algorithm, support vector machine (SVM), in the training set and validation set, and evaluated in the test set. Further, a combined model adding clinical findings to the radiologic model was developed. Based on the LI-RADS category, subgroup analyses were conducted.

Results

We included 116 patients with MVI which were diagnosed through pathological confirmation. Six imaging features were selected about MVI prediction: four LI-RADS features (corona enhancement, enhancing capsule, non-rim aterial phase hyperehancement, tumor size) and two non-LI-RADS features (internal arteries, non-smooth tumor margin). The radiological feature with the best accuracy was corona enhancement followed by internal arteries and tumor size. The accuracies of the radiological model and combined model were 0.725–0.714 and 0.802–0.732 in the training set, validation set, and test set, respectively. In the LR-4/5 subgroup, a sensitivity of 100% and an NPV of 100% were obtained by the high-sensitivity threshold. A specificity of 100% and a PPV of 100% were acquired through the high specificity threshold in the LR-M subgroup.

Conclusion

A combination of LI-RADS features and non-LI-RADS features and serum alpha-fetoprotein value could be applied as a preoperative biomarker for predicting MVI by the machine learning approach. Furthermore, its good performance in the subgroup by LI-RADS category may help optimize the management of HCC patients.

Macrotrabecular-Massive Hepatocellular Carcinoma: Light and Shadow in Current Knowledge

The subject of this narrative review is macrotrabecular-massive hepatocellular carcinoma (MTM‐HCC). Despite their rarity, these tumours are of general interest because of their epidemiological and clinical features and for representing a distinct model of the interaction between the angiogenetic system and neoplastic cells. The MTM‐HCC subtype is associated with various adverse biological and pathological parameters (the Alfa-foetoprotein (AFP) serum level, tumour size, vascular invasion, and satellite nodules) and is a key determinant of patient prognosis, with a strong and independent predictive value for early and overall tumour recurrence. Gene expression profiling has demonstrated that angiogenesis activation is a hallmark feature of MTM-HCC, with overexpression of both angiopoietin 2 (ANGPT2) and vascular endothelial growth factor A (VEGFA).

Preoperative diagnosis and prediction of microvascular invasion in hepatocellularcarcinoma by ultrasound elastography

Background

To assess the values of two elastography techniques combined with serological examination and clinical features in preoperative diagnosis of microvascular invasion in HCC patients.

Methods

A total of 74 patients with single Hepatocellular carcinoma (HCC) were included in this study. Shear wave measurement and real-time tissue elastography were used to evaluate the hardness of tumor-adjacent tissues and tumor tissues, as well as the strain rate ratio per lesion before surgery. According to the pathological results, the ultrasound parameters and clinical laboratory indicators related to microvascular invasion were analyzed, and the effectiveness of each parameter in predicting the occurrence of microvascular invasion was compared.

Results

33/74 patients exhibited microvascular invasion. Univariate analysis showed that the hardness of tumor-adjacent tissues (P = 0.003), elastic strain rate ratio (P = 0.032), maximum tumor diameter (P < 0.001), and alpha-fetoprotein (AFP) level (P = 0.007) was significantly different in the patients with and without microvascular invasion. The binary logistic regression analysis showed that the maximum tumor diameter (P = 0.001) was an independent risk factor for predicting microvascular invasion, while the hardness of tumor-adjacent tissues (P = 0.028) was a protective factor. The receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) of the hardness of tumor-adjacent tissues, the maximum diameter of the tumor, and the predictive model Logit(P) in predicting the occurrence of MVI was 0.718, 0.775 and 0.806, respectively.

Conclusion

The hardness of tumor-adjacent tissues, maximum tumor diameter, and the preoperative prediction model predict the occurrence of MVI in HCC patients.

Progression of Prothrombin Induced by Vitamin K Absence-II in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer and the third leading cause of cancer-related death worldwide. Due to the lack of efficient tools for early detection, asymptomatic HCC patients are diagnosed at an advanced stage, leading to a poor prognosis. To improve survival, serum biomarker prothrombin induced by vitamin K absence-II (PIVKA-II) was under investigation. PIVKA-II is an abnormal protein produced in HCC. The coagulation function was insufficient due to the lack of Gla residues. Elevated PIVKA-II was associated with bad tumor behavior in terms of proliferation, metastasis, and invasion. Three major signaling pathways were proposed to clarify the mechanism. With the advantages including affordability, minimal invasiveness, convenience, and efficiency, PIVKA-II could improve HCC management consisting of four aspects. First, PIVKA-II was an effective and dynamic tool for improving HCC surveillance in high-risk population. Changes in the serum levels of PIVKA-II provided valuable molecular alteration information before imaging discovery. Second, PIVKA-II offered a complementary approach for HCC early detection. Compared to traditional diagnostic approaches, the combination of PIVKA-II and other biomarkers had better performance. Third, PIVKA-II was an indicator for the assessment of response to treatment in HCC. Preoperative assessment was for selecting personalized therapy, and postoperative measurement was for assessing treatment efficacy. Fourth, PIVKA-II was considered as a prognostic predictor for HCC. Patients with elevated PIVKA-II were more likely to develop microvascular invasion, metastasis, and recurrence.

Hepatocellular Carcinomas: Towards a pathomolecular approach

Molecular analysis of primary liver malignancies has provided a refinement of the pathological diagnosis of this entity and the identification of an increasing number of tumor subtypes of hepatocellular proliferation, either malignant (hepatocellular carcinomas) or benign (hepatocellular adenomas). Besides the diagnosis, a combined pathomolecular approach can also provide further insights into patient prognosis, and help select patients who can benefit from targeted therapies. Hepatocellular carcinomas define a heterogeneous group of malignant hepatocellular proliferation at various levels: macroscopic, histological and molecular. While most carcinomas occur in patients with chronic liver diseases and advanced fibrosis in the background liver, some arise from the malignant transformation of a pre-existing hepatocellular adenoma. TERT promoter mutations are the most frequent genomic alterations observed in the process of malignancy, and they occur early in the process of liver carcinogenesis. Overall, a more active biopsy strategy should be considered a key step in the management of patients with HCC.

Hepatocellular carcinoma: a clinical and pathological overview

HCC incidence rates have been rising in the past 3 decades and by 2025 > 1 million individuals will be affected annually. High-throughput sequencing technologies led to the identification of several molecular HCC subclasses that can be broadly grouped into 2 major subgroups, each characterized by specific morphological and phenotypical features. It is likely that this increasing knowledge and a more appropriate characterization of HCC at the pathological level will impact HCC patient management.

Update on Hepatocellular Carcinoma: a Brief Review from Pathologist Standpoint

Hepatocellular carcinoma is one of the most common cancers and an important health problem all over the world. Its prognosis is poor. For better patient care, early diagnosis is essential. Although new imaging techniques have a big impact on hepatocellular carcinoma diagnosis, histopathological examination is still the gold standard for precise diagnosis. Histopathological evaluation gives exact diagnosis in the meaning of tumor size, histological subtypes, grading, and differential diagnosis from metastasis and other tumors. Immunohistochemistry as a part of diagnostic histopathological technique plays an important role in routine practice. Immunohistochemistry is useful for confirming of hepatocytic origin, supporting hepatocellular malignancy, and differential diagnosis. It also gives prognostic information. There are growing attempts to classify tumors by their molecular genetic signatures. This is also actual for hepatocellular carcinoma. This mini review focuses on the histopathology of hepatocellular carcinoma including subtypes; differential diagnosis and immunohistochemistry as an ancillary diagnostic tool, updated or added entities, i.e., combined hepatocellular-cholangiocarcinoma; small hepatocellular carcinoma; correlation with molecular studies; and future perspectives.

Prediction of Microvascular Invasion in Hepatocellular Carcinoma With a Multi-Disciplinary Team-Like Radiomics Fusion Model on Dynamic Contrast-Enhanced Computed Tomography

Objective

To investigate microvascular invasion (MVI) of HCC through a noninvasive multi-disciplinary team (MDT)-like radiomics fusion model on dynamic contrast enhanced (DCE) computed tomography (CT).

Methods

This retrospective study included 111 patients with pathologically proven hepatocellular carcinoma, which comprised 57 MVI-positive and 54 MVI-negative patients. Target volume of interest (VOI) was delineated on four DCE CT phases. The volume of tumor core (V_tc) and seven peripheral tumor regions (V_pt, with varying distances of 2, 4, 6, 8, 10, 12, and 14 mm to tumor margin) were obtained. Radiomics features extracted from different combinations of phase(s) and VOI(s) were cross-validated by 150 classification models. The best phase and VOI (or combinations) were determined. The top predictive models were ranked and screened by cross-validation on the training/validation set. The model fusion, a procedure analogous to multidisciplinary consultation, was performed on the top-3 models to generate a final model, which was validated on an independent testing set.

Results

Image features extracted from V_tc+V_pt(12mm) in the portal venous phase (PVP) showed dominant predictive performances. The top ranked features from V_tc+V_pt(12mm) in PVP included one gray level size zone matrix (GLSZM)-based feature and four first-order based features. Model fusion outperformed a single model in MVI prediction. The weighted fusion method achieved the best predictive performance with an AUC of 0.81, accuracy of 78.3%, sensitivity of 81.8%, and specificity of 75% on the independent testing set.

Conclusion

Image features extracted from the PVP with V_tc+V_pt(12mm) are the most reliable features indicative of MVI. The MDT-like radiomics fusion model is a promising tool to generate accurate and reproducible results in MVI status prediction in HCC.

Predictors for the progression of hepatic cirrhosis to hepatocellular carcinoma under long-term antiviral therapy

OBJECTIVE

Patients diagnosed with hepatitis B virus (HBV)-related hepatic cirrhosis have the potential for progression to hepatocellular carcinoma (HCC) even while undergoing long-term nucleos(t)ide analog (NA) therapy. This study investigated the predictors for the progression of hepatic cirrhosis to HCC under long-term NA therapy.

METHODS

This retrospective study enrolled 898 patients diagnosed with HBV-related hepatic cirrhosis. They received NA therapy between January 2012 and January 2015. The values for the liver stiffness measurement (LSM), laboratory tests, and disease history were collected. The diagnostic specificity of the serum, was assessed with a receiver operating characteristic curve.

RESULTS

The overall 2- and 3-year cumulative incidence of HCC was 6.8% and 15.15%, respectively. The LSM values were higher in the patients who had progressed to HCC. The serum PIVKA-II levels were more efficient than the serum AFP levels for the diagnosis of early HCC as the larger area under curve (0.866 vs. 0.687). The multivariate logistic regression analysis showed that HCC occurrence was significantly associated with the baseline LSM value (odds ratio = 1.035). At the end of the study, the death rate for the patients with larger LSM values was higher than that for those with lower LSM values (67.88% vs. 39.90%).

CONCLUSION

Patients with HBV-related cirrhosis have the potential for progression to HCC even under long-term NA therapy. The LSM value and the serum PIVKA-II level are significant predictors of HCC occurrence.

Optimizing curative management of hepatocellular carcinoma

The goal of curative management of hepatocellular carcinoma is to provide the best chance of remission. However, recurrence rates for both local and distant relapse are high. Patient subgroups at higher risk of these events can be identified based on histological patterns that are closely linked to specific molecular subtypes. Patient outcome has improved with more effective therapeutic strategies thanks to technological advances in surgical techniques and percutaneous ablation. The main goal of controlling the cause of liver disease is to decrease distant/late recurrence and prevent deterioration of hepatic function. Ongoing trials testing the combination of neoadjuvant and/or adjuvant regimens with these procedures as well as routine tumour molecular analysis may modify therapeutic algorithms for hepatocellular carcinoma in the future.

Direct Comparison of Four Presurgical Stratifying Schemes for Prediction of Microvascular Invasion in Hepatocellular Carcinoma by Gadoxetic Acid-Enhanced MRI

BACKGROUND

Microvascular invasion (MVI) is implicated in the poor prognosis of hepatocellular carcinoma (HCC). Presurgical stratifying schemes have been proposed for HCC-MVI but lack external validation.

PURPOSE

To perform external validation and comparison of four presurgical stratifying schemes for the prediction of MVI using gadoxetic acid-based MRI in a cohort of HCC patients.

STUDY TYPE

Retrospective.

SUBJECTS

Included were 183 surgically resected HCCs from patients who underwent pretreatment MRI.

FIELD STRENGTH/SEQUENCE

This includes 1.5-3.0 T with T₂ , T₁ , diffusion-weighted imaging (DWI), and dynamic gadoxetic acid contrast-enhancement imaging sequences.

ASSESSMENT

A two-trait predictor of venous invasion (TTPVI), Lei model, Lee model, and Xu model were compared. We relied on preoperative characteristics and imaging findings via four independent radiologists who were blinded to histologic results, as required by the tested tools.

STATISTICAL TEST

Tests of accuracy between predicted and observed HCC-MVI rates using receiver operating characteristic (ROC) curve and decision curve analysis. The intraclass correlation coefficient (ICC) and Cronbach's alpha statistics were used to evaluate reproducibility.

RESULTS

HCC-MVI was identified in 52 patients (28.4%). The average ROC curves (AUCs) for HCC-MVI predictions were 0.709-0.880, 0.714-0.828, and 0.588-0.750 for the Xu model, Lei model, and Lee model, respectively. The rates of accuracy were 60.7-81.4%, 69.9-75.9%, and 65.6-73.8%, respectively. Decision curve analyses indicated a higher benefit for the Xu and Lei models compared to the Lee model. The ICC and Cronbach's alpha index were highest in the Lei model (0.896/0.943), followed by the Xu model (0.882/0.804), and the Lee model (0.769/0.715). The TTPVI resulted in a Cronbach's alpha index of 0.606 with a sensitivity of 34.6-61.5% and a specificity of 76.3-91.6%.

DATA CONCLUSION

Stratifying schemes relying on gadoxetic acid-enhanced MRI provide an additional insight into the presence of preoperative MVI. The Xu model outperformed the other models in terms of accuracy when performed by an experienced radiologist. Conversely, the Lei model outperformed the other models in terms of reproducibility.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:433-447.

Role of liver biopsy in hepatocellular carcinoma

The role of liver biopsy in the diagnosis of hepatocellular carcinoma (HCC) has been challenged over time by the ability of imaging techniques to characterize liver lesions in patients with known cirrhosis. In fact, in the diagnostic algorithm for this tumor, histology is currently relegated to controversial cases. Furthermore, the risk of complications, such as tumor seeding and bleeding, as well as inadequate sampling have further limited the use of liver biopsy for HCC management. However, there is growing evidence of prognostic and therapeutic information available from microscopic and molecular analysis of HCC and, as the information content of the tissue sample increases, the advantages of liver biopsy might modify the current risk/benefit ratio. We herein review the role and potentiality of liver biopsy in the diagnosis and management of HCC. As the potentiality of precision medicine comes to the management of HCC, it will be crucial to have rapid pathways to define prognosis, and even treatment, by identifying the patients who could most benefit from target-driven therapies. All of the above reasons suggest that the current role of liver biopsy in the management of HCC needs substantial reconsideration.

Changing role of histopathology in the diagnosis and management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and fatal cancer in the world. HCC frequently presents with advanced disease, has a high recurrence rate and limited treatment options, which leads to very poor prognosis. This warrants urgent improvement in the diagnosis and treatment. Liver biopsy plays very important role in the diagnosis and prognosis of HCC, but with technical advancements and progression in the field of imaging, clinical guidelines have restricted the role of biopsy to very limited situations. Biopsy also has its own problems of needle tract seeding of tumor, small risk of complications, technical and sampling errors along with interpretative errors. Despite this, tissue analysis is often required because imaging is not always specific, limited expertise and lack of advanced imaging in many centers and limitations of imaging in the diagnosis of small, mixed and other variant forms of HCC. In addition, biopsy confirmation is often required for clinical trials of new drugs and targeted therapies. Tissue biomarkers along with certain morphological features, phenotypes and immune-phenotypes that serve as important prognostic and outcome predictors and as decisive factors for therapy decisions, add to the continuing role of histopathology. Advancements in cancer biology and development of molecular classification of HCC with clinic pathological correlation, lead to discovery of HCC phenotypic surrogates of prognostic and therapeutically significant molecular signatures. Thus tissue characteristics and morphology based correlates of molecular subtypes provide invaluable information for management and prognosis. This review thus focuses on the importance of histopathology and resurgence of role of biopsy in the diagnosis, management and prognostication of HCC.

Macrotrabecular-massive hepatocellular carcinoma: A distinctive histological subtype with clinical relevance

We recently identified a histological subtype of hepatocellular carcinoma (HCC), designated as "macrotrabecular-massive" (MTM-HCC) and associated with specific molecular features. In order to assess the clinical relevance of this variant, we investigated its prognostic value in two large series of patients with HCC treated by either surgical resection or radiofrequency ablation (RFA). We retrospectively included 237 HCC surgical samples and 284 HCC liver biopsies from patients treated by surgical resection and RFA, respectively. Histological slides were reviewed by pathologists specialized in liver disease, and the MTM-HCC subtype was defined by the presence of a predominant (>50%) macrotrabecular architecture (more than six cells thick). The main clinical and biological features were recorded at baseline. Clinical endpoints were early and overall recurrence. The MTM-HCC subtype was identified in 12% of the whole cohort (16% of surgically resected samples, 8.5% of liver biopsy samples). It was associated at baseline with known poor prognostic factors (tumor size, alpha-fetoprotein level, satellite nodules, and vascular invasion). Multivariate analysis showed that MTM-HCC subtype was an independent predictor of early and overall recurrence (surgical series: hazard ratio, 3.03; 95% confidence interval, 1.38-6.65; P = 0.006; and 2.76; 1.63-4.67; P < 0.001; RFA series: 2.37; 1.36-4.13; P = 0.002; and 2.19; 1.35-3.54; P = 0.001, respectively). Its prognostic value was retained even after patient stratification according to common clinical, biological, and pathological features of aggressiveness. No other baseline parameter was independently associated with recurrence in the RFA series.

CONCLUSION

The MTM-HCC subtype, reliably observed in 12% of patients eligible for curative treatment, represents an aggressive form of HCC that may require more specific therapeutic strategies. (Hepatology 2018;68:103-112).