Microvascular Invasion Is a Better Predictor of Tumor Recurrence and Overall Survival Following Surgical Resection for Hepatocellular Carcinoma Compared to the Milan Criteria

Correlation between 18 F-FDG PET/CT metabolic parameters and microvascular invasion before liver transplantation in patients with hepatocellular carcinoma

BACKGROUND

Microvascular infiltration (MVI) before liver transplantation (LT) in patients with hepatocellular carcinoma (HCC) is associated with postoperative tumor recurrence and survival. MVI is mainly assessed by pathological analysis of tissue samples, which is invasive and heterogeneous. PET/computed tomography (PET/CT) with 18 F-labeled fluorodeoxyglucose ( 18 F-FDG) as a tracer has been widely used in the examination of malignant tumors. This study investigated the association between 18 F-FDG PET/CT metabolic parameters and MVI before LT in HCC patients.

METHODS

About 124 HCC patients who had 18 F-FDG PET/CT examination before LT were included. The patients' clinicopathological features and 18 F-FDG PET/CT metabolic parameters were recorded. Correlations between clinicopathological features, 18 F-FDG PET/CT metabolic parameters, and MVI were analyzed. ROC curve was used to determine the optimal diagnostic cutoff value, area under the curve (AUC), sensitivity, and specificity for predictors of MVI.

RESULT

In total 72 (58.06%) patients were detected with MVI among the 124 HCC patients. Univariate analysis showed that tumor size ( P  = 0.001), T stage ( P  < 0.001), maximum standardized uptake value (SUV max ) ( P  < 0.001), minimum standardized uptake value (SUV min ) ( P  = 0.031), mean standardized uptake value (SUV mean ) ( P  = 0.001), peak standardized uptake value (SUV peak ) ( P  = 0.001), tumor-to-liver ratio (SUV ratio ) ( P  = 0.010), total lesion glycolysis (TLG) ( P  = 0.006), metabolic tumor volume (MTV) ( P  = 0.011) and MVI were significantly different. Multivariate logistic regression showed that tumor size ( P  = 0.018), T stage ( P  = 0.017), TLG ( P  = 0.023), and MTV ( P  = 0.015) were independent predictors of MVI. In the receiver operating characteristic curve, TLG predicted MVI with an AUC value of 0.645. MTV predicted MVI with an AUC value of 0.635. Patients with tumor size ≥5 cm, T3-4, TLG > 400.67, and MTV > 80.58 had a higher incidence of MVI.

CONCLUSION

18 F-FDG PET/CT metabolic parameters correlate with MVI and may be used as a noninvasive technique to predict MVI before LT in HCC patients.

Development and validation of a cross-modality tensor fusion model using multi-modality MRI radiomics features and clinical radiological characteristics for the prediction of microvascular invasion in hepatocellular carcinoma

OBJECTIVES

To develop and validate a cross-modality tensor fusion (CMTF) model using multi-modality MRI radiomics features and clinical radiological characteristics for the prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

This study included 174 HCC patients (47 MVI-positive and 127 MVI-negative) confirmed by postoperative pathology. The synthetic minority over-sampling technique was used to augment MVI-positive samples. The amplified dataset of 254 samples (127 MVI-positive and 127 MVI-negative) was randomly divided into training and test cohorts in a 7:3 ratio. Radiomics features were respectively extracted from arterial phase, delayed phase, diffusion-weighted imaging, and fat-suppressed T2-weighted imaging. The least absolute shrinkage and selection operator was used for feature selection. Univariate and multivariate logistic regression analyses were employed to identify clinical and radiological independent predictors. The selected multi-modality MRI radiomics features, clinical and radiological characteristics were used to construct the CMTF model, single modality (SM) model, early fusion (EF) model.

RESULTS

The CMTF model demonstrated superior performance in predicting MVI compared to the SM and EF models. When integrating four MRI modalities, the CMTF model achieved a high area under the curve (AUC) with 95 % confidence interval (95 % CI) of 0.894 (0.820-0.968). Additionally, incorporating clinical and radiological characteristics further enhanced the predictive performance of CMTF model, the AUC (95 % CI) value increased to 0.945 (0.892-0.998).

CONCLUSION

The CMTF model showed promising performance in preoperative MVI prediction, providing a more effective non-invasive detection tool for HCC patients.

The role of artificial intelligence in the management of liver diseases

Universal neonatal hepatitis B virus (HBV) vaccination and the advent of direct-acting antivirals (DAA) against hepatitis C virus (HCV) have reshaped the epidemiology of chronic liver diseases. However, some aspects of the management of chronic liver diseases remain unresolved. Nucleotide analogs can achieve sustained HBV DNA suppression but rarely lead to a functional cure. Despite the high efficacy of DAAs, successful antiviral therapy does not eliminate the risk of hepatocellular carcinoma (HCC), highlighted the need for cost-effective identification of high-risk populations for HCC surveillance and tailored HCC treatment strategies for these populations. The accessibility of high-throughput genomic data has accelerated the development of precision medicine, and the emergence of artificial intelligence (AI) has led to a new era of precision medicine. AI can learn from complex, non-linear data and identify hidden patterns within real-world datasets. The combination of AI and multi-omics approaches can facilitate disease diagnosis, biomarker discovery, and the prediction of treatment efficacy and prognosis. AI algorithms have been implemented in various aspects, including non-invasive tests, predictive models, image diagnosis, and the interpretation of histopathology findings. AI can support clinicians in decision-making, alleviate clinical burdens, and curtail healthcare expenses. In this review, we introduce the fundamental concepts of machine learning and review the role of AI in the management of chronic liver diseases.

Significance of anatomical resection and wide surgical margin for HCC patients with MVI undergoing laparoscopic hepatectomy: A multicenter study

OBJECTIVE

To investigate the impact of surgical resection margin and hepatic resection type on prognosis and compare their prognostic significance on patients with hepatocellular carcinoma (HCC) with or without microvascular invasion (MVI) who underwent laparoscopic liver resection (LLR).

METHODS

A retrospective analysis was conducted on 320 patients with HCC who underwent LLR. According to the grading of MVI, patients were classified as M0, M1 and M2. Patients were divided into the anatomical resection (AR) and nonanatomical resection (NAR) groups according to the hepatic resection type. Survival and Cox regression analyses were performed to explore the effects of AR and NAR, wide and narrow resection margin on overall survival (OS) and time to recurrence (TTR).

RESULTS

In the whole cohort, narrow resection margin was an independent risk factor for OS and TTR, whereas NAR was not. Subgroup analysis showed that narrow resection margin and NAR were both independent risk factors for OS and TTR in HCC patients with MVI. The 5-year OS and TTR rates of the two groups (NAR-wide resection margin and AR-narrow resection margin) with M1 were 85.3 % versus 62 % and 34.4 % versus 60.2 %. Similarly, the 5-year OS and TTR rates of the two groups (NAR-wide resection margin and AR-narrow resection margin) with M2 were 80.2 % versus 47.9 % and 30.8 % versus 64.8 %.

CONCLUSIONS

Anatomical hepatectomy and wide resection margin were independent protective factors for HCC patients with MVI receiving LLR. Nonetheless, wide resection margin had a greater impact on prognosis than anatomical hepatectomy.

Grading severity of MVI impacts long-term outcomes after laparoscopic liver resection for early-stage hepatocellular carcinoma: A multicenter study

PURPOSE

To examine the relationship between microvascular invasion (MVI) grading severity and long-term outcomes in early-stage hepatocellular carcinoma (HCC) patients undergoing laparoscopic liver resection (LLR).

METHODS

Patients who had LLR for early-stage HCC were enrolled. According to the grading severity of MVI, patients were classified into M0, M1 and M2. Recurrence-free survival (RFS) and overall survival (OS) among the groups were compared. Univariate and multivariate Cox regression analyses were performed to identify independent risk factors of OS and RFS.

RESULTS

Among 233 patients, MVI grading as M0, M1, and M2 accounts for 122 (52.4 ​%), 84 (36 ​%), and 27 (11.6 ​%) patients, respectively. The median OS and RFS in patients with M0, M1, and M2 were 84.9, 40.1, and 25.2 months; and 76.9, 27.0, and 18.8 months, respectively. Multivariable analyses identified both M1 and M2 to be independent risk factors for OS and RFS.

CONCLUSION

Grading severity of MVI was independently associated with RFS and OS after LLR for early-stage HCC. Patients with MVI, especially those with M2, should receive stringent recurrence surveillance and active adjuvant therapy.

A nomogram model for early recurrence of HBV-related hepatocellular carcinomas after radical hepatectomy

Background

To identify the risk factors and construct a predictive model for early recurrence of hepatitis B virus(HBV-)- related hepatocellular carcinomas(HCCs) after radical resection.

Data and methods

A total of 465 HBV-related HCC patients underwent radical resections between January 1, 2012 and August 31, 2018.Their data were collected through the inpatient information management system of the First Affiliated Hospital of University of Science and Technology of China. Survival and subgroup analyses of early recurrence among male and female patients were performed using Kaplan-Meier curves. The independent risk factors associated with early postoperative tumor recurrence were analyzed using multivariate Cox proportional hazards regression model. Based on these independent risk factors, a risk function model for early recurrence was fitted, and a column chart for the prediction model was drawn for internal and external validation.

Results

A total of 181 patients developed early recurrences, including 156 males and 25 females. There was no difference in the early recurrence rates between males and females. Tumor diameters>5cm, microvascular invasion and albumin level<35 g/L were independent risk factors for early recurrence. A nomogram for the early recurrence prediction model was drawn; the areas under the curve for the model and for external verification were 0.638 and 0.655, respectively.

Conclusion

Tumor diameter>5 cm, microvascular invasion, and albumin level<35 g/L were independent risk factors for early recurrence. The prediction model based on three clinical indicators could predict early recurrence, with good discrimination, calibration, and extrapolation.

NLR stability predicts response to immune checkpoint inhibitors in advanced hepatocellular carcinoma

A high baseline NLR is associated with a poor prognosis of immunotherapy in patients with advanced HCC. As anti-tumour immune activation takes time, early dynamic changes in NLR may serve as a biomarker for predicting immunotherapy response. We conducted a retrospective study in which we enrolled 209 patients with aHCC who received ICIs (training cohort: N = 121, validation cohort: N = 88). In the training cohort, we categorized the patients based on the early changes in their NLR. Specifically, we defined patients as NLR Stable-Responder, NLR Responder and NLR Non-Responder. We compared the outcomes of these three patient groups using survival analysis. Additionally, we shortened the observation period to 6 weeks and validated the findings in the validation cohort. In the training cohort, early dynamic changes in NLR (HR 0.14, 95%CI 0.03-0.65, p = 0.012, HR 0.19, 95%CI 0.07-0.54, p = 0.002; HR 0.21, 95%CI 0.10-0.42, p < 0.001, HR 0.40, 95%CI 0.23-0.69, p = 0.001), PD-L1 < 1% (HR 5.36, 95%CI 1.12-25.66, p = 0.036; HR 2.98, 95%CI 1.51-5.91, p = 0.002) and MVI (HR 3.52, 95%CI 1.28-9.69, p = 0.015; HR 1.99, 95%CI 1.14-3.47, p = 0.015) were identified as independent predictors of OS and PFS. In the validation cohort, when the observation period was reduced to 6 weeks, early NLR changes still have predictive value. Early dynamic changes in NLR may be an easily defined, cost-effective, non-invasive biomarker to predict aHCC response to ICIs.

Multi-transcriptomics analysis of microvascular invasion-related malignant cells and development of a machine learning-based prognostic model in hepatocellular carcinoma

Background

Microvascular invasion (MVI) stands as a pivotal pathological hallmark of hepatocellular carcinoma (HCC), closely linked to unfavorable prognosis, early recurrence, and metastatic progression. However, the precise mechanistic underpinnings governing its onset and advancement remain elusive.

Methods

In this research, we downloaded bulk RNA-seq data from the TCGA and HCCDB repositories, single-cell RNA-seq data from the GEO database, and spatial transcriptomics data from the CNCB database. Leveraging the Scissor algorithm, we delineated prognosis-related cell subpopulations and discerned a distinct MVI-related malignant cell subtype. A comprehensive exploration of these malignant cell subpopulations was undertaken through pseudotime analysis and cell-cell communication scrutiny. Furthermore, we engineered a prognostic model grounded in MVI-related genes, employing 101 algorithm combinations integrated by 10 machine-learning algorithms on the TCGA training set. Rigorous evaluation ensued on internal testing sets and external validation sets, employing C-index, calibration curves, and decision curve analysis (DCA).

Results

Pseudotime analysis indicated that malignant cells, showing a positive correlation with MVI, were primarily concentrated in the early to middle stages of differentiation, correlating with an unfavorable prognosis. Importantly, these cells showed significant enrichment in the MYC pathway and were involved in extensive interactions with diverse cell types via the MIF signaling pathway. The association of malignant cells with the MVI phenotype was corroborated through validation in spatial transcriptomics data. The prognostic model we devised demonstrated exceptional sensitivity and specificity, surpassing the performance of most previously published models. Calibration curves and DCA underscored the clinical utility of this model.

Conclusions

Through integrated multi-transcriptomics analysis, we delineated MVI-related malignant cells and elucidated their biological functions. This study provided novel insights for managing HCC, with the constructed prognostic model offering valuable support for clinical decision-making.

Survival in Patients With Recurrent Intermediate-Stage Hepatocellular Carcinoma: Sorafenib Plus TACE vs TACE Alone Randomized Clinical Trial

Importance

Transarterial chemoembolization (TACE) is commonly used to treat patients with recurrent intermediate-stage hepatocellular carcinoma (HCC) and positive microvascular invasion (MVI); however, TACE alone has demonstrated unsatisfactory survival benefits. A previous retrospective study suggested that TACE plus sorafenib (SOR-TACE) may be a better therapeutic option compared with TACE alone.

Objective

To investigate the clinical outcomes of SOR-TACE vs TACE alone for patients with recurrent intermediate-stage HCC after R0 hepatectomy with positive MVI.

Design, Setting, and Participants

In this phase 3, open-label, multicenter randomized clinical trial, patients with recurrent intermediate-stage HCC and positive MVI were randomly assigned in a 1:1 ratio via a computerized minimization technique to either SOR-TACE treatment or TACE alone. This trial was conducted at 5 hospitals in China, and enrolled patients from October 2019 to December 2021, with a follow-up period of 24 months. Data were analyzed from June 2023 to September 2023.

Interventions

Randomization to on-demand TACE (conventional TACE: doxorubicin, 50 mg, mixed with lipiodol and gelatin sponge particles [diameter: 150-350 μm]; drug-eluting bead TACE: doxorubicin, 75 mg, mixed with drug-eluting particles [diameter: 100-300 μm or 300-500 μm]) (TACE group) or sorafenib, 400 mg, twice daily plus on-demand TACE (SOR-TACE group) (conventional TACE: doxorubicin, 50 mg, mixed with lipiodol and gelatin sponge particles [diameter, 150-350 μm]; drug-eluting bead TACE: doxorubicin, 75 mg, mixed with drug-eluting particles [diameter: 100-300 μm or 300-500 μm]).

Main Outcomes and Measures

The primary end point was overall survival by intention-to-treat analysis. Safety was assessed in patients who received at least 1 dose of study treatment.

Results

A total of 162 patients (median [range] age, 55 [28-75] years; 151 males [93.2%]), were randomly assigned to be treated with either SOR-TACE (n = 81) or TACE alone (n = 81). The median overall survival was significantly longer in the SOR-TACE group than in the TACE group (22.2 months vs 15.1 months; hazard ratio [HR], 0.55; P < .001). SOR-TACE also prolonged progression-free survival (16.2 months vs 11.8 months; HR, 0.54; P < .001), and improved the objective response rate when compared with TACE alone based on the modified Response Evaluation Criteria in Solid Tumors criteria (80.2% vs 58.0%; P = .002). Any grade adverse events were more common in the SOR-TACE group, but all adverse events responded well to treatment. No unexpected adverse events or treatment-related deaths occurred in this study.

Conclusions and Relevance

The results of this randomized clinical trial demonstrated that SOR-TACE achieved better clinical outcomes than TACE alone. These findings suggest that combined treatment should be used for patients with recurrent intermediate-stage HCC after R0 hepatectomy with positive MVI.

Trial Registration

ClinicalTrials.gov Identifier: NCT04103398.

Preoperative prediction of microvascular invasion risk in hepatocellular carcinoma with MRI: peritumoral versus tumor region

OBJECTIVES

To explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI).

METHODS

A total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC).

RESULTS

The XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80.

CONCLUSION

Compared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted.

CLINICAL RELEVANCE STATEMENT

The 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region.

KEY POINTS

We investigated tumor and different peritumoral regions, as well as their fusion. MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region. The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI.

Decision-Tree Models Indicative of Microvascular Invasion on MRI Predict Survival in Patients with Hepatocellular Carcinoma Following Tumor Ablation

Purpose

Histological microvascular invasion (MVI) is a risk factor for poor survival and early recurrence in hepatocellular carcinoma (HCC) after surgery. Its prognostic value in the setting of locoregional therapies (LRT), where no tissue samples are obtained, remains unknown. This study aims to establish CT-derived indices indicative of MVI on liver MRI with superior soft tissue contrast and evaluate their association with patient survival after ablation via interstitial brachytherapy (iBT) versus iBT combined with prior conventional transarterial chemoembolization (cTACE).

Patients and Methods

Ninety-five consecutive patients, who underwent ablation via iBT alone (n = 47) or combined with cTACE (n = 48), were retrospectively included between 01/2016 and 12/2017. All patients received contrast-enhanced MRI prior to LRT. Overall (OS), progression-free survival (PFS), and time-to-progression (TTP) were assessed. Decision-tree models to determine Radiogenomic Venous Invasion (RVI) and Two-Trait Predictor of Venous Invasion (TTPVI) on baseline MRI were established, validated on an external test set (TCGA-LIHC), and applied in the study cohorts to investigate their prognostic value for patient survival. Statistics included Fisher's exact and t-test, Kaplan-Meier and cox-regression analysis, area under the receiver operating characteristic curve (AUC-ROC) and Pearson's correlation.

Results

OS, PFS, and TTP were similar in both treatment groups. In the external dataset, RVI showed low sensitivity but relatively high specificity (AUC-ROC = 0.53), and TTPVI high sensitivity but only low specificity (AUC-ROC = 0.61) for histological MVI. In patients following iBT alone, positive RVI and TTPVI traits were associated with poorer OS (RVI: p < 0.01; TTPVI: p = 0.08), PFS (p = 0.04; p = 0.04), and TTP (p = 0.14; p = 0.03), respectively. However, when patients with combined cTACE and iBT were stratified by RVI or TTPVI, no differences in OS (p = 0.75; p = 0.55), PFS (p = 0.70; p = 0.43), or TTP (p = 0.33; p = 0.27) were observed.

Conclusion

The study underscores the role of non-invasive imaging biomarkers indicative of MVI to identify patients, who would potentially benefit from embolotherapy via cTACE prior to ablation rather than ablation alone.

Nomogram for preoperative estimation of microvascular invasion risk in hepatocellular carcinoma

Microvascular invasion (MVI) is an adverse prognostic indicator of tumor recurrence after surgery for hepatocellular carcinoma (HCC). Therefore, developing a nomogram for estimating the presence of MVI before liver resection is necessary. We retrospectively included 260 patients with pathologically confirmed HCC at the Fifth Medical Center of Chinese PLA General Hospital between January 2021 and April 2024. The patients were randomly divided into a training cohort (n = 182) for nomogram development, and a validation cohort (n = 78) to confirm the performance of the model (7:3 ratio). Significant clinical variables associated with MVI were then incorporated into the predictive nomogram using both univariate and multivariate logistic analyses. The predictive performance of the nomogram was assessed based on its discrimination, calibration, and clinical utility. Serum carnosine dipeptidase 1 ([CNDP1] OR 2.973; 95 % CI 1.167-7.575; p = 0.022), cirrhosis (OR 8.911; 95 % CI 1.922-41.318; p = 0.005), multiple tumors (OR 4.095; 95 % CI 1.374-12.205; p = 0.011), and tumor diameter ≥3 cm (OR 4.408; 95 % CI 1.780-10.919; p = 0.001) were independent predictors of MVI. Performance of the nomogram based on serum CNDP1, cirrhosis, number of tumors and tumor diameter was achieved with a concordance index of 0.833 (95 % CI 0.771-0.894) and 0.821 (95 % CI 0.720-0.922) in the training and validation cohorts, respectively. It fitted well in the calibration curves, and the decision curve analysis further confirmed its clinical usefulness. The nomogram, incorporating significant clinical variables and imaging features, successfully predicted the personalized risk of MVI in HCC preoperatively.

Identification of VEGFs-related gene signature for predicting microangiogenesis and hepatocellular carcinoma prognosis

Microangiogenesis is an important prognostic factor in various cancers, including hepatocellular carcinoma (HCC). The Vascular Endothelial Growth Factor (VEGF) has been shown to contribute to tumor angiogenesis. Recently, several studies have investigated the regulation of VEGF production by a single gene, with few researchers exploring all genes that affect VEGF production. In this study, we comprehensively analyzed all genes affecting VEGF production in HCC and developed a risk model and gene-based risk score based on VEGF production. Moreover, the model's predictive capacity on prognosis of HCCs was verified using training and validation datasets. The developed model showed good prediction of the overall survival rate. Patients with a higher risk score experienced poor outcomes compared to those with a lower risk score. Furthermore, we identified the immunological causes of the poor prognosis of patients with high-risk scores comparing with those with low-risk scores.

A clinical-radiomic-pathomic model for prognosis prediction in patients with hepatocellular carcinoma after radical resection

PURPOSE

Radical surgery, the first-line treatment for patients with hepatocellular cancer (HCC), faces the dilemma of high early recurrence rates and the inability to predict effectively. We aim to develop and validate a multimodal model combining clinical, radiomics, and pathomics features to predict the risk of early recurrence.

MATERIALS AND METHODS

We recruited HCC patients who underwent radical surgery and collected their preoperative clinical information, enhanced computed tomography (CT) images, and whole slide images (WSI) of hematoxylin and eosin (H & E) stained biopsy sections. After feature screening analysis, independent clinical, radiomics, and pathomics features closely associated with early recurrence were identified. Next, we built 16 models using four combination data composed of three type features, four machine learning algorithms, and 5-fold cross-validation to assess the performance and predictive power of the comparative models.

RESULTS

Between January 2016 and December 2020, we recruited 107 HCC patients, of whom 45.8% (49/107) experienced early recurrence. After analysis, we identified two clinical features, two radiomics features, and three pathomics features associated with early recurrence. Multimodal machine learning models showed better predictive performance than bimodal models. Moreover, the SVM algorithm showed the best prediction results among the multimodal models. The average area under the curve (AUC), accuracy (ACC), sensitivity, and specificity were 0.863, 0.784, 0.731, and 0.826, respectively. Finally, we constructed a comprehensive nomogram using clinical features, a radiomics score and a pathomics score to provide a reference for predicting the risk of early recurrence.

CONCLUSIONS

The multimodal models can be used as a primary tool for oncologists to predict the risk of early recurrence after radical HCC surgery, which will help optimize and personalize treatment strategies.

Infiltrative Vessel Co-optive Growth Pattern Induced by IQGAP3 Overexpression Promotes Microvascular Invasion in Hepatocellular Carcinoma

PURPOSE

Microvascular invasion (MVI) is a major unfavorable prognostic factor for intrahepatic metastasis and postoperative recurrence of hepatocellular carcinoma (HCC). However, the intervention and preoperative prediction for MVI remain clinical challenges due to the absent precise mechanism and molecular marker(s). Herein, we aimed to investigate the mechanisms underlying vascular invasion that can be applied to clinical intervention for MVI in HCC.

EXPERIMENTAL DESIGN

The histopathologic characteristics of clinical MVI+/HCC specimens were analyzed using multiplex immunofluorescence staining. The liver orthotopic xenograft mouse model and mechanistic experiments on human patient-derived HCC cell lines, including coculture modeling, RNA-sequencing, and proteomic analysis, were used to investigate MVI-related genes and mechanisms.

RESULTS

IQGAP3 overexpression was correlated significantly with MVI status and reduced survival in HCC. Upregulation of IQGAP3 promoted MVI+-HCC cells to adopt an infiltrative vessel co-optive growth pattern and accessed blood capillaries by inducing detachment of activated hepatic stellate cells (HSC) from the endothelium. Mechanically, IQGAP3 overexpression contributed to HCC vascular invasion via a dual mechanism, in which IQGAP3 induced HSC activation and disruption of the HSC-endothelial interaction via upregulation of multiple cytokines and enhanced the trans-endothelial migration of MVI+-HCC cells by remodeling the cytoskeleton by sustaining GTPase Rac1 activity. Importantly, systemic delivery of IQGAP3-targeting small-interfering RNA nanoparticles disrupted the infiltrative vessel co-optive growth pattern and reduced the MVI of HCC.

CONCLUSIONS

Our results revealed a plausible mechanism underlying IQGAP3-mediated microvascular invasion in HCC, and provided a potential target to develop therapeutic strategies to treat HCC with MVI.

Current Trends and Advancements in the Management of Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) remains a significant global health burden with a high mortality rate. Over the past 40 years, significant progress has been achieved in the prevention and management of HCC.

SUMMARY

Hepatitis B vaccination programs, the development of direct acting antiviral drugs for Hepatitis C, and effective surveillance strategies provide a profound basis for the prevention of HCC. Advanced surgery and liver transplantation along with local ablation techniques potentially offer cure for the disease. Also, just recently, the introduction of immunotherapy opened a new chapter in systemic treatment. Finally, the introduction of the BCLC classification system for HCC, clearly defining patient groups and assigning reasonable treatment options, has standardized treatment and become the basis of almost all clinical trials for HCC. With this review, we provide a comprehensive overview of the evolving landscape of HCC management and also touch on current challenges.

KEY MESSAGE

A comprehensive and multidisciplinary approach is crucial for effective HCC management. Continued research and clinical trials are imperative to further enhance treatment options and will ultimately reduce the global burden of this devastating disease.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

ADVANCES IN KNOWLEDGE

GCN based on MRI could predict MVI on HCC.

Predicting microvascular invasion in hepatocellular carcinoma with a CT- and MRI-based multimodal deep learning model

PURPOSE

To investigate the value of a multimodal deep learning (MDL) model based on computed tomography (CT) and magnetic resonance imaging (MRI) for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

A total of 287 patients with HCC from our institution and 58 patients from another individual institution were included. Among these, 119 patients with only CT data and 116 patients with only MRI data were selected for single-modality deep learning model development, after which select parameters were migrated for MDL model development with transfer learning (TL). In addition, 110 patients with simultaneous CT and MRI data were divided into a training cohort (n = 66) and a validation cohort (n = 44). We input the features extracted from DenseNet121 into an extreme learning machine (ELM) classifier to construct a classification model.

RESULTS

The area under the curve (AUC) of the MDL model was 0.844, which was superior to that of the single-phase CT (AUC = 0.706-0.776, P < 0.05), single-sequence MRI (AUC = 0.706-0.717, P < 0.05), single-modality DL model (AUCall-phase CT = 0.722, AUCall-sequence MRI = 0.731; P < 0.05), clinical (AUC = 0.648, P < 0.05), but not to that of the delay phase (DP) and in-phase (IP) MRI and portal venous phase (PVP) CT models. The MDL model achieved better performance than models described above (P < 0.05). When combined with clinical features, the AUC of the MDL model increased from 0.844 to 0.871. A nomogram, combining deep learning signatures (DLS) and clinical indicators for MDL models, demonstrated a greater overall net gain than the MDL models (P < 0.05).

CONCLUSION

The MDL model is a valuable noninvasive technique for preoperatively predicting MVI in HCC.

Comparison of survival benefit and safety between surgery following conversion therapy versus surgery alone in patients with surgically resectable hepatocellular carcinoma at CNLC IIb/IIIa stage: a propensity score matching study

OBJECTIVE

The objective of this study is to evaluate and compare the survival benefit and safety of surgery following conversion therapy versus surgery alone in patients diagnosed with surgically resectable hepatocellular carcinoma (HCC) at China Liver Cancer Staging (CNLC) IIb/IIIa stage.

METHODS

A total of 95 patients diagnosed with surgically resectable CNLC IIb/IIIa HCC were retrospectively enrolled in our study from November 2018 to December 2022. Among them, 30 patients underwent conversion therapy followed by hepatectomy, while the remaining 65 received surgery alone. The primary endpoint was recurrence-free survival (RFS). Propensity score matching was employed to minimize bias in the retrospective analysis.

RESULTS

Compared to the surgery alone group, the conversion therapy group demonstrated a significantly prolonged median RFS (17.1 vs. 7.0 months; P =0.014), a reduced incidence of microvascular invasion (MVI, 23.3 vs. 81.5%; P <0.001), and a comparable rate of achieving Textbook Outcome in Liver Surgery (TOLS, 83.3 vs. 76.9%; P =0.476). Multivariate analysis indicated that conversion therapy was independently associated with improved RFS after hepatectomy (HR=0.511, P =0.027). The same conclusions were obtained after propensity score matching.

CONCLUSIONS

The findings of our study offer preliminary evidence that preoperative conversion therapy significantly prolongs RFS in patients with surgically resectable HCC at CNLC IIb/IIIa stage. Furthermore, combining conversion therapy and hepatectomy represents a relatively safe treatment strategy.

Identification of molecular characteristics of hepatocellular carcinoma with microvascular invasion based on deep targeted sequencing

BACKGROUND

As an indicator of tumor invasiveness, microvascular invasion (MVI) is a crucial risk factor for postoperative relapse, metastasis, and unfavorable prognosis in hepatocellular carcinoma (HCC). Nevertheless, the genetic mechanisms underlying MVI, particularly for Chinese patients, remain mostly uncharted.

METHODS

We applied deep targeted sequencing on 66 Chinese HCC samples. Focusing on the telomerase reverse transcriptase (TERT) promoter (TERTp) and TP53 co-mutation (TERTp+/TP53+) group, gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of the TERTp+/TP53+ group on tumor progression and metastasis. Additionally, we evaluated the tumor immune microenvironment of the TERTp+/TP53+ group in HCC using multiplex immunofluorescence (mIF) staining.

RESULTS

Among the 66 HCC samples, the mutated genes that mostly appeared were TERT, TP53, and CTNNB1. Of note, we found 10 cases with TERTp+/TP53+, of which nine were MVI-positive and one was MVI-negative, and there was a co-occurrence of TERTp and TP53 (p < 0.05). Survival analysis demonstrated that patients with the TERTp+/TP53+ group had lower the disease-free survival (DFS) (p = 0.028). GSEA results indicated that telomere organization, telomere maintenance, DNA replication, positive regulation of cell cycle, and negative regulation of immune response were significantly enriched in the TERTp+/TP53+ group (all adjusted p-values (p.adj) < 0.05). mIF revealed that the TERTp+/TP53+ group decreased CD8+ T cells infiltration (p = 0.25) and enhanced PDL1 expression (p = 0.55).

CONCLUSIONS

TERTp+/TP53+ was significantly enriched in MVI-positive patients, leading to poor prognosis for HCC patients by promoting proliferation of HCC cell and inhibiting infiltration of immune cell surrounding HCC. TERTp+/TP53+ can be utilized as a potential indicator for predicting MVI-positive patients and poor prognosis, laying a preliminary foundation for further exploration of co-mutation in HCC with MVI and clinical treatment.

Post-transplant hepatitis B virus reactivation impacts the prognosis of patients with hepatitis B-related hepatocellular carcinoma: a dual-centre retrospective cohort study in China

BACKGROUND

Highly active hepatitis B virus (HBV) is known to be associated with poor outcomes in patients with hepatocellular carcinoma (HCC). This study aims to investigate the relationship between HBV status and HCC recurrence after liver transplantation.

METHODS

The study retrospectively analyzed HCC patients undergoing liver transplantation in two centres between January 2015 and December 2020. The authors reviewed post-transplant HBV status and its association with outcomes.

RESULTS

The prognosis of recipients with hepatitis B surface antigen (HBsAg) reappearance ( n =58) was poorer than those with HBsAg persistent negative ( n =351) and positive ( n =53). In HBsAg persistent positive group, recipients with HBV DNA reappearance or greater than 10-fold increase above baseline had worse outcomes than those without ( P <0.01). HBV reactivation was defined as (a) HBsAg reappearance or (b) HBV DNA reappearance or greater than 10-fold increase above baseline. After propensity score matching, the 5-year overall survival rate and recurrence-free survival rate after liver transplantation in recipients with HBV reactivation were significantly lower than those without (32.0% vs. 62.3%; P <0.01, and 16.4% vs. 63.1%; P <0.01, respectively). Moreover, HBV reactivation was significantly related to post-transplant HCC recurrence, especially lung metastasis. Cox regression analysis revealed that beyond Milan criteria, microvascular invasion and HBsAg-positive graft were independent risk factors for post-transplant HBV reactivation, and a novel nomogram was established accordingly with a good predictive efficacy (area under the time-dependent receiver operating characteristic curve=0.78, C-index =0.73).

CONCLUSIONS

Recipients with HBV reactivation had worse outcomes and higher tumour recurrence rates than those without. The nomogram could be used to evaluate the risk of post-transplant HBV reactivation effectively.

Comparison of outcomes between preoperative and postoperative systemic treatment in patients with hepatocellular carcinoma: a SEER database-based study

Background

Significant advancements in systemic treatment for hepatocellular carcinoma have been made in recent years. However, the optimal timing of systemic treatment before or after surgery remains unknown. This study aims to evaluate the impact of sequencing systemic treatment and surgical intervention on the long-term prognosis of hepatocellular carcinoma patients.

Methods

In our study, we analyzed data from patients diagnosed with primary liver cancer (2004-2015) extracted from the SEER database. Patients who underwent both systemic treatment and surgical intervention were selected, divided into preoperative and postoperative systemic therapy groups. The primary endpoint of the study is overall survival(OS), and the secondary endpoint is cancer-specific survival (CSS). Propensity score matching (PSM) reduced the influence of confounding factors, while Kaplan-Meier curves and a multivariable Cox proportional hazards model accounted for variables during survival analysis.

Results

A total of 1918 eligible HCC patients were included, with 1406 cases in the preoperative systemic treatment group and 512 cases in the postoperative systemic treatment group. Survival analysis showed that both the preoperative group demonstrated longer median overall survival (OS) and median cancer-specific survival (CSS) before and after PSM. After conducting multivariate COX regression analysis with stepwise adjustment of input variables, the postoperative systemic treatment group continued to exhibit a higher risk of all-cause mortality (HR: 1.84, 95% CI: 1.55-2.1) and cancer-specific mortality (HR: 2.10, 95% CI: 1.73-2.54). Subgroup analysis indicated consistent results for overall survival (OS) across different subgroups.

Conclusions

Hepatocellular carcinoma patients from the SEER database who received preoperative systemic therapy had superior OS and CSS compared to those who received postoperative systemic therapy.

Prediction of microvascular invasion and pathological differentiation of hepatocellular carcinoma based on a deep learning model

PURPOSE

To develop a deep learning (DL) model based on preoperative contrast-enhanced computed tomography (CECT) images to predict microvascular invasion (MVI) and pathological differentiation of hepatocellular carcinoma (HCC).

METHODS

This retrospective study included 640 consecutive patients who underwent surgical resection and were pathologically diagnosed with HCC at two medical institutions from April 2017 to May 2022. CECT images and relevant clinical parameters were collected. All the data were divided into 368 training sets, 138 test sets and 134 validation sets. Through DL, a segmentation model was used to obtain a region of interest (ROI) of the liver, and a classification model was established to predict the pathological status of HCC.

RESULTS

The liver segmentation model based on the 3D U-Network had a mean intersection over union (mIoU) score of 0.9120 and a Dice score of 0.9473. Among all the classification prediction models based on the Swin transformer, the fusion models combining image information and clinical parameters exhibited the best performance. The area under the curve (AUC) of the fusion model for predicting the MVI status was 0.941, its accuracy was 0.917, and its specificity was 0.908. The AUC values of the fusion model for predicting poorly differentiated, moderately differentiated and highly differentiated HCC based on the test set were 0.962, 0.957 and 0.996, respectively.

CONCLUSION

The established DL models established can be used to noninvasively and effectively predict the MVI status and the degree of pathological differentiation of HCC, and aid in clinical diagnosis and treatment.

CT and MRI of abdominal cancers: current trends and perspectives in the era of radiomics and artificial intelligence

Abdominal cancers continue to pose daily challenges to clinicians, radiologists and researchers. These challenges are faced at each stage of abdominal cancer management, including early detection, accurate characterization, precise assessment of tumor spread, preoperative planning when surgery is anticipated, prediction of tumor aggressiveness, response to therapy, and detection of recurrence. Technical advances in medical imaging, often in combination with imaging biomarkers, show great promise in addressing such challenges. Information extracted from imaging datasets owing to the application of radiomics can be used to further improve the diagnostic capabilities of imaging. However, the analysis of the huge amount of data provided by these advances is a difficult task in daily practice. Artificial intelligence has the potential to help radiologists in all these challenges. Notably, the applications of AI in the field of abdominal cancers are expanding and now include diverse approaches for cancer detection, diagnosis and classification, genomics and detection of genetic alterations, analysis of tumor microenvironment, identification of predictive biomarkers and follow-up. However, AI currently has some limitations that need further refinement for implementation in the clinical setting. This review article sums up recent advances in imaging of abdominal cancers in the field of image/data acquisition, tumor detection, tumor characterization, prognosis, and treatment response evaluation.

Deep learning-based accurate diagnosis and quantitative evaluation of microvascular invasion in hepatocellular carcinoma on whole-slide histopathology images

BACKGROUND

Microvascular invasion (MVI) is an independent prognostic factor that is associated with early recurrence and poor survival after resection of hepatocellular carcinoma (HCC). However, the traditional pathology approach is relatively subjective, time-consuming, and heterogeneous in the diagnosis of MVI. The aim of this study was to develop a deep-learning model that could significantly improve the efficiency and accuracy of MVI diagnosis.

MATERIALS AND METHODS

We collected H&E-stained slides from 753 patients with HCC at the First Affiliated Hospital of Zhejiang University. An external validation set with 358 patients was selected from The Cancer Genome Atlas database. The deep-learning model was trained by simulating the method used by pathologists to diagnose MVI. Model performance was evaluated with accuracy, precision, recall, F1 score, and the area under the receiver operating characteristic curve.

RESULTS

We successfully developed a MVI artificial intelligence diagnostic model (MVI-AIDM) which achieved an accuracy of 94.25% in the independent external validation set. The MVI positive detection rate of MVI-AIDM was significantly higher than the results of pathologists. Visualization results demonstrated the recognition of micro MVIs that were difficult to differentiate by the traditional pathology. Additionally, the model provided automatic quantification of the number of cancer cells and spatial information regarding MVI.

CONCLUSIONS

We developed a deep learning diagnostic model, which performed well and improved the efficiency and accuracy of MVI diagnosis. The model provided spatial information of MVI that was essential to accurately predict HCC recurrence after surgery.

Comparative effectiveness of several adjuvant therapies after hepatectomy for hepatocellular carcinoma patients with microvascular invasion

BACKGROUND

For resectable hepatocellular carcinoma (HCC), radical hepatectomy is commonly used as a curative treatment. However, postoperative recurrence significantly diminishes the overall survival (OS) of HCC patients, especially with microvascular invasion (MVI) as an independent high-risk factor for recurrence. While some studies suggest that postoperative adjuvant therapy may decrease the risk of recurrence following liver resection in HCC patients, the specific role of adjuvant therapies in those with MVI remains unclear.

AIM

To conduct a network meta-analysis (NMA) to evaluate the efficacy of various adjuvant therapies and determine the optimal adjuvant regimen.

METHODS

A systematic literature search was conducted on PubMed, EMBASE, and Web of Science until April 6, 2023. Studies comparing different adjuvant therapies or comparing adjuvant therapy with hepatectomy alone were included. Hazard ratios (HRs) with 95% confidence intervals were used to combine data on recurrence free survival and OS in both pairwise meta-analyses and NMA.

RESULTS

Fourteen eligible trials (2268 patients) reporting five different therapies were included. In terms of reducing the risk of recurrence, radiotherapy (RT) [HR = 0.34 (0.23, 0.5); surface under the cumulative ranking curve (SUCRA) = 97.7%] was found to be the most effective adjuvant therapy, followed by hepatic artery infusion chemotherapy [HR = 0.52 (0.35, 0.76); SUCRA = 65.1%]. Regarding OS improvement, RT [HR: 0.35 (0.2, 0.61); SUCRA = 93.1%] demonstrated the highest effectiveness, followed by sorafenib [HR = 0.48 (0.32, 0.69); SUCRA = 70.9%].

CONCLUSION

Adjuvant therapy following hepatectomy may reduce the risk of recurrence and provide a survival benefit for HCC patients with MVI. RT appears to be the most effective adjuvant regimen.

Protein profiles reveal MSH6/MSH2 as a potential biomarker for hepatocellular carcinoma with microvascular invasion

AIM

Microvascular invasion (MVI) is an independent risk factor for postoperative recurrence and metastasis in hepatocellular carcinoma (HCC). However, the specific protein expression profiles that differentiate HCC with MVI from those without MVI remain unclear.

METHODS

The profiles of proteins in early-stage HCC tissues and normal liver tissues were characterized by quantitative proteomics techniques. Immunohistochemical (IHC) staining was undertaken on tissue microarrays from 80 HCC patients to assess the expression of MSH2 and MSH6. Cell counting, colony formation, migration, and invasion assays were carried out in vitro.

RESULTS

We identified 5164 proteins in both HCC tissues and adjacent normal liver tissues. Compared to HCC without MVI, 148 upregulated proteins and 97 downregulated proteins were found in HCC with MVI. Particularly noteworthy was the remarkable upregulation of MSH6/MSH2 among these dysregulated proteins in HCC with MVI. Further validation through bioinformatics prediction and IHC confirmed the elevated expression of MSH6/MSH2, which correlated with aggressive disease characteristics and poor prognosis. Receiver operating characteristic curve analyses revealed a substantial area under the curve of 0.761 (specificity 71.79%, sensitivity 73.17%) for the combined use of MSH6/MSH2. Knockdown of MSH6/MSH2 significantly inhibited HCC cell proliferation and invasion in vitro.

CONCLUSIONS

Our study establishes MSH6 or MSH2 as an oncogene that is prominently overexpressed during HCC progression, which provides new targets for HCC with MVI.

Pien Tze Huang Inhibits Migration and Invasion of Hepatocellular Carcinoma Cells by Repressing PDGFRB/YAP/CCN2 Axis Activity

OBJECTIVE

To investigate the effects of Pien Tze Huang (PZH) on the migration and invasion of HCC cells and underlying molecular mechanism.

METHODS

Cell counting kit-8 (CCK-8) was applied to evaluate the cell viabilities of SMMC-7721, SK-Hep-1, C3A and HL-7702 (6 × 103 cells/well) co-incubated with different concentrations of PZH (0, 0.2, 0.4, 0.6, 0.8 mg/mL) for 24 h. Transwell, wound healing assay, CCK-8 and Annexin V-FITC/PI staining were conducted to investigate the effects of PZH on the migration, invasion, proliferation and apoptosis of SK-Hep-1 and SMMC-7721 cells (650 µ g/mL for SK-Hep-1 cells and 330 µ g/mL for SMMC-7721 cells), respectively. In vivo, lung metastasis mouse model constructed by tail vein injection of HCC cells was used for evaluating the anti-metastasis function of PZH. SK-Hep-1 cells (106 cells/200 µ L per mice) were injected into B-NDG mice via tail vein. Totally 8 mice were randomly divided into PZH and control groups, 4 mice in each group. After 2-d inoculation, mice in the PZH group were administered with PZH (250 mg/kg, daily) and mice in the control group received only vehicle (PBS) from the 2nd day after xenograft to day 17. Transcriptome analysis based on RNA-seq was subsequently used for deciphering anti-tumor mechanism of PZH. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were applied to verify RNA-seq results. Luciferase reporter assay was performed to examine the transcriptional activity of yes-associated protein (YAP).

RESULTS

PZH treatment significantly inhibited the migration, invasion, proliferation and promoted the apoptosis of HCC cells in vitro and in vivo (P<0.01). Transcriptome analysis indicated that Hippo signaling pathway was associated with anti-metastasis function of PZH. Mechanical study showed PZH significantly inhibited the expressions of platelet derived growth factor receptor beta (PDGFRB), YAP, connective tissue growth factor (CCN2), N-cadherin, vimentin and matrix metallopeptidase 2 (MMP2, P<0.01). Meanwhile, the phosphorylation of YAP was also enhanced by PZH treatment in vitro and in vivo. Furthermore, PZH played roles in inhibiting the transcriptional activity of YAP.

CONCLUSION

PZH restrained migration, invasion and epithelial-mesenchymal transition of HCC cells through repressing PDGFRB/YAP/CCN2 axis.

Circulating Tumor DNA Clinical Applications in Hepatocellular Carcinoma: Current Trends and Future Perspectives

BACKGROUND

Globally, liver cancers are the second most lethal malignancy after lung cancer (0.83 million deaths in 2020). Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer and is typically associated with liver fibrosis or cirrhosis. HCC diagnosis relies on histologic examination of surgical specimens or conventional tissue biopsy material. However, standard tissue biopsies are invasive and often do not accurately reflect the tumor heterogeneity. On the other hand, the use of liquid biopsies, represented mainly by circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs), has greatly increased in the past 2 decades. Indeed, liquid biopsies are a noninvasive, repeatable, and sensitive approach to studying tumor biology.

CONTENT

This review describes current clinical applications of ctDNA analysis in the management of patients with chronic liver disease, cirrhosis, and HCC. There is a substantial clinical potential of ctDNA, but interventional studies are still lacking for the moment.

SUMMARY

Detection of ctDNA in both asymptomatic individuals and high-risk patients (with chronic liver disease or cirrhosis) contributes to the early diagnosis of HCC. ctDNA analysis also offer tremendous information on the tumor burden and on the risk of early recurrence. The implementation of ctDNA analysis, in association with classical tumor markers (e.g., alpha-fetoprotein), may improve (a) HCC screening in high-risk patients, (b) stratification of the recurrence risk after surgery, and (c) prognosis evaluation of patients with HCC.

Presence of onco-fetal neighborhoods in hepatocellular carcinoma is associated with relapse and response to immunotherapy

Onco-fetal reprogramming of the tumor ecosystem induces fetal developmental signatures in the tumor microenvironment, leading to immunosuppressive features. Here, we employed single-cell RNA sequencing, spatial transcriptomics and bulk RNA sequencing to delineate specific cell subsets involved in hepatocellular carcinoma (HCC) relapse and response to immunotherapy. We identified POSTN+ extracellular matrix cancer-associated fibroblasts (EM CAFs) as a prominent onco-fetal interacting hub, promoting tumor progression. Cell-cell communication and spatial transcriptomics analysis revealed crosstalk and co-localization of onco-fetal cells, including POSTN+ CAFs, FOLR2+ macrophages and PLVAP+ endothelial cells. Further analyses suggest an association between onco-fetal reprogramming and epithelial-mesenchymal transition (EMT), tumor cell proliferation and recruitment of Treg cells, ultimately influencing early relapse and response to immunotherapy. In summary, our study identifies POSTN+ CAFs as part of the HCC onco-fetal niche and highlights its potential influence in EMT, relapse and immunotherapy response, paving the way for the use of onco-fetal signatures for therapeutic stratification.

Extracellular contrast agent-enhanced MRI is as effective as gadoxetate disodium-enhanced MRI for predicting microvascular invasion in HCC

PURPOSE

To compare the performances of gadoxetate disodium-enhanced MRI (EOB-MRI) and extracellular contrast agent-enhanced MRI (ECA-MRI) for predicting microvascular invasion (MVI) in HCC.

MATERIALS AND METHODS

From November 2009 to December 2021, consecutive HCC patients who underwent preoperative contrast-enhanced MRI were retrospectively enrolled into either an ECA-MRI or EOB-MRI cohort. In the ECA-MRI cohort, a preoperative MVI score was constructed in the training dataset using a logistic regression model that evaluated pathological type. In a propensity score-matched testing dataset of the ECA-MRI cohort, the MVI score was validated and compared with a previously proposed EOB-MRI-based MVI score calculated in the EOB-MRI cohort. Time-to-early recurrence survival was evaluated by the Kaplan-Meier method with the log-rank test.

RESULTS

A total of 536 patients were included (478 men; 53 years, interquartile range, 46-62 years), 322 (60.1 %) with pathologically confirmed MVI. Based on the training dataset, independent variables associated with MVI included serum alpha-fetoprotein > 400 ng/ml (odds ratio [OR] = 2.3), infiltrative appearance (OR = 4.9), internal artery (OR = 2.5) and nodule-in-nodule architecture (OR = 2.4), which were incorporated into the ECA-MRI-based MVI score. The testing dataset AUC of the ECA-MRI score was 0.720, which was comparable to that of the EOB-MRI-based MVI score (AUC = 0.721; P =.99). Patients from either the ECA-MRI or the EOB-MRI cohort with model-predicted MVI had significantly shorter time-to-early recurrence than those without MVI (P <.001).

CONCLUSION

Based on the preoperative serum alpha-fetoprotein and three MRI features, ECA-MRI demonstrated comparable performance to EOB-MRI for predicting MVI in HCC.

Effect of transarterial chemoembolization as postoperative adjuvant therapy for intermediate-stage hepatocellular carcinoma with microvascular invasion: a multicenter cohort study

BACKGROUND

Intermediate-stage hepatocellular carcinoma (HCC) with microvascular invasion (MVI) is associated with high recurrence rates and poor survival outcomes after surgery. This study aimed to evaluate the efficacy of postoperative transarterial chemoembolization (TACE) on prognosis of intermediate-stage HCC patients with MVI after curative liver resection (LR).

MATERIALS AND METHODS

Patients who had intermediate-stage HCC with MVI and underwent curative LR between January 2013 and December 2019 at three institutions in China were identified for further analysis. Overall survival (OS) and recurrence-free survival (RFS) were compared between patients treated with and without postoperative TACE by propensity score-matching.

RESULTS

A total of 246 intermediate-stage HCC patients with MVI were enrolled, 137 entered into the LR group and 109 entered into the LR+TACE group. The 1-year, 3-year, and 5-year RFS rates were 42.0, 27.2, and 17.8% in LR+TACE group, and 31.8, 18.2, and 8.7% in LR group. The 1-year, 3-year, and 5-year OS rates were 81.7, 47.2, and 26.1% in the LR+TACE group, and 67.3, 35.6, and 18.5% in the LR group. Compared with LR alone, LR+TACE was associated with significantly better RFS [hazard ratio (HR), 1.443; 95% CI: 1.089-1.914; P =0.009] and OS (HR, 1.438; 95% CI: 1.049-1.972; P =0.023). No difference was observed with RFS and OS in single TACE and multiple TACE in the matched cohort.

CONCLUSION

Postoperative adjuvant TACE could be beneficial for intermediate-stage HCC patients with MVI.

Factors affecting overall survival and disease-free survival after surgery for hepatocellular carcinoma: a nomogram-based prognostic model-a Western European multicenter study

Few studies have assessed the clinical implications of the combination of different prognostic indicators for overall survival (OS) and disease-free survival (DFS) of resected hepatocellular carcinoma (HCC). This study aimed to evaluate the prognostic factors in HCC patients for OS and DFS outcomes and establish a nomogram-based prognostic model to predict the DFS of HCC. A multicenter, retrospective European study was conducted through the collection of data on 413 consecutive treated patients with a first diagnosis of HCC between January 2010 and December 2020. Univariate and multivariate Cox regression analyses were performed to identify all independent risk factors for OS and DFS outcomes. A nomogram prognostic staging model was subsequently established for DFS and its precision was verified internally by the concordance index (C-Index) and externally by calibration curves. For OS, multivariate Cox regression analysis indicated Child-Pugh B7 score (HR 4.29; 95% CI 1.74-10.55; p = 0.002) as an independent prognostic factor, along with Barcelona Clinic Liver Cancer (BCLC) stage ≥ B (HR 1.95; 95% CI 1.07-3.54; p = 0.029), microvascular invasion (MVI) (HR 2.54; 95% CI 1.38-4.67; p = 0.003), R1/R2 resection margin (HR 1.57; 95% CI 0.85-2.90; p = 0.015), and Clavien-Dindo Grade 3 or more (HR 2.73; 95% CI 1.44-5.18; p = 0.002). For DFS, multivariate Cox regression analysis indicated BCLC stage ≥ B (HR 2.15; 95% CI 1.34-3.44; p = 0.002) as an independent prognostic factor, along with multiple nodules (HR 2.04; 95% CI 1.25-3.32; p = 0.004), MVI (HR 1.81; 95% CI 1.19-2.75; p = 0.005), satellite nodules (HR 1.63; 95% CI 1.09-2.45; p = 0.018), and R1/R2 resection margin (HR 3.39; 95% CI 2.19-5.25; < 0.001). The C-Index of the nomogram, tailored based on the previous significant factors, showed good accuracy (0.70). Internal and external calibration curves for the probability of DFS rate showed optimal consistency and fit well between the nomogram-based prediction and actual observations. MVI and R1/R2 resection margins should be considered as significant OS and DFS predictors, while satellite nodules should be included as a significant DFS predictor. The nomogram-based prognostic model for DFS provides a more effective prognosis assessment for resected HCC patients, allowing for individualized treatment plans.

Recurrence-free Survival After Liver Transplantation Versus Surgical Resection for Hepatocellular Carcinoma: Role of High-risk MRI Features

BACKGROUND

This study aimed to evaluate recurrence-free survival (RFS) and overall survival (OS) after liver transplantation (LT) or liver resection (LR) for hepatocellular carcinoma (HCC) and perform subgroup analysis for HCC with high-risk imaging findings for recurrence on preoperative liver magnetic resonance imaging (MRI; high-risk MRI features).

METHODS

We included patients with HCC eligible for both LT and LR and received either of the treatments between June 2008 and February 2021 from 2 tertiary referral medical centers after propensity score-matching. RFS and OS were compared between LT and LR using Kaplan-Meier curves with the log-rank test.

RESULTS

Propensity score-matching yielded 79 patients in the LT group and 142 patients in the LR group. High-risk MRI features were noted in 39 patients (49.4%) in the LT group and 98 (69.0%) in the LR group. The Kaplan-Meier curves for RFS and OS were not significantly different between the 2 treatments among the high-risk group (RFS, P  = 0.079; OS, P  = 0.755). Multivariable analysis showed that treatment type was not a prognostic factor for RFS and OS ( P  = 0.074 and 0.937, respectively).

CONCLUSIONS

The advantage of LT over LR for RFS may be less evident among patients with high-risk MRI features.

Clinical benefits of intraoperative radiotherapy for the recurrence of centrally located hepatocellular carcinoma with microvascular invasion

BACKGROUND

Although the efficacy and safety of intraoperative radiotherapy (IORT) in the treatment of malignant tumours, such as breast cancer, have been documented, it remains unclear whether this treatment is effective for centrally located hepatocellular carcinoma (HCC) with microvascular invasion (MVI).

AIMS

This study aimed to explore the efficacy and safety of IORT in the treatment of centrally located HCC with MVI.

METHODS AND RESULTS

Patients with centrally located HCC, who underwent surgery between January 2016 and January 2020, were enrolled. The patient cohort was then allocated to two groups: those who underwent IORT combined with liver resection (IORT+LR); or LR alone (LR). Propensity score matching and Cox proportional hazards regression analyses were performed. The Kaplan-Meier method was used to estimate recurrence-free survival (RFS), and the log-rank test was used to determine whether RFS differed between the groups. Subgroup analysis was performed to evaluate differences in RFS and early recurrence rates in patients with different MVI grades. E-values were generated to measure the sensitivity to unmeasured confounding factors. In total, 97 patients were enrolled, 27 of whom underwent IORT+LR and 70 underwent LR alone. The 1-, 3-, and 5-year RFS rates in the IORT+LR group were 66%, 50%, and 32%, respectively, whereas those in the LR group were 54%, 37%, and 26%, respectively. After matching analysis, 23 patients were successfully matched, and RFS was found to be significantly different between the two groups (p = .04). IORT was an independent prognostic factor for RFS (hazard ratio 0.46 [95% confidence interval 0.21-0.99]). In subgroup analysis, RFS between the IORT+LR and LR groups was significantly different in patients with MVI (M1 grade) (p = .0067). The postoperative early recurrence rate was significantly reduced with IORT (p < .05). No serious complications were reported in either group following surgery. Based on E-values, the results appeared to be robust against unmeasured confounding factors.

CONCLUSION

IORT+LR provided safe, feasible treatment for patients with centrally located HCC with MVI, along with an improvement in prognosis and lower early recurrence rates.

A Nomogram of Magnetic Resonance Imaging for Preoperative Assessment of Microvascular Invasion and Prognosis of Hepatocellular Carcinoma

BACKGROUND

Microvascular invasion (MVI) is a predictor of recurrence and overall survival in hepatocellular carcinoma (HCC), the preoperative diagnosis of MVI through noninvasive methods play an important role in clinical treatment.

AIMS

To investigate the effectiveness of radiomics features in evaluating MVI in HCC before surgery.

METHODS

We included 190 patients who had undergone contrast-enhanced MRI and curative resection for HCC between September 2015 and November 2021 from two independent institutions. In the training cohort of 117 patients, MVI-related radiomics models based on multiple sequences and multiple regions from MRI were constructed. An independent cohort of 73 patients was used to validate the proposed models. A final Clinical-Imaging-Radiomics nomogram for preoperatively predicting MVI in HCC patients was generated. Recurrence-free survival was analyzed using the log-rank test.

RESULTS

For tumor-extracted features, the performance of signatures in fat-suppressed T1-weighted images and hepatobiliary phase was superior to that of other sequences in a single-sequence model. The radiomics signatures demonstrated better discriminatory ability than that of the Clinical-Imaging model for MVI. The nomogram incorporating clinical, imaging and radiomics signature showed excellent predictive ability and achieved well-fitted calibration curves, outperforming both the Radiomics and Clinical-Radiomics models in the training and validation cohorts.

CONCLUSIONS

The Clinical-Imaging-Radiomics nomogram model of multiple regions and multiple sequences based on serum alpha-fetoprotein, three MRI characteristics, and 12 radiomics signatures achieved good performance for predicting MVI in HCC patients, which may help clinicians select optimal treatment strategies to improve subsequent clinical outcomes.

Meta-analysis of Prognostic Factors for Overall Survival Among Resected Patients with Spontaneous Ruptured Hepatocellular Carcinoma

OBJECTIVE

Our meta-analysis was performed to explore the prognostic factors for overall survival among post-hepatectomy patients with spontaneous ruptured hepatocellular carcinoma (SRHCC).

METHODS

PubMed, EMBASE, the Cochrane Library, and Web of Science were all searched up for relevant studies regarding prognostic factors with SRHCC. RevMan5.3 software and Stata 14.0 software were used for statistical analysis.

RESULTS

A total of nineteen studies with 1876 resected SRHCC patients were finally identified. Pooled results indicated that preoperative AFP (high vs low) (P = 0.003), concurrent liver cirrhosis (yes vs no) (P = 0.02), preoperative liver function (child A vs non-child A) (P = 0.0007), tumor size (large vs small) (P < 0.00001), tumor number (solitary vs multiple) (P = 0.002), satellite foci (yes vs no) (P = 0.0006), micro-vascular invasion (yes vs no) (P < 0.00001), type of hepatectomy (major or minor) (P = 0.04), surgical margin (R + vs R -) (P < 0.00001), and type of hepatectomy (emergency hepatectomy vs staged hepatectomy) (P = 0.005) were prognostic factors for overall survival among post-hepatectomy SRHCC patients.

CONCLUSION

Apart from some conventional prognostic factors identified in resected patients with SRHCC, numerous prognostic factors have also been unmasked, which might provide clinical reference to stratify patients with different therapeutic regimes.

Circulating tumor cells participate in the formation of microvascular invasion and impact on clinical outcomes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor worldwide. Although the treatment strategies have been improved in recent years, the long-term prognosis of HCC is far from satisfactory mainly due to high postoperative recurrence and metastasis rate. Vascular tumor thrombus, including microvascular invasion (MVI) and portal vein tumor thrombus (PVTT), affects the outcome of hepatectomy and liver transplantation. If vascular invasion could be found preoperatively, especially the risk of MVI, more reasonable surgical selection will be chosen to reduce the risk of postoperative recurrence and metastasis. However, there is a lack of reliable prediction methods, and the formation mechanism of MVI/PVTT is still unclear. At present, there is no study to explore the possibility of tumor thrombus formation from a single circulating tumor cell (CTC) of HCC, nor any related study to describe the possible leading role and molecular mechanism of HCC CTCs as an important component of MVI/PVTT. In this study, we review the current understanding of MVI and possible mechanisms, discuss the function of CTCs in the formation of MVI and interaction with immune cells in the circulation. In conclusion, we discuss implications for potential therapeutic targets and the prospect of clinical treatment of HCC.

Repeat hepatectomy versus percutaneous ablation for recurrent hepatocellular carcinoma: emphasis on the impact of early or late recurrence

PURPOSE

Recurrent hepatocellular carcinoma (rHCC) patients with early recurrence usually suffer a poorer prognosis than those with late recurrence. We aimed to compare the treatment efficacy of repeat hepatectomy (RH) and percutaneous ablation (PA) in early-stage rHCC patients with early or late recurrence.

METHODS

This retrospective study enrolled 268 patients diagnosed with early-stage rHCC who received RH and PA. Overall survival (OS) and repeat recurrence-free survival (rRFS) were compared using log-rank analysis. Propensity score matching (PSM) was used to reduce the confounding bias.

RESULTS

Among the 268 patients with early-stage rHCC, 79 underwent RH and 189 underwent PA. Early (n = 174) and late (n = 94) recurrence was defined as recurrence within and after 2 years following initial hepatectomy, respectively. For patients with early recurrence, RH and PA provided similar 5-year OS (71.5% versus 74.4%, P = 0.87) and rRFS rates (24.7% versus 24.9%, P = 0.73). For patients with late recurrence, RH resulted in comparable 5-year OS (73.1% versus 86.1%, P = 0.62) and rRFS rates (36.6% versus 27.8%, P = 0.34) as PA. After PSM, RH continued to share similar 5-year OS and rRFS rates with PA in patients with early recurrence, and comparable efficacy of RH and PA was also observed in patients with late recurrence.

CONCLUSION

RH can offer comparable OS and rRFS rates as PA for early-stage rHCC patients, regardless of whether they experience early or late recurrence. Therefore, both RH and PA are feasible treatment options for early-stage rHCC patients.

Characterization of Microvascular Invasion in Hepatocellular Carcinoma Using Computational Modeling of Interstitial Fluid Pressure and Velocity

BACKGROUND

Most solid tumors show increased interstitial fluid pressure (IFP), and this increased IFP is an obstacle to treatment. A noninvasive model for measuring IFP in hepatocellular carcinoma (HCC) is an unresolved issue.

PURPOSE

To develop a noninvasive model to measure IFP and interstitial fluid velocity (IFV) in HCC and to characterize the microvascular invasion (MVI) status by using this model.

STUDY TYPE

Retrospective.

POPULATION

A total of 97 HCC patients (mean age 57.6 ± 10.9 years, 77.3% males), 53 of them with MVI and 44 of them without MVI.

FIELD STRENGTH/SEQUENCE

A 3-T, three-dimensional spoiled gradient-recalled echo.

ASSESSMENT

MVI was defined as microscopic vascular invasion of small vessels within the peritumoral liver tissue. The volumes of interest (VOIs) were manually delineated and enclosed the tumor lesion and healthy liver parenchyma, respectively. The extended Tofts model (ETM) was used to estimate permeability parameters from all the VOIs. Subsequently, the continuity partial differential equation (PDE) was implemented and IFP and IFV were acquired.

STATISTICAL TESTS

Wilcoxon signed-ranks tests, histogram analysis, Mann-Whitney U test, Fisher's exact test, least absolute shrinkage and selection operator (LASSO) logistic regression, receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC), Youden index, DeLong test, and Benjamini-Hochberg correction. A P value <0.05 was considered statistically significant.

RESULTS

The HCC lesions exhibited elevated IFP and reduced IFV. There were no significant differences in any measured demographic and clinical features between the MVI-positive and MVI-negative groups, except for tumor size. Nine IFP histogram analysis-derived parameters and seven IFV histogram analysis-derived parameters could be used to characterize the MVI status. LASSO regression selected five features: IFP maximum, IFP 10th percentile, IFP 90th percentile, IFV SD, and IFV 10th percentile. The combination of these features showed the highest AUC (0.781) and specificity (77.3%).

DATA CONCLUSION

A noninvasive IFP and IFV measurement model for HCC was developed. Specific IFP- and IFV-derived parameters exhibited significant association with the MVI status.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 2.

Deciphering intratumoral heterogeneity of hepatocellular carcinoma with microvascular invasion with radiogenomic analysis

BACKGROUND AND AIMS

The recurrence and metastasis of hepatocellular carcinoma (HCC) are mainly caused by microvascular invasion (MVI). Our study aimed to uncover the cellular atlas of MVI+ HCC and investigate the underlying immune infiltration patterns with radiomics features.

METHODS

Three MVI positive HCC and three MVI negative HCC samples were collected for single-cell RNA-seq analysis. 26 MVI positive HCC and 30 MVI negative HCC tissues were underwent bulk RNA-seq analysis. For radiomics analysis, radiomics features score (Radscore) were built using preoperative contrast MRI for MVI prediction and overall survival prediction. We deciphered the metabolism profiles of MVI+ HCC using scMetabolism and scFEA. The correlation of Radscore with the level of APOE+ macrophages and iCAFs was identified. Whole Exome Sequencing (WES) was applied to distinguish intrahepatic metastasis (IM) and multicentric occurrence (MO). Transcriptome profiles were compared between IM and MO.

RESULTS

Elevated levels of APOE+ macrophages and iCAFs were detected in MVI+ HCC. There was a strong correlation between the infiltration of APOE+ macrophages and iCAFs, as confirmed by immunofluorescent staining. MVI positive tumors exhibited increased lipid metabolism, which was attributed to the increased presence of APOE+ macrophages. APOE+ macrophages and iCAFs were also found in high levels in IM, as opposed to MO. The difference of infiltration level and Radscore between two nodules in IM was relatively small. Furthermore, we developed Radscore for predicting MVI and HCC prognostication that were also able to predict the level of infiltration of APOE+ macrophages and iCAFs.

CONCLUSION

This study demonstrated the interactions of cell subpopulations and distinct metabolism profiles in MVI+ HCC. Besides, MVI prediction Radscore and MVI prognostic Radscore were highly correlated with the infiltration of APOE+ macrophages and iCAFs, which helped to understand the biological significance of radiomics and optimize treatment strategy for MVI+ HCC.

A model based on adipose and muscle-related indicators evaluated by CT images for predicting microvascular invasion in HCC patients

BACKGROUND AND AIM

The presence of microvascular invasion (MVI) will impair the surgical outcome of hepatocellular carcinoma (HCC). Adipose and muscle tissues have been confirmed to be associated with the prognosis of HCC. We aimed to develop and validate a nomogram based on adipose and muscle related-variables for preoperative prediction of MVI in HCC.

METHODS

One hundred fifty-eight HCC patients from institution A (training cohort) and 53 HCC patients from institution B (validation cohort) were included, all of whom underwent preoperative CT scan and curative resection with confirmed pathological diagnoses. Least absolute shrinkage and selection operator (LASSO) logistic regression was applied to data dimensionality reduction and screening. Nomogram was constructed based on the independent variables, and evaluated by external validation, calibration curve, receiver operating characteristic (ROC) curve and decision curve analysis (DCA).

RESULTS

Histopathologically identified MVI was found in 101 of 211 patients (47.9%). The preoperative imaging and clinical variables associated with MVI were visceral adipose tissue (VAT) density, intramuscular adipose tissue index (IMATI), skeletal muscle (SM) area, age, tumor size and cirrhosis. Incorporating these 6 factors, the nomogram achieved good concordance index of 0.79 (95%CI: 0.72-0.86) and 0.75 (95%CI: 0.62-0.89) in training and validation cohorts, respectively. In addition, calibration curve exhibited good consistency between predicted and actual MVI probabilities. ROC curve and DCA of the nomogram showed superior performance than that of models only depended on clinical or imaging variables. Based on the nomogram score, patients were divided into high (> 273.8) and low (< = 273.8) risk of MVI presence groups. For patients with high MVI risk, wide-margin resection or anatomical resection could significantly improve the 2-year recurrence free survival.

CONCLUSION

By combining 6 preoperative independently predictive factors of MVI, a nomogram was constructed. This model provides an optimal preoperative estimation of MVI risk in HCC patients, and may help to stratify high-risk individuals and optimize clinical decision making.

Neoadjuvant intensity modulated radiotherapy for a single and small (≤5 cm) hepatitis B virus-related hepatocellular carcinoma predicted to have high risks of microvascular invasion: a randomized clinical trial

BACKGROUND

The presence of microvascular invasion (MVI) significantly impairs postoperative long-term survival of patients with hepatocellular carcinoma (HCC). The role of neoadjuvant radiotherapy (RT) in treating patients with an early-stage HCC predicted to have high risks of MVI remains to be explored.

MATERIALS AND METHODS

Consecutive patients with a resectable single and small (≤5 cm) hepatitis B virus-related HCC predicted to have high risks of MVI were randomized 1:1 to receive either neoadjuvant intensity modulated radiation therapy (18 Gy with fractionated doses of 3 Gy) followed by surgery 4 weeks later or upfront surgery. The primary endpoint was disease-free survival (DFS). The secondary outcomes included overall survival (OS), objective response rate, RT-related toxicity and surgical complications.

RESULTS

There were 30 patients randomized to each of the two groups. In the neoadjuvant RT group, three patients violated the study protocol, with two having upfront hepatectomy and one radiofrequency ablation after RT. The objective response rate after RT was 25.0% (7/28), but 2 patients suffered from grade 3 liver toxicity. The median follow-up was 68 months (interquartile range, 58-70 months) in the neoadjuvant RT group, and 68 months (interquartile range, 62-75 months) in the upfront surgery group. On intention-to-treat analysis, the median DFS and median OS were not reached in both the 2 arms. The 1-year, 2-year, 3-year and 5-year DFS rates for the neoadjuvant RT group were 86.7%, 76.7%, 60.0% and 56.3%, versus 90.0%, 66.7%, 52.8% and 45.7% in the upfront surgery group ( P =0.448), respectively. The corresponding OS rates were 96.7%, 86.7%, 83.3% and 72.7%, versus 100.0%, 93.3%, 79.6% and 60.7% ( P = 0.399).

CONCLUSION AND RELEVANCE

For patients with a resectable single and small hepatitis B virus-related HCC predicted to have high risks of MVI, neoadjuvant RT gave a promising response rate with a mild toxicity. Nevertheless, the neoadjuvant RT yielded similar long-term DFS and OS rates compared with patients who underwent upfront surgery.

Laparoscopic and open liver resection for hepatocellular carcinoma with type 2 diabetes mellitus: multicenter propensity score-matched study

PURPOSE

This study aimed at analyzing and comparing the perioperative results and long-term oncological outcomes of hepatocellular carcinoma (HCC) patients with type 2 diabetes mellitus (T2DM) treated with laparoscopic (LLR) versus open liver resection (OLR).

METHODS

Clinicopathological data of HCC patients with T2DM who underwent LLR or OLR as initial treatment from four medical centers were retrospectively reviewed. The survival outcomes of patients who underwent laparoscopic liver resection (LLR) were compared with those of patients who underwent open liver resection (OLR). Using the Kaplan-Meier method, survival curves for the two groups of patients were generated, and the log-rank test was used to compare survival differences. Propensity score matching (PSM) analysis was used to match patients of the LLR and OLR groups in a 1:1 ratio.

RESULTS

230 HCC patients with T2DM were enrolled, including 101 patients in the LLR group and 129 patients in the OLR group. After PSM, 90 patients were matched in each of the study group. Compared with the OLR group, the LLR group had less blood loss, a shorter hospitalization and fewer postoperative complications. The LLR group had a significantly better overall survival (OS) and recurrence-free survival (RFS) than the OLR group before and after PSM. Subgroup analysis demonstrated that HCC patients with T2DM had survival benefits from LLR regardless of the course of T2DM.

CONCLUSIONS

Laparoscopic liver resection for HCC patients with T2DM can be safely performed with favorable perioperative and long-term oncological outcomes at high-volume liver cancer centers, regardless of the course of T2DM.

Development of nomograms to predict recurrence after conversion hepatectomy for hepatocellular carcinoma previously treated with transarterial interventional therapy

BACKGROUND

Lack of opportunity for radical surgery and postoperative tumor recurrence are challenges for surgeons and hepatocellular carcinoma (HCC) patients. This study aimed to develop nomograms to predict recurrence risk and recurrence-free survival (RFS) probability after conversion hepatectomy for patients previously receiving transarterial interventional therapy.

METHODS

In total, 261 HCC patients who underwent conversion liver resection and previously received transarterial interventional therapy were retrospectively enrolled. Nomograms to predict recurrence risk and RFS were developed, with discriminative ability and calibration evaluated by C-statistics, calibration plots, and the Area under the Receiver Operator Characteristic (AUROC) curves.

RESULTS

Univariate/multivariable logistic regression and Cox regression analyses were used to identify predictive factors for recurrence risk and RFS, respectively. The following factors were selected as predictive of recurrence: age, tumor number, microvascular invasion (MVI) grade, preoperative alpha-fetoprotein (AFP), preoperative carbohydrate antigen 19-9 (CA19-9), and Eastern Cooperative Oncology Group performance score (ECOG PS). Similarly, age, tumor number, postoperative AFP, postoperative protein induced by vitamin K absence or antagonist-II (PIVKA-II), and ECOG PS were incorporated for the prediction of RFS. The discriminative ability and calibration of the nomograms revealed good predictive ability. Calibration plots showed good agreement between the nomogram predictions of recurrence and RFS and the actual observations.

CONCLUSIONS

A pair of reliable nomograms was developed to predict recurrence and RFS in HCC patients after conversion resection who previously received transarterial interventional therapy. These predictive models can be used as guidance for clinicians to help with treatment strategies.

Comparison of non-radiomics imaging features and radiomics models based on contrast-enhanced ultrasound and Gd-EOB-DTPA-enhanced MRI for predicting microvascular invasion in hepatocellular carcinoma within 5 cm

OBJECTIVES

The purpose of this study is to establish microvascular invasion (MVI) prediction models based on preoperative contrast-enhanced ultrasound (CEUS) and ethoxybenzyl-enhanced magnetic resonance imaging (EOB-MRI) in patients with a single hepatocellular carcinoma (HCC) ≤ 5 cm.

METHODS

Patients with a single HCC ≤ 5 cm and accepting CEUS and EOB-MRI before surgery were enrolled in this study. Totally, 85 patients were randomly divided into the training and validation cohorts in a ratio of 7:3. Non-radiomics imaging features, the CEUS and EOB-MRI radiomics scores were extracted from the arterial phase, portal phase and delayed phase images of CEUS and the hepatobiliary phase images of EOB-MRI. Different MVI predicting models based on CEUS and EOB-MRI were constructed and their predictive values were evaluated.

RESULTS

Since univariate analysis revealed that arterial peritumoral enhancement on the CEUS image, CEUS radiomics score, and EOB-MRI radiomics score were significantly associated with MVI, three prediction models, namely the CEUS model, the EOB-MRI model, and the CEUS-EOB model, were developed. In the validation cohort, the areas under the receiver operating characteristic curve of the CEUS model, the EOB-MRI model, and the CEUS-EOB model were 0.73, 0.79, and 0.86, respectively.

CONCLUSIONS

Radiomics scores based on CEUS and EOB-MRI, combined with arterial peritumoral enhancement on CEUS, show a satisfying performance of MVI predicting. There was no significant difference in the efficacy of MVI risk evaluation between radiomics models based on CEUS and EOB-MRI in patients with a single HCC ≤ 5 cm.

CLINICAL RELEVANCE STATEMENT

Radiomics models based on CEUS and EOB-MRI are effective for MVI predicting and conducive to pretreatment decision-making in patients with a single HCC within 5 cm.

KEY POINTS

• Radiomics scores based on CEUS and EOB-MRI, combined with arterial peritumoral enhancement on CEUS, show a satisfying performance of MVI predicting. • There was no significant difference in the efficacy of MVI risk evaluation between radiomics models based on CEUS and EOB-MRI in patients with a single HCC ≤ 5 cm.

Additional value of interleukin-6 level to predict histopathological features of hepatocellular carcinoma before liver transplantation

BACKGROUND & AIMS

Inflammatory biomarkers are increasingly used as outcome predictors in the field of oncology and liver transplantation for HCC, but no study has shown the prognostic value of IL6 after LT. The goal of this study was to evaluate the predictive value of IL-6 on histopathological features of HCC on explant, its predictive value on recurrence risk and its additional value to other scores and inflammatory markers at the time of transplantation.

METHODS

From 2009 to 2019, all adults transplanted with a first liver graft and diagnosed with HCC on the explant analysis were retrospectively included (n = 229). Only patients who had a pre-LT IL6 level determination were analysed in this study (n = 204).

RESULTS

High IL-6 level at transplantation was associated with a significantly higher risk of vascular invasion (15% vs 6%; p = 0.023), microsatellitosis (11% vs 3%; p = 0.013), lower rate of histological response both in terms of complete response (2% vs 14%, p = 0.004) and of necrosis (p = 0.010). Patients with pre-LT IL-6 level > 15 ng/ml had a lower overall and cancer-specific survival (p = 0.013). Recurrence-free survival was lower in patients with IL-6 > 15 ng/ml with a 3-year recurrence-free survival of 88% versus 78% (p = 0.034). IL6 levels were significantly higher in patients with early recurrence compared to patients without (p = 0.002) or with late recurrence (p = 0.044).

CONCLUSIONS

IL6 level at transplantation is an independent predictor of pejorative histological features of HCC and is associated to the risk of recurrence.

Contrast-Enhanced Ultrasound with Deep Learning with Attention Mechanisms for Predicting Microvascular Invasion in Single Hepatocellular Carcinoma

RATIONALE AND OBJECTIVES

Prediction of microvascular invasion (MVI) status of hepatocellular carcinoma (HCC) holds clinical significance for decision-making regarding the treatment strategy and evaluation of patient prognosis. We developed a deep learning (DL) model based on contrast-enhanced ultrasound (CEUS) to predict MVI of HCC.

MATERIALS AND METHODS

We retrospectively analyzed the data for single primary HCCs that were evaluated with CEUS 1 week before surgical resection from December 2014 to February 2022. The study population was divided into training (n = 198) and test (n = 54) cohorts. In this study, three DL models (Resnet50, Resnet50+BAM, Resnet50+SE) were trained using the training cohort and tested in the test cohort. Tumor characteristics were also evaluated by radiologists, and multivariate regression analysis was performed to determine independent indicators for the development of predictive nomogram models. The performance of the three DL models was compared to that of the MVI prediction model based on radiologist evaluations.

RESULTS

The best-performing model, ResNet50+SE model achieved the ROC of 0.856, accuracy of 77.2, specificity of 93.9%, and sensitivity of 52.4% in the test group. The MVI prediction model based on a combination of three independent predictors showed a C-index of 0.729, accuracy of 69.4, specificity of 73.8%, and sensitivity of 62%.

CONCLUSION

The DL algorithm can accurately predict MVI of HCC on the basis of CEUS images, to help identify high-risk patients for the assist treatment.