Performance of PIVKA-II for early hepatocellular carcinoma diagnosis and prediction of microvascular invasion

Establishment and Validation of Diagnostic Model of Microvascular Invasion in Solitary Hepatocellular Carcinoma

BACKGROUND

The microvascular invasion (MVI) score evaluates the presence of MVI in patients with hepatocellular carcinoma (HCC) by integrating multiple factors associated with MVI. We aimed to establish a MVI scoring system for HCC based on the clinical characteristics and serum biomarkers of patients with HCC.

METHODS

A total of 1027 patients with HCC hospitalized at Shandong Provincial Hospital from January 2016 to August 2021 were included and randomly divided into the development group and validation group at a ratio of 3:1. Univariable and multivariable logistic regression analyses were conducted to identify independent risk factors for MVI in HCC patients. Based on these independent risk factors, the preoperative MVI scoring system (diagnostic model) for HCC was established and verified. The receiver operating characteristic (ROC) curves, calibration curves and decision curve analyses (DCA) were employed to evaluate the discrimination and clinical application of the diagnostic model.

RESULTS

Independent risk factors for MVI of HCC involved Hepatitis B virus infection (HBV), large tumor diameter, higher logarithm of Alpha-fetoprotein (Log AFP), higher logarithm of AFP-L3% (Log AFP-L3%), higher logarithm of protein induced by vitamin K absence or antagonist-II (Log PIVKA-II) and higher logarithm of Carbohydrate antigen 125 (Log CA125). The diagnostic model incorporating these six independent risk factors was finally established. The areas under the ROC curve (AUC) assessed by the nomogram in the development cohort and validation cohort were 0.806 (95% CI, 0.773-0.839) and 0.818 (95% CI, 0.763-0.874) respectively. The calibration curve revealed that the results predicted by our diagnostic model for MVI in HCC were highly consistent with the postoperative pathological outcomes. The DCA further indicated promising clinical application of the diagnostic model.

CONCLUSION

An effective preoperative diagnostic model for MVI of HCC based on readily available tumor markers and clinical characteristics has been established, which is both clinically significant and easy to implement for diagnosing MVI.

Tumor biology characteristics score based on alpha-fetoprotein and protein induced by vitamin K absence or antagonist II as a predictor for recurrence and survival after curative resection for hepatocellular carcinoma: a multicenter cohort study

BACKGROUND

Current hepatocellular carcinoma (HCC) staging systems lack comprehensive assessment of tumor biologic characteristics. This study aimed to develop and validate a tumor biology characteristics score (TBCS) based on alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist II (PIVKA-II) to predict long-term oncologic outcomes after HCC resection.

METHODS

In this multicenter retrospective cohort study, patients who underwent curative resection for HCC between June 2018 and December 2022 were included. TBCS (range, 2-6 points) was calculated by combining preoperative AFP (<20, 20-199, and ≥200 ng/mL) and PIVKA-II levels (<40, 40-399, and ≥400 mAU/mL). Patients were stratified into low (2 points), medium (3-4 points), and high TBCS groups (5-6 points). The primary outcomes were recurrence-free survival (RFS) and overall survival (OS).

RESULTS

A total of 695 patients were analyzed; the low, medium, and high TBCS groups comprised 132 (19.0%), 233 (33.5%), and 330 patients (47.5%), respectively. Notably, 5-year RFS was 30.4%, 14.7%, and 9.7%, whereas 5-year OS was 42.1%, 35.5%, and 23.5% for low, medium, and high TBCS groups, respectively (both P <.001). Multivariate analysis identified TBCS as an independent predictor of both RFS (medium TBCS: hazard ratio [HR], 1.583; 95% CI, 1.219-2.057; P =.001; high TBCS: HR, 1.895; 95% CI, 1.473-2.438; P <.001) and OS (high TBCS: HR, 1.781; 95% CI, 1.353-2.343; P <.001).

CONCLUSION

The novel TBCS combining AFP and PIVKA-II effectively stratified patients with HCC into distinct prognostic groups after curative-intent resection, independently predicting both RFS and OS. This score may help identify high-risk patients for more intense postoperative recurrence surveillance and receipt of adjuvant therapies.

Preoperative plasma cell-free DNA chromosomal instability predicts microvascular invasion in hepatocellular carcinoma: a prospective study

BACKGROUND

Microvascular invasion (MVI) has been recognized as a risk factor for early recurrence after hepatectomy in patients with hepatocellular carcinoma (HCC). This study aimed to estimate the performance of an ultrasensitive chromosomal aneuploidy detector (UCAD) model for preoperative MVI prediction in operable HCC patients based on plasma cell-free DNA (cfDNA).

METHODS

A prospective study included HCC patients who underwent surgery in 2021. Preoperative peripheral plasma samples of eligible patients were collected to extract cfDNA, which was then subject to next generation sequencing. Low-coverage whole-genome sequencing data were analyzed for chromosomal instability using different parameters, including Z-score, chromosomal instability score (CIN score), tumor fraction (TFx) and a UCAD model (UCAD = CIN score + TFx + Z-score of all chromosomes). Receiver operating characteristic (ROC) curve was used to evaluate the performance of these parameters in preoperative MVI prediction.

RESULTS

Finally, a total of 74 patients with HCC who undergone hepatectomy were prospectively enrolled. Chromosomal instability was evaluated by copy number alterations and oncogenes MCL1 (located at 1q), MYC (located at 8q), TERT (located at 5p), EGFR (located at 7p), and VEGFA (located at 6p) were identified in plasma cfDNA. The UCAD model was a superior parameter in predicting preoperative MVI, with an area under curve (AUC) value 0.749 with a sensitivity of 0.938 specificity of 0.466. Univariate analysis revealed that tumor size (≥ 5 cm) and UCAD (> 0.199) significantly increased the risk of MVI, which were further demonstrated by multivariate analysis, with odd ratio of 1.338 (95%CI, 1.060-1.689) and 2.028 (95%CI, 1.053-3.908) (P < 0.05).

CONCLUSIONS

Our cfDNA-based UCAD model has shown a promising performance for preoperative MVI prediction in operable HCC patients.

TRIAL REGISTRATION

This study was registered at https://clinicaltrials.gov/ on 16 May 2022, retrospectively registered, Registration number: NCT05371873.

Radiomics Diagnosis of Microvascular Invasion in Hepatocellular Carcinoma Using 3D Ultrasound and Whole-Slide Image Fusion

This study aims to develop a machine learning model that accurately diagnoses microvascular invasion (MVI) in hepatocellular carcinoma by using radiomic features from MVI-positive regions of interest (ROIs). Unlike previous studies, which do not account for the location and distribution of MVI, this research focuses on correlating preoperative imaging with postoperative pathological MVI. This study involves obtaining ex vivo 3D ultrasound images of 36 hepatic specimens from nine rabbits. These images are fused with whole-slide images to localize MVI regions precisely. The identified MVI regions are segmented into MVI-positive ROIs, with a 1:3 ratio of positive to negative ROIs. Radiomic features are extracted from each ROI, and 30 features highly associated with MVI are selected for model development. The performance of several machine learning models is evaluated using metrics such as sensitivity, specificity, accuracy, the area under the curve (AUC), and F1 score. The GBDT model achieves the best results, with an AUC of 0.91, an F1 score of 0.85, a sensitivity of 0.76, a specificity of 0.92, and an accuracy of 0.86. The high diagnostic accuracy of these models highlights the potential for future clinical application in the precise diagnosis of MVI using radiomic features from MVI-positive ROIs.

Decision Fusion Model for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Multi-MR Habitat Imaging and Machine-Learning Classifiers

RATIONALE AND OBJECTIVES

Accurate prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is crucial for guiding treatment. This study evaluates and compares the performance of clinicoradiologic, traditional radiomics, deep-learning radiomics, feature fusion, and decision fusion models based on multi-region MR habitat imaging using six machine-learning classifiers.

MATERIALS AND METHODS

We retrospectively included 300 HCC patients. The intratumoral and peritumoral regions were segmented into distinct habitats, from which radiomics and deep-learning features were extracted using arterial phase MR images. To reduce feature dimensionality, we applied intra-class correlation coefficient (ICC) analysis, Pearson correlation coefficient (PCC) filtering, and recursive feature elimination (RFE). Based on the selected optimal features, prediction models were constructed using decision tree (DT), K-nearest neighbors (KNN), logistic regression (LR), random forest (RF), support vector machine (SVM), and XGBoost (XGB) classifiers. Additionally, fusion models were developed utilizing both feature fusion and decision fusion strategies. The performance of these models was validated using the area under the receiver operating characteristic curve (ROC AUC), calibration curves, and decision curve analysis.

RESULTS

The decision fusion model (VOI-Peri10-1) using LR and integrating clinicoradiologic, radiomics, and deep-learning features achieved the highest AUC of 0.808 (95% confidence interval [CI]: 0.807-0.912) in the test cohort, with good calibration (Hosmer-Lemeshow test, P > 0.050) and clinical net benefit.

CONCLUSION

The LR-based decision fusion model integrating clinicoradiologic, radiomics, and deep-learning features shows promise for preoperative prediction of MVI in HCC, aiding in patient outcome predictions and personalized treatment planning.

Real-world efficacy of radiomics versus clinical predictors for microvascular invasion in patients with hepatocellular carcinoma: Large cohort study

AIM

Microvascular invasion (MVI) affects the prognosis and treatment of hepatocellular carcinoma (HCC); however, its preoperative diagnosis is challenging. Analysis of computed tomography (CT) images using radiomics can detect MVI, but its effectiveness depends on the imaging conditions. We compared the efficacies of radiomics, clinical, and combined models for predicting MVI in HCC using nonstandardized scanning protocols.

METHODS

This multicenter study included 533 patients who underwent hepatic resection for HCC. Patients were divided randomly into training (n = 426) and test groups (n = 107). We manually extracted 3D CT features in hepatic arterial, portal venous, and venous phases. The radiomics model was trained by machine learning. A logistic regression model was developed based on clinical information, and a fused model was created integrating clinical information and radiomics prediction score (Rad_Score). We calculated areas under the receiver operating characteristic curves (AUCs) for the radiomics, clinical, and mixed models in the test groups.

RESULTS

The clinical model incorporated hepatitis B virus surface antigen, tumor diameter, and log-transformed α-fetoprotein and des-gamma-carboxyprothrombin. The AUCs of the radiomics and clinical models were comparable (p = 0.76). Rad_Score was not an independent significant factor in the fused model (p = 0.40) and its addition did not improve the accuracy of the clinical model alone (p = 0.51).

CONCLUSIONS

A clinical model is as effective as a CT radiomics model for predicting MVI status in patients with HCC based on real-world scanning data, and integration of both models does not improve the predictive performance compared with a clinical model alone.

Hepatocellular carcinoma: Revising the surgical approach in light of the concept of multiparametric therapeutic hierarchy

The clinical management of hepatocellular carcinoma (HCC) is strongly influenced by several prognostic factors, mainly tumor stage, patient's health, liver function and specific characteristics of each intervention. The interplay between these factors should be carefully evaluated by a multidisciplinary tumor board. To support this, the novel "multiparametric therapeutic hierarchy" (MTH) concept has been recently proposed. This review will present the main features of available surgical treatments for HCC (liver transplantation, liver resection, ablation). Strengths and weaknesses are reported in the light of clinical decision making and of treatment allocation, with a special focus on the collocation of each treatment in the MTH framework and on how MTH may be useful in supporting clinical decision. Sequential treatments and their role to allow further surgical treatments will also be analyzed.

Multiregional Radiomics to Predict Microvascular Invasion in Hepatocellular Carcinoma Using Multisequence MRI

OBJECTIVES

This study aimed to develop a multiregional radiomics-based model using multisequence MRI to predict microvascular invasion in hepatocellular carcinoma.

METHODS

We enrolled 141 patients with hepatocellular carcinoma, including 61 with microvascular invasion, who were diagnosed between March 2017 and July 2022. Clinical data were compared using the Wilcoxon rank-sum test or χ2 test. Patients were randomly divided into training (n=112, 80%) and test (n=29, 20%) data sets. Four MRI sequences-including T2-weighted imaging, T2-weighted imaging with fat suppression, arterial phase-contrast enhancement, and portal venous phase contrast enhancement-were used to build the radiomics model. The tumor volumes of interest were manually delineated, and the expand-5 mm and expand-10 mm volumes of interest were automatically generated. A total of 1409 radiomic features were extracted from each volume of interest. Feature selection was performed using the least absolute shrinkage and selection operator and Spearman correlation analysis. Three logistic regression models (Tumor, Tumor-Expand5, and Tumor-Expand10) were established based on the radiomic features. Model performance was assessed using receiver operating characteristic analysis and Delong's test.

RESULTS

Maximum tumor diameter, hepatitis B virus DNA, and aspartate aminotransferase levels were significantly different between the groups. The Tumor-Expand5mm model exhibited the best performance among the 3 models, with areas under the curve of 0.90 and 0.84 in the training and test data sets.

CONCLUSIONS

The Tumor-Expand5 model based on multisequence MRI shows great potential for predicting microvascular invasion in patients with hepatocellular carcinoma, and may further contribute to personal clinical decision-making.

Role of biomarkers in the diagnosis and management of HCC

For many cancers, biomarkers have served as an important tool across the cancer care continuum from risk stratification and early detection to diagnosis and treatment. Alpha-fetoprotein (AFP) remains one of the few validated biomarkers for patients with HCC. Although AFP has shown potential for each of these steps, its performance, when used alone, has often been suboptimal. There continue to be discordant recommendations about AFP's value when combined with ultrasound for surveillance, as well as its role in diagnostic algorithms. Conversely, high AFP levels are associated with aggressive tumor biology and survival, so it remains a key factor for the selection of candidates for liver transplant. There have been immense efforts to identify and validate additional biomarkers for each of these steps in the HCC care continuum. Indeed, biomarker panels have shown promising data for HCC risk stratification and surveillance among patients with cirrhosis, as well as prognostication and detection of minimal residual disease in patients undergoing HCC treatment. Several large prospective studies are currently ongoing to evaluate the role of these emerging biomarkers in clinical practice.

Comparative Validation of Prediction Models for HCC Outcomes in Living Donor Liver Transplantation: Superiority of Tumor Markers to Imaging Study

BACKGROUND

Living donor liver transplantation (LDLT) offers timely curative treatment for unresectable hepatocellular carcinoma (HCC). This study aims to validate and compare previous prediction models for HCC outcomes in 488 LDLT recipients.

METHODS

For 488 patients who underwent LDLT for HCC, pretransplant imaging studies assessed by modified RECSIT criteria, tumor markers such as alpha feto-protein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA II), and explant pathology were recruited. C-index of models for the HCC outcomes was compared, followed by further investigation for the predictive performances of the best model.

RESULTS

We found MoRAL (11√PIVKA-II + 2√AFP) demonstrated a higher C-index for HCC recurrence than other models that included radiologically viable tumor number and/or size (MoRAL: 0.709, Milan: 0.537, UCSF: 0.575, Up-to-7: 0.572, French AFP: 0.634, Pre-MORAL: 0.637, HALT-HCC: 0.626, Metroticket2.0: 0.629) and also had the highest C-index for HCC-specific deaths (0.706). Five-year HCC recurrence was well stratified upon dividing the patients into three groups by MoRAL cutoffs (11.9% for MoRAL < 100, 29.6% for MoRAL 100-200, and 48.6% for MoRAL > 200, p < 0.001). However, patients with major vessel invasion or portal vein tumor thrombus showed similarly high HCC recurrence regardless of this grouping (p = 0.612).

CONCLUSION

The MoRAL, based on tumor markers, showed the best predictive performance for HCC recurrence and HCC-specific death among the validated models, except in cases with major vessel invasion or portal vein tumor thrombus.

Diagnostic Performance of PIVKA-II in Italian Patients with Hepatocellular Carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) represents the second leading cause of cancer deaths worldwide. Six-month imaging along with alpha-fetoprotein (AFP) serum levels detection are the current gold standard to exclude HCC. Protein induced by vitamin K absence (PIVKA-II) has been proposed as a potential screening biomarker for HCC. This study was designed to evaluate the role of PIVKA-II as diagnostic HCC marker, and the correlation between PIVKA-II levels and HCC stage.

METHODS

PIVKA-II levels were assessed on serum samples of Italian patients. The study population included 80 patients with HCC, 111 with liver cirrhosis (LC), and 111 with chronic hepatitis C (CHC).

RESULTS

PIVKA-II serum levels progressively increase from patients with CHC to patients with HCC. In the HCC group, PIVKA-II values are higher in the more advanced stages of the disease, assessed by the Barcelona Clinic Liver Cancer (BCLC) staging system (BCLC-B vs. BCLC-A vs. BCLC-0). Youden's index analysis identified a value >37 mAU/mL as the optimal threshold for the best combination of sensitivity and specificity (80% and 76%, respectively) and, at the best cut-off of 5.2 ng/mL, AFP yielded 53% specificity and 78% sensitivity. The combination of PIVKA-II and AFP reached positive and negative predictive values of 73.9% and 94.2%, respectively.

CONCLUSIONS

PIVKA-II levels are increased in the HCC patients, compared to control groups. The increase is more evident in patients with advanced HCC. The diagnostic performance of PIVKA-II seems more sensitive than AFP while the combination of PIVKA-II and AFP resulted in the best diagnostic accuracy, reaching 73.9% positive predictive value and 94.2% negative predictive value, thus improving the diagnostic capability of the single marker.

Prognostic significance of early alpha fetoprotein and des-gamma carboxy prothrombin responses in unresectable hepatocellular carcinoma patients undergoing triple combination therapy

Background

Recent advancements in combination therapy for unresectable hepatocellular carcinoma (uHCC) have shown promise, but reliable serological prognostic indicators are currently lacking for patients undergoing triple combination therapy of stereotactic body radiation therapy (SBRT), immunotherapy, and targeted therapy. We aimed to investigate the prognostic significance of early alpha fetoprotein (AFP) and des-gamma-carboxy prothrombin (DCP) responses in these patients.

Methods

This retrospective research included 115 uHCC patients treated with SBRT in combination with immunotherapy and targeted therapy (triple therapy) at our institution from April 2021 to December 2022. Participants were categorized into high AFP and high DCP cohorts based on baseline levels. AFP and DCP responses were defined as decreases from baseline of over 50% and 70%, respectively, according to ROC curve analysis. Differences in overall survival (OS), progression-free survival (PFS), and objective response rate (ORR) were assessed between the tumor biomarker response and non-response groups.

Results

Multivariate analysis indicated that AFP or DCP response at 6-8 weeks post-therapy significantly influenced ORR (high AFP cohort: odds ratio [OR] 5.50, 95% CI 2.04-14.83, p=0.001; high DCP cohort: OR 7.99, 95%CI 2.82-22.60, p<0.001). The median PFS was notably longer in tumor biomarker response groups (high AFP cohort: 13.7 vs 6.2 months, hazard ratio [HR] 0.36, 95% CI 0.20-0.62, p<0.001; high DCP cohort: 15.6 vs 9.3 months, HR 0.44, 95% CI 0.26-0.74, p=0.002). AFP or DCP response was associated with prolonged OS (high AFP cohort: not reached vs. 21.9 months, HR 0.47, 95% CI 0.22-0.99, p=0.047; high DCP cohort: not reached vs. 20.6 months, HR 0.35, 95% CI 0.14-0.86, p=0.022).

Conclusion

AFP or DCP response at 6-8 weeks post-therapy predicts better oncological outcomes in patients with uHCC treated with triple therapy.

Prognostic significance of postoperative serological incomplete conversion of AFP and PIVKA-II after hepatic resection for hepatocellular carcinoma: a multicenter analysis of 1755 patients

BACKGROUND

The value of serum biomarkers, particularly alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II), gains increasing attention in prognostic evaluation and recurrence monitoring for patients with hepatocellular carcinoma (HCC). This study investigated the implications of serological incomplete conversion (SIC) of these 2 biomarkers as prognostic indicators for long-term outcomes after HCC resection.

METHODS

A multicenter observational study was conducted on a cohort of HCC patients presenting with AFP (>20 ng/mL) or PIVKA-II (>40 mAU/mL) positivity who underwent curative-intent resection. Based on their postoperative AFP and PIVKA-II levels at first postoperative follow-up (4~8 weeks after surgery), these patients were stratified into the serological incomplete conversion (SIC) and serological complete conversion (SCC) groups. The study endpoints were recurrence and overall survival (OS).

RESULTS

Among 1755 patients, 379 and 1376 were categorized as having SIC and SCC, respectively. The SIC group exhibited 1- and 5-year OS rates of 67.5% and 26.3%, with the corresponding recurrence rates of 53.2% and 79.0%, respectively; while the SCC group displayed 1- and 5-year OS rates of 95.8% and 62.5%, with the corresponding recurrence rates of 16.8% and 48.8%, respectively (both P < .001). Multivariate Cox regression analysis demonstrated that postoperative SIC was an independent risk factor for both increased recurrence (HR: 2.40, 95% CI, 2.04-2.81, P < .001) and decreased OS (HR: 2.69, 95% CI, 2.24-3.24, P < .001).

CONCLUSION

The results emphasize that postoperative incomplete conversion of either AFP or PIVKA-II is a significant prognostic marker, indicating a higher risk for adverse oncologic outcomes following HCC resection. This revelation has crucial implications for refining postoperative adjuvant therapy and surveillance strategies for HCC patients.

Blood biomarkers of hepatocellular carcinoma: a critical review

Hepatocellular Carcinoma (HCC) is a malignant tumor with high morbidity and mortality worldwide, which represents a serious threat to human life, health and quality of life. Blood-based detection is essential for HCC screening, early diagnosis, prognosis evaluation, and surveillance. Current non-invasive detection strategy including serum alpha-fetoprotein (AFP), ultrasound, computerized tomography, and magnetic resonance imaging. The limited specificity of an AFP and the dependence on operator experience and diagnostic personnel for ultrasound have constrained their utility in early HCC diagnosis. In recent years, with the development of various detection technologies, there has been an increasing focus on exploring blood-based detection markers for HCC. The types of markers include protein markers, DNA mutation, DNA epigenetic modification, mRNA, miRNA, and so on. However, numerous methodological and biological factors limit the clinical sensitivity and generalization performance of these new biomarkers. In this review, we describe the state-of-the-art technologies for cfDNA analysis, and discuss outstanding biological and technical challenges that, if addressed, would substantially improve HCC diagnostics and patient care.

Recurrence risk prediction models for hepatocellular carcinoma after liver transplantation

Liver transplantation (LT) is an effective method for curing hepatocellular carcinoma (HCC). However postoperative tumor recurrence can lead to higher mortality rates. To select suitable candidates for LT, the Milan Criteria (MC) were first proposed based on tumor morphological characteristics. For those patients who meet the MC, the MC can effectively reduce the postoperative tumor recurrence rate and improve the prognosis of patients undergoing LT. It has always been internationally recognized as the gold standard for selecting candidates for LT, marking a milestone in the history of LT for HCC. However, its strict conditions exclude some HCC patients who could benefit from LT. Therefore, comprehension consideration criteria, including serum biomarkers, tumor histology, and other factor, have been continuously proposed in addition to tumor morphology. This article summaries the prediction model for HCC recurrence after LT from five aspects: tumor morphology, serum markers, histopathology, cellular inflammatory factors and downstaging treatment before transplantation. The aim is to assist clinicians in accurately assessing HCC status, selecting appropriate liver transplant candidates, maximize graft and patients' survival, and optimizing the utilization of social health resources.

Prediction of microvascular invasion in hepatocellular carcinoma with conventional ultrasound, Sonazoid-enhanced ultrasound, and biochemical indicator: a multicenter study

PURPOSE

To develop and validate a preoperative prediction model based on multimodal ultrasound and biochemical indicator for identifying microvascular invasion (MVI) in patients with a single hepatocellular carcinoma (HCC) ≤ 5 cm.

METHODS

From May 2022 to November 2023, a total of 318 patients with pathologically confirmed single HCC ≤ 5 cm from three institutions were enrolled. All of them underwent preoperative biochemical, conventional ultrasound (US), and contrast-enhanced ultrasound (CEUS) (Sonazoid, 0.6 mL, bolus injection) examinations. Univariate and multivariate logistic regression analyses on clinical information, biochemical indicator, and US imaging features were performed in the training set to seek independent predictors for MVI-positive. The models were constructed and evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis in both validation and test sets. Subgroup analyses in patients with different liver background and tumor sizes were conducted to further investigate the model's performance.

RESULTS

Logistic regression analyses showed that obscure tumor boundary in B-mode US, intra-tumoral artery in pulsed-wave Doppler US, complete Kupffer-phase agent clearance in Sonazoid-CEUS, and biomedical indicator PIVKA-II were independently correlated with MVI-positive. The combined model comprising all predictors showed the highest AUC, which were 0.937 and 0.893 in the validation and test sets. Good calibration and prominent net benefit were achieved in both sets. No significant difference was found in subgroup analyses.

CONCLUSIONS

The combination of biochemical indicator, conventional US, and Sonazoid-CEUS features could help preoperative MVI prediction in patients with a single HCC ≤ 5 cm.

CRITICAL RELEVANCE STATEMENT

Investigation of imaging features in conventional US, Sonazoid-CEUS, and biochemical indicators showed a significant relation with MVI-positivity in patients with a single HCC ≤ 5 cm, allowing the construction of a model for preoperative prediction of MVI status to help treatment decision making.

KEY POINTS

MVI status is important for patients with a single HCC ≤ 5 cm. The model based on conventional US, Sonazoid-CEUS and PIVKA-II performs best for MVI prediction. The combined model has potential for preoperative prediction of MVI status.

Exosomal mRNA in plasma serves as a predictive marker for microvascular invasion in hepatocellular carcinoma

BACKGROUND AND AIM

There is a pressing need for non-invasive preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). This study investigates the potential of exosome-derived mRNA in plasma as a biomarker for diagnosing MVI.

METHODS

Patients with suspected HCC undergoing hepatectomy were prospectively recruited for preoperative peripheral blood collection. Exosomal RNA profiling was conducted using RNA sequencing in the discovery cohort, followed by differential expression analysis to identify candidate targets. We employed multiplexed droplet digital PCR technology to efficiently validate them in a larger sample size cohort.

RESULTS

A total of 131 HCC patients were ultimately enrolled, with 37 in the discovery cohort and 94 in the validation cohort. In the validation cohort, the expression levels of RSAD2, PRPSAP1, and HOXA2 were slightly elevated while CHMP4A showed a slight decrease in patients with MVI compared with those without MVI. These trends were consistent with the findings in the discovery cohort, although they did not reach statistical significance (P > 0.05). Notably, the expression level of exosomal PRPSAP1 in plasma was significantly higher in patients with more than 5 MVI than in those without MVI (0.147 vs 0.070, P = 0.035).

CONCLUSION

This study unveils the potential of exosome-derived PRPSAP1 in plasma as a promising indicator for predicting MVI status preoperatively.

Preoperative Gadoxetic Acid-Enhanced MRI Features for Evaluation of Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma: Creating Nomograms for Risk Assessment

BACKGROUND

Vessels encapsulating tumor cluster (VETC) and microvascular invasion (MVI) have a synergistic effect on prognosis assessment and treatment selection of hepatocellular carcinoma (HCC). Preoperative noninvasive evaluation of VETC and MVI is important.

PURPOSE

To explore the diagnosis value of preoperative gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) features for MVI, VETC, and recurrence-free survival (RFS) in HCC.

STUDY TYPE

Retrospective.

POPULATION

240 post-surgery patients with 274 pathologically confirmed HCC (allocated to training and validation cohorts with a 7:3 ratio) and available tumor marker data from August 2014 to December 2021.

FIELD STRENGTH/SEQUENCE

3-T, T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging.

ASSESSMENT

Three radiologists subjectively reviewed preoperative MRI, evaluated clinical and conventional imaging features associated with MVI+, VETC+, and MVI+/VETC+ HCC. Regression-based nomograms were developed for HCC in the training cohort. Based on the nomograms, the RFS prognostic stratification system was further. Follow-up occurred every 3-6 months.

STATISTICAL TESTS

Chi-squared test or Fisher's exact test, Mann-Whitney U-test or t-test, least absolute shrinkage and selection operator-penalized, multivariable logistic regression analyses, receiver operating characteristic analysis, Harrell's concordance index (C-index), Kaplan-Meier plots. Significance level: P < 0.05.

RESULTS

In the training group, 44 patients with MVI+ and 74 patients with VETC+ were histologically confirmed. Three nomograms showed good performance in the training (C-indices: MVI+ vs. VETC+ vs. MVI+/VETC+, 0.892 vs. 0.848 vs. 0.910) and validation (C-indices: MVI+ vs. VETC+ vs. MVI+/VETC+, 0.839 vs. 0.810 vs. 0.855) cohorts. The median follow-up duration for the training cohort was 43.6 (95% CI, 35.0-52.2) months and 25.8 (95% CI, 16.1-35.6) months for the validation cohort. Patients with either pathologically confirmed or nomogram-estimated MVI, VETC, and MVI+/VETC+ suffered higher risk of recurrence.

DATA CONCLUSION

GA-enhanced MRI and clinical variables might assist in preoperative estimation of MVI, VETC, and MVI+/VETC+ in HCC.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Clinical Nomogram Model for Pre-Operative Prediction of Microvascular Invasion of Hepatocellular Carcinoma before Hepatectomy

Background and Objectives: Microvascular invasion (MVI) significantly impacts recurrence and survival rates after liver resection in hepatocellular carcinoma (HCC). Pre-operative prediction of MVI is crucial in determining the treatment strategy. This study aims to develop a nomogram model to predict the probability of MVI based on clinical features in HCC patients. Materials and Methods: A total of 489 patients with a pathological diagnosis of HCC were enrolled from our hospital. Those registered from 2012-2015 formed the derivation cohort, and those from 2016-2019 formed the validation cohort for pre-operative prediction of MVI. A nomogram model for prediction was created using a regression model, with risk factors derived from clinical and tumor-related features before surgery. Results: Using the nomogram model to predict the odds ratio of MVI before hepatectomy, the AFP, platelet count, GOT/GPT ratio, albumin-alkaline phosphatase ratio, ALBI score, and GNRI were identified as significant variables for predicting MVI. The Youden index scores for each risk variable were 0.287, 0.276, 0.196, 0.185, 0.115, and 0.112, respectively, for the AFP, platelet count, GOT/GPT ratio, AAR, ALBI, and GNRI. The maximum value of the total nomogram scores was 220. An increase in the number of nomogram points indicated a higher probability of MVI occurrence. The accuracy rates ranged from 55.9% to 64.4%, and precision rates ranged from 54.3% to 68.2%. Overall survival rates were 97.6%, 83.4%, and 73.9% for MVI(-) and 80.0%, 71.8%, and 41.2% for MVI(+) (p < 0.001). The prognostic effects of MVI(+) on tumor-free survival and overall survival were poor in both the derivation and validation cohorts. Conclusions: Our nomogram model, which integrates clinical factors, showed reliable calibration for predicting MVI and provides a useful tool enabling surgeons to estimate the probability of MVI before resection. Consequently, surgical strategies and post-operative care programs can be adapted to improve the prognosis of HCC patients where possible.

Construction of an immunosensor based on Cys/Au@TiO2 modification for the detection of liver cancer marker PIVKA-II

An ultrasensitive immunosensor of Cys/Au@TiO2 based on disposable screen-printed electrodes (SPE) for PIVKA-II detection for hepatocellular carcinoma (HCC) diagnosis was developed by utilizing Cystine (Cys) and nanocomposite Au@TiO2. Firstly, HAuCl4 underwent a reduction reaction with NaBH4, then Au nanoparticles were coated onto TiO2 nanoparticles. Followed, Cys/Au@TiO2 was formed through self-assembly of cysteine to allow the monoclonal antibody of abnormal thrombospondin to bound to the amino group on the surface of the composite by covalent bonding. The mechanism is to determine the changes in the current of the sensor caused by the specific binding of the abnormal prothrombin monoclonal antibody adsorbed by the complex with its antigen. The Cys/Au@TiO2 immunosensor was fully characterized by various analytical approaches and it showed a wide linear testing range of 1-10000 pg mL-1 (R2 = 0.991) and the limit of detection down to 0.77 pg ml-1, with highly sensitivity and specificity. The results showed that the developed immunosensor platform can effectively detect trace amounts of PIVKA-II protein and has potent clinical application for HCC diagnosis.

New predictors of microvascular invasion for small hepatocellular carcinoma ≤ 3 cm

BACKGROUND

Microvascular invasion (MVI) is a risk factor for postoperative recurrence of hepatocellular carcinoma (HCC), even in early-stage HCC. In small HCC ≤ 3 cm, treatment options include anatomical resection or non-anatomical resection, and MVI has a major effect on treatment decisions. We aimed to identify the predictors of MVI in small HCC ≤ 3 cm.

METHODS

We retrospectively studied 129 patients with very early or early-stage HCC ≤ 3 cm who had undergone 18F-fluorodeoxyglucose positron emission tomography/computed tomography and subsequent hepatic resection from January 2016 to August 2023. These patients were divided into the derivation cohort (n = 86) and validation cohort (n = 43). We examined the risk factors for MVI using logistic regression analysis, and established a predictive scoring system in the derivation cohort. We evaluated the accuracy of our scoring system in the validation cohort.

RESULTS

In the derivation cohort, a Lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3), prothrombin induced by vitamin K deficiency or antagonist-II (PIVKA-II), and metabolic tumor volume (MTV) were independent predictors of MVI. We established the scoring system using these three factors. In the validation test, there were no MVI-positive cases with a score of 0 and 1, and all cases were MVI-positive with a score of 4. Moreover, with a score ≥ 2, the sensitivity, specificity, and accuracy of our scoring system were 100%, 71.4%, and 81.4%, respectively.

CONCLUSIONS

Our scoring system can accurately predict MVI in small HCC ≤ 3 cm, and could contribute to establishing an appropriate treatment strategy.

PIVKA-II combined with alpha-fetoprotein for the diagnostic value of hepatic tumors in children: a multicenter, prospective observational study

BACKGROUND

To investigate whether protein induced by vitamin K antagonist-II (PIVKA-II) combined with alpha-fetoprotein (AFP) can improve the diagnostic and differential diagnostic accuracy of childhood hepatic tumors.

METHODS

A multi-center prospective observational study was performed at nine regional institutions around China. Children with hepatic mass (Group T) were divided into hepatoblastoma group (Group THB) and hemangioendothelioma group (Group THE), children with extrahepatic abdominal mass (Group C). Peripheral blood was collected from each patient prior to surgery or chemotherapy. The area under the curve (AUROC) was used to evaluate the diagnostic efficiency of PIVKA-II and the combined tumor markers with AFP.

RESULTS

The mean levels of PIVKA-II and AFP were both significantly higher in Group T than Group C (p = 0.001, p < 0.001), in Group THB than Group THE (p = 0.018, p = 0.013) and in advanced HB than non-advanced HB (p = 0.001, p = 0.021). For the diagnosis of childhood hepatic tumors, AUROC of PIVKA-II (cut-off value 32.6 mAU/mL) and AFP (cut-off value 120 ng/mL) was 0.867 and 0.857. The differential diagnostic value of PIVKA-II and AFP in hepatoblastoma from hemangioendothelioma was further assessed, AUROC of PIVKA-II (cut-off value 47.1mAU/mL) and AFP (cut-off value 560 ng/mL) was 0.876 and 0.743. The combined markers showed higher AUROC (0.891, 0.895 respectively) than PIVKA-II or AFP alone.

CONCLUSIONS

The serum level of PIVKA-II was significantly higher in children with hepatic tumors, especially those with malignant tumors. The combination of PIVKA-II with AFP further increased the diagnostic performance.

TRIAL REGISTRATION

Clinical Trials, NCT03645655. Registered 20 August 2018, https://www.

CLINICALTRIALS

gov/ct2/show/NCT03645655 .

Latest insights into the epidemiology, characteristics, and therapeutic strategies of chronic hepatitis B patients in indeterminate phase

As a hepatotropic virus, hepatitis B virus (HBV) can establish a persistent chronic infection in the liver, termed, chronic hepatitis B (CHB), which causes a series of liver-related complications, including fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). HCC with HBV infection has a significantly increased morbidity and mortality, whereas it could be preventable. The current goal of antiviral therapy for HBV infection is to decrease CHB-related morbidity and mortality, and achieve sustained suppression of virus replication, which is known as a functional or immunological cure. The natural history of chronic HBV infection includes four immune phases: the immune-tolerant phase, immune-active phase, inactive phase, and reactivation phase. However, many CHB patients do not fit into any of these defined phases and are regarded as indeterminate. A large proportion of indeterminate patients are only treated with dynamic monitoring rather than recommended antiviral therapy, mainly due to the lack of definite guidelines. However, many of these patients may gradually have significant liver histopathological changes during disease progression. Recent studies have focused on the prevalence, progression, and carcinogenicity of indeterminate CHB, and more attention has been given to the prevention, detection, and treatment for these patients. Herein, we discuss the latest understanding of the epidemiology, clinical characteristics, and therapeutic strategies of indeterminate CHB, to provide avenues for the management of these patients.

Development of a diagnostic nomogram for alpha-fetoprotein-negative hepatocellular carcinoma based on serological biomarkers

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Serum biomarkers play an important role in the early diagnosis and prognosis of HCC. Because a certain percentage of HCC patients are negative for alpha-fetoprotein (AFP), the diagnosis of AFP-negative HCC is essential to improve the detection rate of HCC.

AIM

To establish an effective model for diagnosing AFP-negative HCC based on serum tumour biomarkers.

METHODS

A total of 180 HCC patients were enrolled in this study. The expression levels of GP73, des-γ-carboxyprothrombin (DCP), CK18-M65, and CK18-M30 were detected by a fully automated chemiluminescence analyser. The variables were selected by logistic regression analysis. Several models were constructed using stepwise backward logistic regression. The performance of the models was compared using the C statistic, integrated discrimination improvement, net reclassification improvement, and calibration curves. The clinical utility of the nomogram was assessed using decision curve analysis (DCA).

RESULTS

The results showed that the expression levels of GP73, DCP, CK18-M65, and CK18-M30 were significantly greater in AFP-negative HCC patients than in healthy controls (P < 0.001). Multivariate logistic regression analysis revealed that GP73, DCP, and CK18-M65 were independent factors for diagnosing AFP-negative HCC. By comparing the diagnostic performance of multiple models, we included GP73 and CK18-M65 as the model variables, and the model had good discrimination ability (area under the curve = 0.946) and good goodness of fit. The DCA curves indicated the good clinical utility of the nomogram.

CONCLUSION

Our study identified GP73 and CK18-M65 as serum biomarkers with certain application value in the diagnosis of AFP-negative HCC. The diagnostic nomogram based on CK18-M65 combined with GP73 demonstrated good performance and effectively identified high-risk groups of patients with HCC.

Development of a diagnostic nomogram for alpha-fetoprotein-negative hepatocellular carcinoma based on serological biomarkers

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Serum biomarkers play an important role in the early diagnosis and prognosis of HCC. Because a certain percentage of HCC patients are negative for alpha-fetoprotein (AFP), the diagnosis of AFP-negative HCC is essential to improve the detection rate of HCC.

AIM

To establish an effective model for diagnosing AFP-negative HCC based on serum tumour biomarkers.

METHODS

A total of 180 HCC patients were enrolled in this study. The expression levels of GP73, des-γ-carboxyprothrombin (DCP), CK18-M65, and CK18-M30 were detected by a fully automated chemiluminescence analyser. The variables were selected by logistic regression analysis. Several models were constructed using stepwise backward logistic regression. The performance of the models was compared using the C statistic, integrated discrimination improvement, net reclassification improvement, and calibration curves. The clinical utility of the nomogram was assessed using decision curve analysis (DCA).

RESULTS

The results showed that the expression levels of GP73, DCP, CK18-M65, and CK18-M30 were significantly greater in AFP-negative HCC patients than in healthy controls (P < 0.001). Multivariate logistic regression analysis revealed that GP73, DCP, and CK18-M65 were independent factors for diagnosing AFP-negative HCC. By comparing the diagnostic performance of multiple models, we included GP73 and CK18-M65 as the model variables, and the model had good discrimination ability (area under the curve = 0.946) and good goodness of fit. The DCA curves indicated the good clinical utility of the nomogram.

CONCLUSION

Our study identified GP73 and CK18-M65 as serum biomarkers with certain application value in the diagnosis of AFP-negative HCC. The diagnostic nomogram based on CK18-M65 combined with GP73 demonstrated good performance and effectively identified high-risk groups of patients with HCC.

Tumor budding is a meaningful prognostic marker in patients with hepatocellular carcinoma after curative hepatectomy

Aim

Tumor budding (TB) has excellent prognostic value in many solid tumors, but there is little research on it in hepatocellular carcinoma (HCC). This study assessed the prognostic value of TB in patients with HCC who received hepatectomy.

Methods

This retrospective study included 210 patients with HCC who received curative hepatectomy at the First Affiliated Hospital of Xi'an Jiaotong University, between 2016 and 2018. TB was evaluated on hematoxylin‐ and eosin‐stained slides according to the criteria established by the 2016 International Tumor Budding Consensus Conference. t‐tests, Chi‐squared tests, and rank‐sum tests were used to correlate the extent of TB with clinicopathological parameters. Prognostic analysis was performed using Cox regression models and the Kaplan–Meier method.

Results

The positive detection rate of TB was 45.2% (95/210) in 210 patients with HCC. Patients positive for TB always exhibit lower tumor differentiation, higher hepatitis B virus DNA levels, and more severe liver fibrosis. Multivariate Cox analysis identified TB (hazard ratio [HR]: 2.232, 95% confidence interval [CI]: 1.479–3.368, p < 0.001) as an independent prognostic factor for patients' recurrence‐free survival (RFS), similar to tumor size (HR: 1.070, 95% CI: 1.070–1.142, p = 0.042) and satellite nodule (HR: 2.266, 95% CI: 1.298–3.956, p = 0.004). Kaplan–Meier analysis also demonstrated that TB‐positive patients had a significantly worse RFS. Interestingly, subgroup analysis revealed that among HCC patients with negative microvascular invasion (MVI), TB was also strongly associated with RFS (HR: 3.206, 95% CI: 1.667–6.168, p < 0.001). These findings suggest that TB may serve as a supplemental prognostic biomarker for HCC‐negative MVI.

Conclusions

TB is an adverse prognostic biomarker for HCC, particularly in patients negative for MVI. TB evaluation should be considered in the postoperative pathological examination of HCC in clinical practice.

Preoperative Three-Dimensional Morphological Tumor Features Predict Microvascular Invasion in Hepatocellular Carcinoma

RATIONALE AND OBJECTIVES

The study was designed to evaluate microvascular invasion (MVI) using three-dimensional (3D) morphological indicators prior to surgery.

MATERIALS AND METHODS

This retrospective study included 156 patients with hepatocellular carcinoma (HCC) at our hospital from 2017 to 2018. Through thin-layer CT scanning and 3D reconstruction, the tumor surface inclination angles can be quantitatively analyzed to determine the surface irregularity rate (SIR), which serves as a comprehensive assessment method for tumor irregularity based on preoperative 3D morphological evaluation. Univariate and multivariate logistic regression analyses were employed to investigate the correlation with MVI.

RESULTS

The SIR was related to MVI (OR: 10.667, P < 0.001). Multivariate logistic regression analysis showed that the SIR was an independent risk factor for MVI. The area under the receiver operating characteristic curve (ROC) of prediction model composed of the morphological indicator SIR was 0.831 (95% confidence interval: 0.759-0.895).

CONCLUSION

The preoperative 3D morphological indicator SIR of a tumor is an accurate predictor of MVI, providing a valuable tool in clinical decision-making.

Role of protein induced by vitamin-K absence-II in transplanted patients with HCC not producing alpha-fetoprotein

Elevated Protein Induced by Vitamin-K Absence-II (PIVKA-II) has been shown to be an adverse prognostic factor in HCC patients undergoing liver transplantation (LT). No definitive data are available about the impact of PIVKA-II concerning post-LT recurrence in patients not secreting (≤ 20 ng/mL) alpha-fetoprotein (AFP). An observational retrospective study of the East-West HCC-LT consortium is reported. Between 2000 and 2019, 639 HCC patients were enrolled in 5 collaborative European and Japanese centers. To minimize the initial selection bias, an inverse probability therapy weighting method was adopted to analyze the data. In the post-inverse probability therapy weighting population, PIVKA-II (HR = 2.00; 95% CI: 1.52-2.64; p < 0.001) and AFP (HR=1.82; 95% CI: 1.48-2.24; p < 0.001) were the most relevant independent risk factors for post-LT recurrence. A sub-analysis focusing only on patients who are AFP non-secreting confirmed the negative role of PIVKA-II (HR=2.06, 95% CI: 1.26-3.35; p =0.004). When categorizing the entire population into 4 groups according to the AFP levels (≤ or > 20 ng/mL) and PIVKA (≤ or > 300 mUA/mL) at the time of LT, the lowest recurrence rates were observed in the low AFP-PIVKA-II group (5-year recurrence rate = 8.0%). Conversely, the high AFP-PIVKA-II group had the worst outcome (5-year recurrence rate = 35.1%). PIVKA-II secretion is a relevant risk factor for post-LT HCC recurrence. The role of this marker is independent of the AFP status. Combining both tumor markers, especially in the setting of LT, should be of great relevance for adding information about predicting the post-LT risk of tumor recurrence and selecting these patients for transplantation.

Association of Serum Levels and Immunohistochemical Labelling of Des-Gamma-Carboxy-Prothrombin in Patients Undergoing Liver Transplantation for Hepatocellular Carcinoma

Hepatocellular cancer (HCC) is one of the main reasons for liver transplantation (LT). Biomarkers, such as alpha-foetoprotein (AFP) and Des-gamma-carboxy-prothrombin (DCP), can be helpful in defining the recurrence risk post LT. This study aims to evaluate the association between the intensity of DCP immunohistochemical labelling and serum DCP levels in patients undergoing LT for HCC. We carried out a prospective monocentric study including patients who all underwent LT for cirrhosis between 2016 and 2018 and all fell under the Milan criteria. The accepted diagnostic criteria for HCC were contrast-enhanced imaging and histology. Thirty-nine patients were followed for a median of 21 months, with HCC lesions categorized into negative, focally positive, and diffusely positive groups based on DCP immunohistochemistry. The serum DCP levels were significantly higher in the positive groups (258 mAU/mL for the focally and 257 mAU/mL for the diffusely positive) than in the negative group (48 mAU/mL) (p = 0.005) at diagnosis and at the time of liver transplantation (220 mAU/mL for the diffuse positive group). Microvascular invasion (58.8% vs. 19.0% for the diffusely positive and negative groups, respectively, p < 0.001) and lesion size (20 mm in the diffusely labelled group versus 12 mm in the other groups, p = 0.002) were significantly correlated with DCP labelling. Late recurrence occurred only in the positive groups; in the negative group, it occurred within the first 3 months after transplantation. DCP labelling in liver lesions correlates with serum levels and a more aggressive tumour profile. Further investigation is needed to determine if highly DCP-labelled tumours allow for the better selection of high-risk patients before LT.

Des-gamma-carboxy prothrombin and alpha-fetoprotein levels as biomarkers for hepatocellular carcinoma and their correlation with radiological characteristics

BACKGROUND

Alpha-fetoprotein (AFP), a commonly used biomarker for hepatocellular carcinoma (HCC), is normal in up to one-third of patients.

AIM

To evaluate the diagnostic performance of des-gamma-carboxy-prothrombin (DCP) alone and in combination with AFP.

METHODS

In this study, 202 patients with radiologically proven HCC were enrolled, and their DCP and AFP levels were evaluated for their diagnostic performance.

RESULTS

The mean age of the enrolled patients was 58.5 years; 72.0% were male. DCP was elevated in 86.6% (n = 175) of all patients, 100.0% (n = 74) of patients with portal vein thrombus, and 87.4% (n = 111) of patients with multicentric HCC. AFP was elevated in 64.3% (n = 130) of all the patients, 74% (n = 55) of the patients with portal vein thrombus, and 71.6% (n = 91) of the patients with multicentric HCC (P = 0.030, 0.001, and 0.015, respectively). In tumors less than 2 cm in size (n = 46), DCP was increased in 32 (69.5%) patients, and AFP was increased in 25 (54.3%) patients (P = 0.801). There was good pairing between DCP and AFP for HCCs of 2 cm size or larger (P < 0.001); however, the pairing among tumors < 2 cm size was not significant (P = 0.210). In 69 of the patients (34.1%), only one of the tumor markers was positive; DCP was elevated alone in 57/202 (28.2%) of all patients, and AFP alone was elevated in 12/202 (5.9%) of the patients. The areas under receiver operating characteristic curves (AUROC) for tumors > 2 cm was 0.74 for DCP and 0.59 for AFP; combining both markers resulted in an AUROC of 0.73. For tumors < 2 cm, the AUROC was 0.25 for DCP and 0.40 for AFP.

CONCLUSION

DCP, as an individual marker, had a better diagnostic performance in many cases of HCC. Hence, DCP may replace AFP as the primary HCC biomarker.

Diagnostic performance of PIVKA-II in identifying recurrent hepatocellular carcinoma following curative resection: a retrospective cohort study

Protein induced by vitamin K absence or antagonist II (PIVKA-II) plays a critical role in the diagnosis of hepatocellular carcinoma (HCC), however, studies on its efficacy in diagnosing recurrent HCC were rarely found. A multicenter, retrospective, and observational study was conducted. During the overall follow-up of 5 years, HCC patients who had curative resection were monitored every 3 months in the first year post-surgery and every 6 months thereafter if no recurrence occurred. Tumor markers were collected at the diagnosis of recurrence for those with recurrence and at the last follow-up for those without recurrence. The median serum levels of PIVKA-II and AFP in the recurrence group were significantly higher than those in the non-recurrence group (PIVKA-II: 84.62 vs. 18.76 mAU/ml, p < 0.001; AFP: 4.90 vs. 3.00 ng/ml, p < 0.001) and there is a significant correlation between PIVKA-II and AFP (R = 0.901, p < 0.001). PIVKA-II showed better accuracy than AFP in the diagnosis of overall recurrent HCC (AUC: 0.883 vs. 0.672; p < 0.0001), but also in patients with negative PIVKA-II before curative resection (AUC: 0.878 vs. 0.680, p = 0.001). Clinician should pay more attention to serum PIVKA-II values when following patients after curative HCC resection to detect early recurrence.Clinical trial registration: ChiCTR2300070874.

Merits and boundaries of the BCLC staging and treatment algorithm: Learning from the past to improve the future with a novel proposal

In this Expert Opinion, we thoroughly analyse the Barcelona Clinic Liver Cancer (BCLC) staging and treatment algorithm for hepatocellular carcinoma (HCC) that, since 1999, has standardised HCC management, offering a structured approach for the prognostic evaluation and treatment of patients with HCC. The first part of the article presents the strengths and evolutionary improvements of the BCLC staging system. Nevertheless, both patient characteristics and available treatments have changed in the last two decades, limiting the role of the BCLC criteria for treatment allocation in a growing number of patients. As therapeutic options expand and become more effective, the stage-linked treatment decision-making algorithm may lead to undertreatment and suboptimal outcomes for patients with disease beyond early-stage HCC. Consequently, strict adherence to BCLC criteria is limited in expert centres, particularly for patients diagnosed beyond early-stage HCC. Although the BCLC system remains the benchmark against which other therapeutic frameworks must be judged, the era of precision medicine calls for patient-tailored therapeutic decision-making (by a multidisciplinary tumour board) rather than stage-dictated treatment allocation. Acknowledging this conceptual difference in clinical management, the second part of the article describes a novel "multiparametric therapeutic hierarchy", which integrates a comprehensive assessment of clinical factors, biomarkers, technical feasibility, and resource availability. Lastly, considering the increasing efficacy of locoregional and systemic treatments, the concept of "converse therapeutic hierarchy" is introduced. These treatments can increase the feasibility (conversion approach) and effectiveness (adjuvant approach of systemic therapy) of potentially curative approaches to greatly improve clinical outcomes.

Hepatoprotective Effect Assessment of C-Phycocyanin on Hepatocellular Carcinoma Rat Model by Using Photoacoustic Spectroscopy

Hepatocellular carcinoma (HCC) is the most common primary neoplasia of the liver with elevated mortality. Experimental treatment with antioxidants has a beneficial effect on the experimental models of HCC. Arthrospira maxima (spirulina) and its phycocyanin have antitumoral action on different tumoral cells. However, it is unknown whether phycocyanin is the responsible molecule for the antitumoral effect on HCC. Photoacoustic spectroscopy (PAS) stands out among other spectroscopy techniques for its versatility of samples analyzed. This technique makes it possible to obtain the optical absorption spectrum of solid or liquid, dark or transparent samples. Previous studies report that assessing liver damage in rats produced by the modified resistant hepatocyte model (MRHM) is possible by analyzing their blood optical absorption spectrum. This study aimed to investigate, by PAS, the effect of phycocyanin obtained from spirulina on hepatic dysfunction. The optical absorption spectra analysis of the rat blood indicates the damage level induced by the MRHM group, being in concordance with the carried out biological conventional studies results, indicating an increase in the activity of hepatic enzymes, oxidative stress, Bax/Bcl2 ratio, cdk2, and AKT2 expression results, with a reduction in p53 expression. Also, PAS results suggest that phycocyanin decreases induced damage, due to the prevention of the Bax, AKT2, and p53 altered expression and the tumor progression in a HCC rat model.

PIVKA-II combined with tumor burden score to predict long-term outcomes of AFP-negative hepatocellular carcinoma patients after liver resection

BACKGROUND

This study aimed to establish a simple prognostic scoring model based on tumor burden score (TBS) and PIVKA-II to predict long-term outcomes of α-fetoprotein (AFP)-negative hepatocellular carcinoma (HCC) patients.

METHODS

511 patients were divided into the training cohort (n = 305) and the validation cohort (n = 206) at a ratio of 6:4. Receiver operating characteristic curves (ROC) were established to identify cutoff values of TBS and PIVKA-II. Kaplan-Meier curves were used to analyze survival outcomes. The multivariable Cox regression was used to identify variables independently associated with survival outcomes. The predictive performance of the TBS-PIVKA II score (TPS) model was compared with Barcelona clinic liver cancer (BCLC) stage and American Joint Committee on Cancer (AJCC TNM) stage.

RESULTS

The present study established the TPS model using a simple scoring system (0, 1 for low/high TBS [cutoff value: 4.1]; 0, 1 for low/high PIVKA-II [cutoff value: 239 mAU/mL]). The TPS scoring model was divided into three levels according to the summation of TBS score and PIVKA-II score: TPS 0, TPS 1, and TPS 2. The TPS scoring model was able to stratify OS (training: p < 0.001, validation: p < 0.001) and early recurrence (training: p < 0.001; validation: p = 0.001) in the training cohort and the validation cohort. The TPS score was independently associated with OS (TPS 1 vs. 0, HR: 2.28, 95% CI: 1.01-5.17; TPS 2 vs. 0, HR: 4.21, 95% CI: 2.01-8.84) and early recurrence (TPS 1 vs. 0, HR: 3.50, 95% CI: 1.71-7.16; TPS 2 vs. 0, HR: 3.79, 95% CI: 1.86-7.75) in the training cohort. The TPS scoring model outperformed BCLC stage and AJCC TNM stage in predicting OS and early recurrence in the training cohort and the validation cohort. But the TPS scoring model was unable to stratify the late recurrence in the training cohort (p = 0.872) and the validation cohort (p = 0.458).

CONCLUSIONS

The TPS model outperformed the BCLC stage and AJCC TNM stage in predicting OS and early recurrence of AFP-negative HCC patients after liver resection, which might better assist surgeons in screening AFP-negative HCC patients who may benefit from liver resection.

Preoperative assessment of microvascular invasion risk using gadoxetate-enhanced MRI for predicting outcomes after liver transplantation for single hepatocellular carcinoma within the Milan criteria

OBJECTIVE

To compare therapeutic outcomes after liver transplantation (LT) between hepatocellular carcinomas (HCC) with low and high risk for microvascular invasion (MVI) within the Milan criteria evaluated preoperatively.

METHODS

Eighty patients with a single HCC who underwent LT as the initial therapy between 2008 and 2017 were included from two tertiary referral medical centers in a HBV-predominant population. A preoperative MVI-risk model was used to identify low- and high-risk patients. Recurrence-free survival (RFS) after LT between the two risk groups was compared using Kaplan-Meier curves with the log-rank test. Prognostic factors for RFS were identified using a multivariable Cox hazard regression analysis.

RESULTS

Eighty patients were included (mean age, 51.8 years +/- 7.5 [standard deviation], 65 men). Patients were divided into low-risk (n = 64) and high-risk (n = 16) groups for MVI. The RFS rates after LT were significantly lower in the MVI high-risk group compared to the low-risk group at 1 year (75.0% [95% CI: 56.5-99.5%] vs. 96.9% [92.7-100%], p = 0.048), 3 years (62.5% [42.8-91.4%] vs. 95.3% [90.3-100%], p = 0.008), and 5 years (62.5% [42.8-91.4%] vs. and 95.3% [90.3-100%], p = 0.008). In addition, multivariable analysis showed that MVI high risk was the only significant factor for poor RFS (p = 0.016).

CONCLUSION

HCC patients with a high risk of MVI showed significantly lower RFS after LT than those without. This model could aid in selecting optimal candidates in addition to the Milan criteria when considering upfront LT for patients with HCC if alternative treatment options are available.

CLINICAL RELEVANCE STATEMENT

High risk for microvascular invasion (MVI) in hepatocellular carcinoma patients lowered recurrence-free survival after liver transplantation, despite meeting the Milan criteria. Identifying MVI risk could aid candidate selection for upfront liver transplantation, particularly if alternative treatments are available.

KEY POINTS

• A predictive model-derived microvascular invasion (MVI) high- and low-risk groups had a significant difference in the incidence of MVI on pathology. • Recurrence-free survival after liver transplantation (LT) for single hepatocellular carcinoma (HCC) within the Milan criteria was significantly different between the MVI high- and low-risk groups. • The peak incidence of tumor recurrence was 20 months after liver transplantation, probably indicating that HCC with high risk for MVI had a high risk of early (≤ 2 years) tumor recurrence.

Incorporation of protein induced by vitamin K absence or antagonist-II into transplant criteria expands beneficiaries of liver transplantation for hepatocellular carcinoma: a multicenter retrospective cohort study in China

INTRODUCTION

In order to maximize the utilization of precious donor liver, precisely determining potential hepatocellular carcinoma (HCC) candidates who will benefit from liver transplantation (LT) is essential. As a crucial diagnostic biomarker for HCC, protein induced by vitamin K absence or antagonist-II (PIVKA-II) has become one of the key indicators for assessing tumor recurrence risk after LT. This study aims to investigate the role of PIVKA-II in recipient selection and prognostic stratification.

METHODS

The clinicopathologic data of HCC patients undergoing LT from 2015 to 2020 in six Chinese transplant centers were collected. Univariate and multivariate analyses were performed to determine risk factors for disease free survival (DFS). Based on these risk factors, survival analysis was made by Kaplan-Meier method and their value in prognostic stratification was assessed.

RESULTS

A total of 522 eligible HCC patients with pre-LT PIVKA-II records were finally included in this study. Tumor burden>8 cm, α-fetoprotein>400 ng/ml, histopathologic grade III and PIVKA-II>240 mAU/ml were identified as independent risk factors for DFS. DFS of patients with PIVKA-II≤240 mAU/ml ( N =288) were significantly higher than those with PIVKA-II>240 mAU/ml ( N =234) (1-year, 3-year, and 5-year DFS: 83.2, 77.3, and 75.9% vs. 75.1, 58.5, and 50.5%; P <0.001). Compared with Hangzhou criteria ( N =305), incorporating PIVKA-II into Hangzhou criteria (including tumor burden, α-fetoprotein, and histopathologic grade) increased the number of patients with eligibility for LT by 21.6% but achieved comparable DFS and overall survival.

CONCLUSIONS

Incorporating PIVKA-II into existing LT criteria could increase the number of eligible HCC patients without compromising post-LT outcomes.

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.

Chinese expert consensus statement on the clinical application of AFP/AFP-L3%/DCP using GALAD and GALAD-like algorithm in HCC

BACKGROUND

Primary hepatocellular carcinoma (HCC) is one of the most prevalent world-wide malignancies. Half of the newly developed HCC occurs in China. Optimizing the strategies for high-risk surveillance and early diagnosis are pivotal for improving 5-year survival. Constructing the scientific non-invasive detection technologies feasible for medical and healthcare institutions is among the key routes for elevating the efficacies of HCC identification and follow-up.

RESULTS

Based on the Chinese and international guidelines, expert consensus statements, literatures and evidence-based clinical practice experiences, this consensus statement puts forward the clinical implications, application subjects, detection techniques and results interpretations of the triple-biomarker (AFP, AFP-L3%, DCP) based GALAD, GALAD like models for liver cancer.

CONCLUSIONS

The compile of this consensus statement aims to address and push the reasonable application of the triple-biomarker (AFP, AFP-L3%, DCP) detections thus to maximize the clinical benefits and help improving the high risk surveillance, early diagnosis and prognosis of HCC.

Hepatocellular carcinoma recurrence: Predictors and management

Hepatocellular carcinoma (HCC), the sixth most common cancer globally, is associated with high mortality rates and more than 830,000 annual deaths. Despite advances in the available management options including surgical resection and local ablative therapies, recurrence rates after the initial treatment exceed 50%, even among patients who have undergone curative-intent therapy. Moreover, postsurgical HCC recurrence occurs in about 70% of cases five years postoperatively. The management of recurrent HCC remains undefined. This review discusses different predictors for HCC recurrence after each treatment modality and different approaches available to stratify these patients. More specific guidelines for managing HCC recurrence and strict surveillance protocols for such recurrence after initial HCC management are needed.

Protein induced by vitamin K absence or antagonist II: Experience to date and future directions

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with high mortality. The realization of precision medicine in HCC relies upon efficient biomarkers. Protein induced by vitamin K absence or antagonist II (PIVKA-II) is an immature prothrombin with insufficient coagulation activity, overexpressing in HCC cells. Previous evidence confirmed the role of PIVKA-II in screening and diagnosing HCC. However, the increased PIVKA-II was observed not only in HCC, but also in non-HCC individuals such as vitamin K deficiency. The joint detection of PIVKA-II and other biomarkers could significantly improve diagnostic accuracy in HCC. Furthermore, PIVKA-II serves as a valuable prognostic predictor, transplantation eligibility, resectability, tumor recurrence, therapeutic efficacy, and malignant tumor behaviors. Additionally, PIVKA-II represents a potential target for agent development to establish new therapeutic strategies. Besides HCC, PIVKA-II also serves as a biomarker of vitamin K status. In this review, we assess the role of PIVKA-II in diagnosis, prediction, and treatment. Over the past decades, substantial progress has been achieved in the application of PIVKA-II. Exploration and innovation are required for further advances in the field of PIVKA-II investigation.

Dynamic changes in three biomarkers predict early-stage hepatocellular carcinoma in patients with chronic hepatitis B receiving antiviral therapy

PURPOSE

Patients with chronic hepatitis B (CHB) remain at risk for hepatocellular carcinoma during antiviral therapy. We aimed to clarify the values of alpha-fetoprotein (AFP), lectin-reactive fraction of AFP (AFP-L3), and des-γ-carboxyprothrombin (DCP) for early warning of HCC.

METHODS

A total of 1348 CHB patients received antiviral therapy and follow-up every 26 weeks. Eighty-four patients with HCC were age-, sex-, and cirrhosis-matched with 168 controls. AFP, AFP-L3, and DCP were compared between the groups from 104 weeks before HCC diagnosis (- 104 w) to the time of diagnosis (0 w).

RESULTS

Of the 84 HCC patients, 60 (71.4%) had early-stage HCC, AFP increased from - 26 w, and AFP-L3 and DCP increased from - 78 w. However, levels were unchanged in controls. ΔAFP, ΔAFP-L3, and ΔDCP showed similar abilities for predicting HCC (P > 0.05). Receiver operating characteristic curve analysis showed that AFP had better diagnostic performance for HCC than AFP-L3, DCP, or their combination. The cut-off values of AFP, AFP-L3, and DCP were 5.3 ng/mL, 1.05%, and 31.5 mAU/mL, respectively. Notably, lower AFP values were required to diagnose HCC in patients with detectable HBV DNA (4.1 ng/mL) or elevated alanine aminotransferase (5.2 ng/mL).

CONCLUSIONS

Changes in AFP, AFP-L3, and DCP can help to predict HCC in CHB patients receiving antiviral therapy. A lower AFP value is needed to diagnose HCC, especially in patients with detectable HBV DNA or elevated alanine aminotransferase.

Roles and Molecular Mechanisms of Biomarkers in Hepatocellular Carcinoma with Microvascular Invasion: A Review

Hepatocellular carcinoma (HCC) being a leading cause of cancer-related death, has high associated mortality and recurrence rates. It has been of great necessity and urgency to find effective HCC diagnosis and treatment measures. Studies have shown that microvascular invasion (MVI) is an independent risk factor for poor prognosis after hepatectomy. The abnormal expression of biomacromolecules such as circ-RNAs, lncRNAs, STIP1, and PD-L1 in HCC patients is strongly correlated with MVI. Deregulation of several markers mentioned in this review affects the proliferation, invasion, metastasis, EMT, and anti-apoptotic processes of HCC cells through multiple complex mechanisms. Therefore, these biomarkers may have an important clinical role and serve as promising interventional targets for HCC. In this review, we provide a comprehensive overview on the functions and regulatory mechanisms of MVI-related biomarkers in HCC.

Preoperative prediction and risk assessment of microvascular invasion in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and highly lethal tumors worldwide. Microvascular invasion (MVI) is a significant risk factor for recurrence and poor prognosis after surgical resection for HCC patients. Accurately predicting the status of MVI preoperatively is critical for clinicians to select treatment modalities and improve overall survival. However, MVI can only be diagnosed by pathological analysis of postoperative specimens. Currently, numerous indicators in serology (including liquid biopsies) and imaging have been identified to effective in predicting the occurrence of MVI, and the multi-indicator model based on deep learning greatly improves accuracy of prediction. Moreover, several genes and proteins have been identified as risk factors that are strictly associated with the occurrence of MVI. Therefore, this review evaluates various predictors and risk factors, and provides guidance for subsequent efforts to explore more accurate predictive methods and to facilitate the conversion of risk factors into reliable predictors.

Development and validation of a diagnostic model for AFP-negative hepatocellular carcinoma

PURPOSE

AFP appears to be negative in about 30% of overall hepatocellular carcinoma (HCC). Our study aimed to develop a nomogram model to diagnose AFP-negative HCC (AFPN-HCC).

PATIENTS AND METHODS

The training set included 294 AFPN-HCC patients, 159 healthy objects, 63 patients with chronic hepatitis B(CHB), and 64 patients with liver cirrhosis (LC). And the validation set enrolled 137 healthy controls objects, 47 CHB patients and 45 patients with LC. LASSO, univariate, and multivariable logistic regression analysis were performed to construct the model and then transformed into a visualized nomogram. The receiver operating characteristic (ROC) curves, the calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were further used for validation.

RESULTS

Four variables including age, PIVKA-II, platelet (PLT) counts, and prothrombin time (PT) were selected to establish the nomogram. The area under the curve (AUC) of the ROC to distinguish AFPN-HCC patients was 0.937(95% CI 0.892-0.938) in training set and 0.942(95% CI 0.921-0.963) in validation set. We also found that the model had high diagnostic value for small-size HCC (tumor size < 5 cm) (AUC = 0.886) and HBV surface antigen-positive AFPN-HCC (AUC = 0.883).

CONCLUSIONS

Our model was effective for discrimination of AFPN-HCC from patients with benign liver diseases and healthy controls, and might be helpful for the diagnosis for AFPN-HCC.

AFP-L3 and DCP are superior to AFP in predicting waitlist dropout in HCC patients: Results of a prospective study

In patients with HCC awaiting liver transplantation (LT), there is a need to identify biomarkers that are superior to AFP in predicting prognosis. AFP-L3 and des-gamma-carboxyprothrombin (DCP) play a role in HCC detection, but their ability to predict waitlist dropout is unknown. In this prospective single-center study commenced in July 2017, 267 HCC patients had all 3 biomarkers obtained at LT listing. Among them, 96.2% received local-regional therapy, and 18.8% had an initial tumor stage beyond Milan criteria requiring tumor downstaging. At listing, median AFP was 7.0 ng/mL (IQR 3.4-21.5), median AFP-L3 was 7.1% (IQR 0.5-12.5), and median DCP was 1.0 ng/mL (IQR 0.2-3.8). After a median follow-up of 19.3 months, 63 (23.6%) experienced waitlist dropout, while 145 (54.3%) received LT, and 59 (22.1%) were still awaiting LT. Using Cox proportional hazards analysis, AFP-L3≥35% and DCP≥7.5 ng/mL were associated with increased waitlist dropout, whereas AFP at all tested cutoffs, including ≥20,≥ 100, and≥250 ng/mL was not. In a multivariable model, AFP-L3≥35% (HR 2.25, p =0.04) and DCP≥7.5 ng/mL (HR 2.20, p =0.02) remained associated with waitlist dropout as did time from HCC diagnosis to listing ≥ 1 year and increasing MELD-Na score. Kaplan-Meier probability of waitlist dropout within 2 years was 21.8% in those with AFP-L3<35% and DCP<7.5 ng/mL, 59.9% with either AFP-L3 or DCP elevated, and 100% for those with both elevated ( p <0.001). In this prospective study, listing AFP-L3% and DCP were superior to AFP in predicting waitlist dropout with the combination of AFP-L3≥35% and DCP≥7.5 ng/mL associated with a 100% risk of waitlist dropout, thus clearly adding prognostic value to AFP alone.

Predictive value of radiomics analysis of enhanced CT for three-tiered microvascular invasion grading in hepatocellular carcinoma

BACKGROUND

Microvascular invasion (MVI) is a major risk factor, for recurrence and metastasis of hepatocellular carcinoma (HCC) after radical surgery and liver transplantation. However, its diagnosis depends on the pathological examination of the resected specimen after surgery; therefore, predicting MVI before surgery is necessary to provide reference value for clinical treatment. Meanwhile, predicting only the existence of MVI is not enough, as it ignores the degree, quantity, and distribution of MVI and may lead to MVI-positive patients suffering due to inappropriate treatment. Although some studies have involved M2 (high risk of MVI), majority have adopted the binary classification method or have not included radiomics.

PURPOSE

To develop three-class classification models for predicting the grade of MVI of HCC by combining enhanced computed tomography radiomics features with clinical risk factors.

METHODS

The data of 166 patients with HCC confirmed by surgery and pathology were analyzed retrospectively. The patients were divided into the training (116 cases) and test (50 cases) groups at a ratio of 7:3. Of them, 69 cases were MVI positive in the training group, including 45 cases in the low-risk group (M1) and 24 cases in the high-risk group (M2), and 47 cases were MVI negative (M0). In the training group, the optimal subset features were obtained through feature selection, and the arterial phase radiomics model, portal venous phase radiomics model, delayed phase radiomics model, three-phase radiomics model, clinical imaging model, and combined model were developed using Linear Support Vector Classification. The test group was used for validation, and the efficacy of each model was evaluated through the receiver operating characteristic curve (ROC).

RESULTS

The clinical imaging features of MVI included alpha-fetoprotein, tumor size, tumor margin, peritumoral enhancement, intratumoral artery, and low-density halo. The area under the curve (AUC) of the ROC values of the clinical imaging model for M0, M1, and M2 were 0.831, 0.701, and 0.847, respectively, in the training group and 0.782, 0.534, and 0.785, respectively, in the test group. After combined radiomics analyis, the AUC values for M0, M1, and M2 in the test group were 0.818, 0.688, and 0.867, respectively. The difference between the clinical imaging model and the combined model was statistically significant (p = 0.029).

CONCLUSION

The clinical imaging model and radiomics model developed in this study had a specific predictive value for HCC MVI grading, which can provide precise reference value for preoperative clinical diagnosis and treatment. The combined application of the two models had a high predictive efficacy.