Practice guidelines for the pathological diagnosis of primary liver cancer: 2015 update

Construction of a nomogram combining CEUS and MRI imaging for preoperative diagnosis of microvascular invasion in hepatocellular carcinoma

Purpose

To use Sonazoid contrast-enhanced ultrasound (S-CEUS) and Gadolinium-Ethoxybenzyl-Diethylenetriamine Penta-Acetic Acid magnetic-resonance imaging (EOB-MRI), exploring a non-invasive preoperative diagnostic strategy for microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

Methods

111 newly developed HCC cases were retrospectively collected. Both S-CEUS and EOB-MRI examinations were performed within one month of hepatectomy. The following indicators were investigated: size; vascularity in three phases of S-CEUS; margin, signal intensity, and peritumoral wedge shape in EOB-MRI; tumoral homogeneity, presence and integrity of the tumoral capsule in S-CEUS or EOB-MRI; presence of branching enhancement in S-CEUS; baseline clinical and serological data. The least absolute shrinkage and selection operator regression and multivariate logistic regression analysis were applied to optimize feature selection for the model. A nomogram for MVI was developed and verified by bootstrap resampling.

Results

Of the 16 variables we included, wedge and margin in HBP of EOB-MRI, capsule integrity in AP or HBP/PVP images of EOB-MRI/S-CEUS, and branching enhancement in AP of S-CEUS were identified as independent risk factors for MVI and incorporated into construction of the nomogram. The nomogram achieved an excellent diagnostic efficiency with an area under the curve of 0.8434 for full data training set and 0.7925 for bootstrapping validation set for 500 repetitions. In evaluating the nomogram, Hosmer-Lemeshow test for training set exhibited a good model fit with P > 0.05. Decision curve analysis of nomogram model yielded excellent clinical net benefit with a wide range (5-80 % and 85-94 %) of risk threshold.

Conclusions

The MVI Nomogram established in this study may provide a strategy for optimizing the preoperative diagnosis of MVI, which in turn may improve the treatment and prognosis of MVI-related HCC.

Optimizing predictions: improved performance of preoperative gadobenate-enhanced MRI hepatobiliary phase features in predicting vessels encapsulating tumor clusters in hepatocellular carcinoma-a multicenter study

BACKGROUND

Vessels Encapsulating Tumor Clusters (VETC) are now recognized as independent indicators of recurrence and overall survival in hepatocellular carcinoma (HCC) patients. However, there has been limited investigation into predicting the VETC pattern using hepatobiliary phase (HBP) features from preoperative gadobenate-enhanced MRI.

METHODS

This study involved 252 HCC patients with confirmed VETC status from three different hospitals (Hospital 1: training set with 142 patients; Hospital 2: test set with 64 patients; Hospital 3: validation set with 46 patients). Independent predictive factors for VETC status were determined through univariate and multivariate logistic analyses. Subsequently, these factors were used to construct two distinct VETC prediction models. Model 1 included all independent predictive factors, while Model 2 excluded HBP features. The performance of both models was assessed using the Area Under the Curve (AUC), Decision Curve Analysis, and Calibration Curve. Prediction accuracy between the two models was compared using Net Reclassification Improvement (NRI) and Integrated Discriminant Improvement (IDI).

RESULTS

CA199, IBIL, shape, peritumoral hyperintensity on HBP, and arterial peritumoral enhancement were independent predictors of VETC. Model 1 showed robust predictive performance, with AUCs of 0.836 (training), 0.811 (test), and 0.802 (validation). Model 2 exhibited moderate performance, with AUCs of 0.813, 0.773, and 0.783 in the respective sets. Calibration and decision curves for both models indicated consistent predictions between predicted and actual VETC, benefiting HCC patients. NRI showed Model 1 increased by 0.326, 0.389, and 0.478 in the training, test, and validation sets compared to Model 2. IDI indicated Model 1 increased by 0.036, 0.028, and 0.025 in the training, test, and validation sets compared to Model 2.

CONCLUSION

HBP features from preoperative gadobenate-enhanced MRI can enhance the predictive performance of VETC in HCC.

Comprehensive analysis of CXCL10 and MIP-3a reveals their potential clinical application in hepatocellular carcinoma

Chemokines play a crucial role in the pathogenesis of patients with hepatocellular carcinoma (HCC). The expression levels of interferon-γ-induced protein-10 (CXCL10) and macrophage inflammatory protein-3α (MIP-3a) were investigated to clarify their clinical significance in HCC. The protein levels of CXCL10 and MIP-3a in the serum of 105 HBV-associated HCC patients, 50 patients with liver cirrhosis (LC), 50 patients with chronic hepatitis B (CHB) and 50 healthy donors (HC) were detected by liquid chip technology (Luminex) or ELISA. In addition, their mRNA levels were also determined in liver cancer and adjacent cancer tissue (paracancer; ParaCa) from 65 HCC patients. The online database UALCAN was used to analyze the association between CXCL10 and pathological manifestations of liver cancer. In addition, the diagnostic value of CXCL10/MIP-3a and AFP in HCC patients was determined by analyzing the Receiver Operating Characteristic Curve (ROC). The protein concentrations of CXCL10 and MIP-3a were significantly higher in the HCC group than in the LC, CHB and HC groups. CXCL10 in sera and liver cancer tissues is significantly positively correlated with ALT, but no significance between CXCL10 in ParaCa tissues and sera-ALT. Their mRNA is significantly higher in cancer tissues than in ParaCa tissues. The areas under the ROC curve of CXCL10, MIP-3a, CXCL10 and MIP-3a combined and AFP were 0.9169, 0.9261, 0.9299 and 0.7880, respectively. Elevated chemokines CXCL10 and MIP-3a in HCC patients may be associated with the clinical manifestation of HCC and could be a potential molecular marker for prognostic evaluation or a therapeutic target for HCC.

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.

Comparison of Sonazoid-Contrast‑Enhanced Ultrasound and Gd‑EOB‑DTPA‑Enhanced MRI for Predicting Microvascular Invasion in Hepatocellular Carcinoma

OBJECTIVE

This study aims to evaluate and compare the predictive accuracy of Sonazoid-contrast-enhanced ultrasound (CEUS) and Gd-EOB-DTPA-enhanced MRI for detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

In this single-center prospective study, we included 64 patients with histopathologically confirmed single HCC lesions. Based on post-operative pathologic data, patients were categorized into two groups: those with MVI (n = 21) and those without MVI (n = 43). The diagnostic efficacy of CEUS was compared with that of MRI in predicting MVI.

RESULTS

Multifactorial analysis revealed that US features (tumor size > 4.35 cm, peritumoral enhancement, post-vascular ring enhancement, peak energy in the arterial phase of the difference between the margin area of HCC and distal liver parenchyma <-1.0 × 106 a.u), MRI features (rim enhancement, irregular tumor margin, and the halo sign) were all independent predictors of MVI (p < 0.05). The sensitivity and specificity of CEUS features in predicting MVI ranged from 61.9% to 86.4% and from 42.9% to 71.4%, respectively. For MRI features, the sensitivity and specificity ranged from 33.3% to 76.3% and from 54.7% to 90.5%, respectively. No statistically significant differences were observed in the area under the curve between CEUS and MRI (p > 0.05). Notably, peak energy of the difference showed the highest sensitivity at 86.4%, while the halo sign in MRI exhibited the highest specificity at 90.5%.

CONCLUSION

Sonazoid-CEUS and Gd-EOB-DTPA-enhanced MRI demonstrate potential in predicting MVI in HCC lesions. Notably, CEUS showed higher sensitivity, whereas MRI displayed greater specificity in predicting MVI.

Dual-energy computed tomography iodine quantification combined with laboratory data for predicting microvascular invasion in hepatocellular carcinoma: a two-centre study

OBJECTIVES

Microvascular invasion (MVI) is a recognized biomarker associated with poorer prognosis in patients with hepatocellular carcinoma. Dual-energy computed tomography (DECT) is a highly sensitive technique that can determine the iodine concentration (IC) in tumour and provide an indirect evaluation of internal microcirculatory perfusion. This study aimed to assess whether the combination of DECT with laboratory data can improve preoperative MVI prediction.

METHODS

This retrospective study enrolled 119 patients who underwent DECT liver angiography at 2 medical centres preoperatively. To compare DECT parameters and laboratory findings between MVI-negative and MVI-positive groups, Mann-Whitney U test was used. Additionally, principal component analysis (PCA) was conducted to determine fundamental components. Mann-Whitney U test was applied to determine whether the principal component (PC) scores varied across MVI groups. Finally, a general linear classifier was used to assess the classification ability of each PC score.

RESULTS

Significant differences were noted (P < .05) in alpha-fetoprotein (AFP) level, normalized arterial phase IC, and normalized portal phase IC between the MVI groups in the primary and validation datasets. The PC1-PC4 accounted for 67.9% of the variance in the primary dataset, with loadings of 24.1%, 16%, 15.4%, and 12.4%, respectively. In both primary and validation datasets, PC3 and PC4 were significantly different across MVI groups, with area under the curve values of 0.8410 and 0.8373, respectively.

CONCLUSIONS

The recombination of DECT IC and laboratory features based on varying factor loadings can well predict MVI preoperatively.

ADVANCES IN KNOWLEDGE

Utilizing PCA, the amalgamation of DECT IC and laboratory features, considering diverse factor loadings, showed substantial promise in accurately classifying MVI. There have been limited endeavours to establish such a combination, offering a novel paradigm for comprehending data in related research endeavours.

Clinical effect of hepatic artery interventional embolization and chemotherapy and its influence on P16 protein expression in patients with liver cancer

OBJECTIVE

To investigate clinical effects of hepatic artery interventional embolization chemotherapy (TACE) for primary hepatocellular carcinoma (PHC).

METHODS

73 patients with PHC in our hospital from January 2017 to January 2018 were selected and divided into 37 cases in study group and 36 cases in control group by random number table method. The control group received only ultrasound-guided microwave ablation treatment, and the study group received TACE treatment again before surgery based on control group. The expression levels of cancer antigen 125 (CA125), alpha-fetoprotein (AFP), multiple tumor suppressors 1 (P16) proteins, and cancer antigen 19-9 (CA19-9) were compared between the two groups at different time periods after treatment, and the remission rate (ORR), control rate (DCR), complication rate at 3 months after treatment and survival rate at 3 years after treatment were compared.

RESULTS

After 1 year of treatment, ORR, DCR, and P16 protein levels in the study group were higher than those in the control group (P < 0.05), and differences were statistically significant; CA125, CA19-9, and AFP levels in study group were lower than those in the control group (P < 0.05), and differences were statistically significant. The regression equation showed that long-term survival rate of both groups showed decreasing trend over time, while long-term survival rate of study group was always higher than that of the control group.

CONCLUSION

Comprehensive intervention for hepatic artery interventional chemoembolization in patients with primary hepatocellular carcinoma is more effective, which can effectively reduce incidence of complications and adverse effects in patients and help shorten treatment time of hepatic artery interventional chemoembolization in patients.

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.

Preoperative prediction of microvascular invasion classification in hepatocellular carcinoma based on clinical features and MRI parameters

Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a critical pathological factor and the degree of MVI influences treatment decisions and patient prognosis. The present study aimed to predict the MVI classification based on preoperative MRI features and clinical parameters. The present retrospective cohort study included 150 patients (training cohort, n=108; validation cohort, n=42) with pathologically confirmed HCC. Clinical and imaging characteristics data were collected from Shengli Oilfield Central Hospital (Dongying, China). Univariate and multivariate logistic regression analyses were conducted to assess the association of clinical variables and MRI parameters with MVI (grade M1 and M2) and the M2 classification. Nomograms were developed based on the predictive factors of MVI and the M2 classification. The discrimination capability, calibration and clinical usefulness of the nomograms were evaluated. Multivariate analysis revealed an association between the Lens culinaris agglutinin-reactive fraction of α-fetoprotein, protein induced by vitamin K absence-II and tumor margin and MVI-positive status, while peritumoral enhancement and tumor size were demonstrated to be marginal predictors, but were also included in the nomogram. However, among MVI-positive patients, only peritumoral hypointensity and tumor size were demonstrated to be risk factors for the M2 classification. The nomograms, incorporating these variables, exhibited a strong ability to discriminate between MVI-positive and MVI-negative patients with HCC in both the training and validation cohort [area under the curve (AUC), 0.877 and 0.914, respectively] and good performance in predicting the M2 classification in the training and validation cohorts (AUC, 0.720 and 0.782, respectively). Nomograms incorporating clinical parameters and preoperative MRI features demonstrated promising potential as straightforward and effective tools for predicting MVI and the M2 classification in patients with HCC. Such predictive tools could aid in the judicious selection of optimal clinical treatments.

MRI-based clinical-radiomics nomogram model for predicting microvascular invasion in hepatocellular carcinoma

BACKGROUND

Preoperative microvascular invasion (MVI) of liver cancer is an effective method to reduce the recurrence rate of liver cancer. Hepatectomy with extended resection and additional adjuvant or targeted therapy can significantly improve the survival rate of MVI+ patients by eradicating micrometastasis. Preoperative prediction of MVI status is of great clinical significance for surgical decision-making and the selection of other adjuvant therapy strategies to improve the prognosis of patients.

PURPOSE

Established a radiomics machine learning model based on multimodal MRI and clinical data, and analyzed the preoperative prediction value of this model for microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

METHOD

The preoperative liver MRI data and clinical information of 130 HCC patients who were pathologically confirmed to be pathologically confirmed were retrospectively studied. These patients were divided into MVI-positive group (MVI+) and MVI-negative group (MVI-) based on postoperative pathology. After a series of dimensionality reduction analysis, six radiomic features were finally selected. Then, linear support vector machine (linear SVM), support vector machine with rbf kernel function (rbf-SVM), logistic regression (LR), Random forest (RF) and XGBoost (XGB) algorithms were used to establish the MVI prediction model for preoperative HCC patients. Then, rbf-SVM with the best predictive performance was selected to construct the radiomics score (R-score). Finally, we combined R-score and clinical-pathology-image independent predictors to establish a combined nomogram model and corresponding individual models. The predictive performance of individual models and combined nomogram was evaluated and compared by receiver operating characteristic curve (ROC).

RESULT

Alpha-fetoprotein concentration, peritumor enhancement, maximum tumor diameter, smooth tumor margins, tumor growth pattern, presence of intratumor hemorrhage, and RVI were independent predictors of MVI. Compared with individual models, the final combined nomogram model (AUC: 0.968, 95% CI: 0.920-1.000) constructed by radiometry score (R-score) combined with clinicopathological parameters and apparent imaging features showed the optimal predictive performance.

CONCLUSION

This multi-parameter combined nomogram model had a good performance in predicting MVI of HCC, and had certain auxiliary value for the formulation of surgical plan and evaluation of prognosis.

Multiparametric MRI manifestations of the spontaneous intratumoral coagulative necrosis in HCC

PURPOSE

To investigate the MRI manifestations of the spontaneous intratumoral coagulative necrosis (iCN) in patients with hepatocellular carcinoma (HCC) and its value in predicting the postoperative early recurrence (≤ 2 years).

METHODS

Patients with HCC who underwent preoperative multiparametric MRI between January 2015 and February 2019 were enrolled in this retrospective study. The MRI manifestations of iCNs on TIWI, T2WI, and ADC were recorded. The sensitivity and specificity of MRI for the detection of iCNs were also evaluated. A multivariable Cox proportional hazards model and the Kaplan-Meier method were used to verify the value of histologically-confirmed and MRI-identified iCNs, respectively, in predicting early recurrence.

RESULTS

A total of 163 patients (median age, 56 years; interquartile range, 49-64 years; 139 men) with HCCs were evaluated, of whom 27(16.6%) had histologically-confirmed iCNs. MRI identified 92.6% (25 of 27; 95% confidence interval [CI] 74.2%, 98.7%) of iCNs (sensitivity), with a specificity of 79.4% (78 of 136; 95% CI 71.4%, 85.7%), based on non-enhancement on post-contrast MRI. And the MRI-identified iCNs were characterized by a similar appearance to surrounding tumour tissue shown on pre-contrast MRI but not enhanced on post-contrast MRI. The multivariable Cox proportional hazards model revealed that only the presence of histologically-confirmed iCN was independently associated with early HCC recurrence (hazard ratio = 2.73; 95% CI 1.20, 6.21; P = 0.017). The Kaplan-Meier curve showed that the presence of MRI-identified iCN was also associated with early recurrence (P < 0.001).

CONCLUSION

Multiparametric MRI identified iCNs with high sensitivity and modest specificity. The presence of iCNs is associated with early HCC recurrence.

Postoperative lenvatinib + PD-1 blockade reduces early tumor recurrence in hepatocellular carcinoma with microvascular invasion (Barcelona Clinic Liver Cancer stage 0 or A): a propensity score matching analysis

BACKGROUND

This study aimed to determine the effectiveness of postoperative adjuvant lenvatinib + PD-1 blockade for patients with early-stage hepatocellular carcinoma (HCC) with microvascular invasion (MVI).

METHODS

A total of 393 patients with HCC (Barcelona Clinic Liver Cancer stage 0 or A) who underwent curative hepatectomy with histopathologically proven MVI were enrolled according to the inclusion and exclusion criteria and assigned to 2 groups: surgery alone (surgery-alone group) and surgery with lenvatinib and PD-1 blockade (surgery + lenvatinib + PD-1 group) to compare recurrence-free survival (RFS), overall survival (OS), recurrence type, and annual recurrence rate after the application of propensity score matching (PSM). The Cox proportional hazards model was used for univariate and multivariate analyses.

RESULTS

Overall, 99 matched pairs were selected using PSM. Patients in the surgery + lenvatinib + PD-1 group had significantly higher 3-year RFS rates (76.8%, 65.7%, and 53.5%) than patients in the surgery-alone group (60.6%, 45.5%, and 37.4%) (P = .012). The 2 groups showed no significant difference in recurrence types and OS. Surgery alone, MVI-M2, and alpha-fetoprotein of ≥200 ng/mL were independent risk factors for RFS (P < .05), and history of alcohol use disorder was an independent risk factor for OS (P = .022).

CONCLUSION

Postoperative lenvatinib + PD-1 blockade improved the RFS in patients with HCC with MVI and was particularly beneficial for specific individuals.

Association Between MRI-Based Radiomics Features and Regional Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma and Its Clinical Outcome

BACKGROUND

Regional lymph node metastasis (LNM) assessment is crucial for predicting intrahepatic cholangiocarcinoma (iCCA) prognosis. However, imaging assessment has limitations for identifying LNM.

PURPOSE

To investigate the association between MRI radiomics features, regional LNM status, and prognosis in iCCA.

STUDY TYPE

Retrospective.

SUBJECTS

Two hundred ninety-six patients (male = 197) with surgically confirmed iCCA.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T. DWI, T2WI, and contrast-enhanced T1WI.

ASSESSMENT

Clinical information, radiologic, and MRI-based radiomics features associated with LNM status were collected to establish models. Performance of MRI, PET/CT, and the combined LNM models were compared in training (N = 207) and test (N = 89) datasets. Overall survival (OS) was compared based on LNM status.

STATISTICAL TESTS

The independent features were selected by 5-fold cross-validation. The performance of MRI, PET/CT, and the models was evaluated using the area under receiver operating characteristic curve (AUC). Univariable and multivariable Cox regression were used to identify independent variables for OS. Kaplan-Meier curves were compared with the log-rank test between LNM positive and negative groups. P < 0.05 was considered statistically significant.

RESULTS

Intrahepatic duct dilatation, enhancement pattern, and CA19-9 were independent clinicoradiologic features. The radiomics model was constructed by the independent radiomics features extracted from T2WI and delay phase T1WI. The combined LNM model showed AUC of 0.888, 0.884, and 0.811 in training, validation, and test cohorts with a positive net benefit. PET/CT exhibited similar sensitivity to the combined LNM model (0.750 vs. 0.733, P > 0.999) while the combined LNM model showed higher specificity (0.703 vs. 0.630, P = 0.039) in the test cohort. High risk of regional LNM was significantly associated with worse OS (median: 24 months) than low risk (median: 30 months, P < 0.0001).

DATA CONCLUSIONS

The combined LNM model has the strongest correlation with LNM status for mass-forming iCCA patients.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Establishing and Externally Validating a Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score-Based Nomogram for Predicting Early Recurrence in BCLC Stage 0/A Hepatocellular Carcinoma Patients After Radical Liver Resection: A Multi-Center Study

Purpose

Early recurrence (ER) is associated with poor prognosis in hepatocellular carcinoma (HCC). In this study, we developed and externally validated a nomogram based on the hemoglobin, albumin, lymphocytes, and platelets (HALP) score to predict ER for patients with BCLC stage 0/A HCC who underwent radical liver resection.

Patients and Methods

A total of 808 BCLC stage 0/A HCC patients from six hospitals were included in this study, and they were assigned to a training cohort (n = 500) and an external validation cohort (n = 308). We used univariate and multivariate Cox regression analysis to identify the independent risk factors for disease-free survival (DFS). We also established and externally validated a nomogram based on these risk predictors. The nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), the concordance index (C-index), the calibration curve, decision curve analysis (DCA), and Kaplan‒Meier analysis.

Results

Multivariate COX regression showed that HBV DNA ≥10,000 IU/mL (P < 0.001), HALP score ≤38.20 (P < 0.001), tumor size (P = 0.003), clinically significant portal hypertension (P = 0.001), Edmondson-Steiner grade (III-IV) (P = 0.007), satellite nodules (P < 0.001), and MVI (P = 0.001) were independent risk factors for post-operative tumor recurrence. The AUC of our nomogram for predicting the 2-year and 5-year DFS was 0.756 and 0.750, respectively, in the training cohort and 0.764 and 0.705, respectively, in the external validation cohort. We divided the patients into low-, intermediate- and high-risk groups according to the risk score calculated by the nomogram. There were statistically significant differences in the DFS and overall survival (OS) among the three groups of patients (P < 0.001).

Conclusion

We developed and externally validated a new nomogram, which is accurate and can predict ER in BCLC stage 0/A HCC patients after curative liver resection.

Impact of HBV Integration on Hepatocellular Carcinoma After Long-Term Antiviral Therapy

Purpose

Few studies have reported the integrated characteristics of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) after long-term antiviral therapy. This study aimed to investigate the HBV integration features in HBV-HCC patients who had undergone long-term antiviral therapy, evaluate their impact on clinical indicators, and analyze the potential mechanisms involved.

Patients and Methods

We utilized genome-wide association study (GWAS) to analyze liver cancer tissues and detect the presence of HBV integration. Seventeen patients with HBV integration were included in the integration (Int) group, while the remaining five patients were included in the non-integration (N-int) group. Clinical indicators were regularly monitored and compared between the two groups. The characteristics of HBV integration patterns were analyzed, and differences between the groups were explored at the chromosome and genomic levels.

Results

After long-term antiviral therapy, although the frequency of HBV integration in HBV-HCC was reduced, residual HBV integration still accelerated the development of HCC. It affected the diagnosis, treatment, and prognosis of patients. HBV integration events led to changes in chromosome structure, which were closely related to HCC. Novel fusion genes were detected at a high frequency and had the potential to be specific detection sites for HBV-HCC.

Conclusion

HBV integration events are synergistically involved in the human genome and HBV, which can lead to chromosome structural instability, gene rearrangement events closely related to HCC production, and the formation of new specific fusion genes.

Prognostic implications of preoperative, postoperative, and dynamic changes of alpha-fetoprotein and des-gamma (γ)-carboxy prothrombin expression pattern for hepatocellular carcinoma after hepatic resection: a multicenter observational study

Background

The utility of pre- and post-operative alpha-fetoprotein (AFP) and des-gamma (γ)-carboxy prothrombin (DCP) expression patterns and their dynamic changes as predictors of the outcome of hepatic resection for hepatocellular carcinoma (HCC) has yet to be well elucidated.

Methods

From a multicenter database, AFP and DCP data during the week prior to surgery and the first post-discharge outpatient visit (within 1-2 months after surgery) were collected from patients with HCC who underwent hepatectomy. AFP-DCP expression patterns were categorized according to the number of positive tumor markers (AFP ≥ 20ng/mL, DCP ≥ 40mAU/mL), including double-negative, single-positive, and double-positive. Changes in the AFP-DCP expression patterns were delineated based on variations in the number of positive tumor markers when comparing pre- and post-operative patterns.

Results

Preoperatively, 53 patients (8.3%), 337 patients (52.8%), and 248 patients (38.9%) exhibited double-negative, single-positive, and double-positive AFP-DCP expression patterns, respectively. Postoperatively, 463 patients (72.6%), 130 patients (20.4%), and 45 patients (7.0%) showed double-negative, single-positive, and double-positive AFP-DCP expression patterns, respectively. Survival analysis showed a progressive decrease in recurrence-free (RFS) and overall survival (OS) as the number of postoperative positive tumor markers increased (both P < 0.001). Multivariate analysis showed that postoperative AFP-DCP expression pattern, but not preoperative AFP-DCP expression pattern, was an independent risk factor for RFS and OS. Further analysis showed that for patients with positive preoperative markers, prognosis gradually improves as positive markers decrease postoperatively. In particular, when all postoperative markers turned negative, the prognosis was consistent with that of preoperative double-negative patients, regardless of the initial number of positive markers.

Conclusions

AFP-DCP expression patterns, particularly postoperative patterns, serve as vital sources of information for prognostic evaluation following hepatectomy for HCC. Moreover, changes in AFP-DCP expression patterns from pre- to post-operation enable dynamic prognostic risk stratification postoperatively, aiding the development of individualized follow-up strategies.

Recommendations on maximising the clinical value of tissue in the management of patients with intrahepatic cholangiocarcinoma

Background & Aims

Patients with intrahepatic cholangiocarcinoma can now be managed with targeted therapies directed against specific molecular alterations. Consequently, tissue samples submitted to the pathology department must produce molecular information in addition to a diagnosis or, for resection specimens, staging information. The pathologist's role when evaluating these specimens has therefore changed to accommodate such personalised approaches.

Methods

We developed recommendations and guidance for pathologists by conducting a systematic review of existing guidance to generate candidate statements followed by an international Delphi process. Fifty-nine pathologists from 28 countries in six continents rated statements mapped to all elements of the specimen pathway from receipt in the pathology department to authorisation of the final written report. A separate survey of 'end-users' of the report including surgeons, oncologists, and gastroenterologists was undertaken to evaluate what information should be included in the written report to enable appropriate patient management.

Results

Forty-eight statements reached consensus for inclusion in the guidance including 10 statements about the content of the written report that also reached consensus by end-user participants. A reporting proforma to allow easy inclusion of the recommended data points was developed.

Conclusions

These guiding principles and recommendations provide a framework to allow pathologists reporting on patients with intrahepatic cholangiocarcinoma to maximise the informational yield of specimens required for personalised patient management.

Impact and Implications

Biopsy or resection lesional tissue from intrahepatic cholangiocarcinoma must yield information about the molecular abnormalities within the tumour that define suitability for personalised therapies in addition to a diagnosis and staging information. Here, we have developed international consensus guidance for pathologists that report such cases using a Delphi process that sought the views of both pathologists and 'end-users of pathology reports. The guide highlights the need to report cases in a way that preserves tissue for molecular testing and emphasises that reporting requires interpretation of histological characteristics within the broader clinical and radiological context. The guide will allow pathologists to report cases of intrahepatic cholangiocarcinoma in a uniform manner that maximises the value of the tissue received to facilitate optimal multidisciplinary patient management.

CEUS in prediction of early recurrence of hepatocellular carcinoma after curative resection and to stratify the risk of early recurrence: a retrospective observational study

PURPOSE

Early recurrence (ER) after surgery is related to early death in patients with hepatocellular carcinoma (HCC) after radical resection. To explore the role of preoperative contrast-enhanced ultrasound (CEUS) in predicting ER of HCC after curative resection and to stratify the risk of ER.

MATERIALS AND METHODS

This study evaluated consecutive 556 patients with HCC who were examined by CEUS during the 2 weeks before curative resection between January 2011 and December 2018. ER was defined as intrahepatic and/or extrahepatic recurrence within 2 year after resection of HCC. Univariate and logistic regression analyses were performed to identify independent risk factors for ER after surgical resection of HCC. Recurrence-free time (RFS) rates were analyzed and compared by log-rank test.

RESULTS

ER occurred in 307 (55.2%) of the 556 patients. Univariate and multivariate analyses revealed that a tumor size ≥ 30 mm and satellite nodules seen on CEUS, DL(deep learning) radiomics reoccurrence score based on the frame of image with the maximum intensity of CEUS and an elevated alpha-fetoprotein level were significantly associated with ER (P < .05). Based on the number of predictors present, patients with CEUS LR-5 HCC were stratified into three risk subgroups: risk group 3 (high-risk patients, 4 predictors), risk group 2 (medium-risk patients, 2-3 predictors), and risk group 1 (low-risk patients, 0-1 predictor). The 2-year RFS rate was 19.4% in risk group 3, 40.9% in risk group 2, and 48.1% in risk group 1; the corresponding mean RFS times were 14.0 ± 2.9 months, 43.7 ± 6.6 months, and 55.5 ± 2.8 months, respectively (P < .001).

CONCLUSIONS

Tumor size ≥ 30 mm and satellite nodules seen on CEUS, DL radiomics reoccurrence score based on the frame of image with the maximum intensity of CEUS and an elevated alpha-fetoprotein level can predict ER of HCC.

CEMRI-Based Quantification of Intratumoral Heterogeneity for Predicting Aggressive Characteristics of Hepatocellular Carcinoma Using Habitat Analysis: Comparison and Combination of Deep Learning

RATIONALE AND OBJECTIVES

To explore both an intratumoral heterogeneity (ITH) model based on habitat analysis and a deep learning (DL) model based on contrast-enhanced magnetic resonance imaging (CEMRI) and validate its efficiency for predicting microvascular invasion (MVI) and pathological differentiation in hepatocellular carcinoma (HCC).

METHODS

CEMRI images were retrospectively obtained from 277 HCCs in 265 patients. Habitat analysis and DL features were extracted from the CEMRI images and selected with the least absolute shrinkage and selection operator approach to develop ITH and DL models, respectively, and these robust features were then integrated to design a fusion model for predicting MVI and poorly differentiated HCC (pHCC). The predictive value of the three models was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

The training and validation sets comprised 221 HCCs and 56 HCCs, respectively. The ITH and DL models presented AUC values of (0.90 vs. 0.87) for predicting MVI in the training set, with AUC values of 0.86 and 0.83 in the validation set. The AUC values of the ITH model to predict pHCC were 0.90 and 0.86 in the two sets, respectively; they were 0.84 and 0.80 for the DL model. The fusion model yielded the best performance for predicting MVI and pHCC in the training set (AUC=0.95, 0.90) and in the validation set (AUC=0.89, 0.87), respectively.

CONCLUSION

A fusion model integrating ITH and DL features derived from CEMRI images can serve as an excellent imaging biomarker for predicting aggressive characteristics in HCC.

A new scoring system for predicting the outcome of hepatocellular carcinoma patients without microvascular invasion-a large-scale multicentre study

BACKGROUND

The prognosis of HCC patients without MVI (so called M0) is highly heterogeneous and the need for adjuvant therapy is still controversial.

METHODS

Patients with HCC with M0 who underwent liver resection (LR) or liver transplantation (LT) as an initial therapy were included. The Eastern Hepatobiliary Surgery Hospital (EHBH)-M0 score was developed from a retrospective cohort to form the training cohort. The classification which was developed using multivariate cox regression analysis was externally validated.

RESULTS

The score was developed using the following factors: α-fetoprotein level, tumour diameter, liver cirrhosis, total bilirubin, albumin and aspartate aminotransferase. The score differentiated two groups of M0 patients (≤3, >3 points) with distinct long-term prognoses outcomes (median overall survival (OS), 98.0 vs. 46.0 months; p < 0.001). The predictive accuracy of the score was greater than the other commonly used staging systems for HCC. And for M0 patients with a higher score underwent LR. Adjuvant transcatheter arterial chemoembolization (TACE) was effective to prolong OS.

CONCLUSIONS

The EHBH M0 scoring system was more accurate in predicting the prognosis of HCC patients with M0 after LR or LT. Adjuvant therapy is recommended for HCC patients who have a higher score.

Apparent diffusion coefficient and tissue stiffness are associated with different tumor microenvironment features of hepatocellular carcinoma

OBJECTIVES

To investigate associations between tissue diffusion, stiffness, and different tumor microenvironment features in resected hepatocellular carcinoma (HCC).

METHODS

Seventy-two patients were prospectively included for preoperative magnetic resonance (MR) diffusion-weighted imaging and MR elastography examination. The mean apparent diffusion coefficient (ADC) and stiffness value were measured on the central three slices of the tumor and peri-tumor area. Cell density, tumor-stroma ratio (TSR), lymphocyte-rich HCC (LR-HCC), and CD8 + T cell infiltration were estimated in resected tumors. The interobserver agreement of MRI measurements and subjective pathological evaluation was assessed. Variables influencing ADC and stiffness were screened with univariate analyses, and then identified with multivariable linear regression. The potential relationship between explored imaging biomarkers and histopathological features was assessed with linear regression after adjustment for other influencing factors.

RESULTS

Seventy-two patients (male/female: 59/13, mean age: 56 ± 10.2 years) were included for analysis. Inter-reader agreement was good or excellent regarding MRI measurements and histopathological evaluation. No correlation between tumor ADC and tumor stiffness was found. Multivariable linear regression confirmed that cell density was the only factor associated with tumor ADC (Estimate = -0.03, p = 0.006), and tumor-stroma ratio was the only factor associated with tumor stiffness (Estimate = -0.18, p = 0.03). After adjustment for fibrosis stage (Estimate = 0.43, p < 0.001) and age (Estimate = 0.04, p < 0.001) in the multivariate linear regression, intra-tumoral CD8 + T cell infiltration remained a significant factor associated with peri-tumor stiffness (Estimate = 0.63, p = 0.02).

CONCLUSIONS

Tumor ADC surpasses tumor stiffness as a biomarker of cellularity. Tumor stiffness is associated with tumor-stroma ratio and peri-tumor stiffness might be an imaging biomarker of intra-tumoral immune microenvironment.

CLINICAL RELEVANCE STATEMENT

Tissue stiffness could potentially serve as an imaging biomarker of the intra-tumoral immune microenvironment of hepatocellular carcinoma and aid in patient selection for immunotherapy.

KEY POINTS

Apparent diffusion coefficient reflects cellularity of hepatocellular carcinoma. Tumor stiffness reflects tumor-stroma ratio of hepatocellular carcinoma and is associated with tumor-infiltrating lymphocytes. Tumor and peri-tumor stiffness might serve as imaging biomarkers of intra-tumoral immune microenvironment.

A multi-parametric prognostic model based on clinicopathologic features: vessels encapsulating tumor clusters and hepatic plates predict overall survival in hepatocellular carcinoma patients

BACKGROUND

Vessels encapsulating tumor clusters (VETC) is a newly described vascular pattern that is distinct from microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Despite its importance, the current pathological diagnosis report does not include information on VETC and hepatic plates (HP). We aimed to evaluate the prognostic value of integrating VETC and HP (VETC-HP model) in the assessment of HCC.

METHODS

A total of 1255 HCC patients who underwent radical surgery were classified into training (879 patients) and validation (376 patients) cohorts. Additionally, 37 patients treated with lenvatinib were studied, included 31 patients in high-risk group and 6 patients in low-risk group. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to establish a prognostic model for the training set. Harrell's concordance index (C-index), time-dependent receiver operating characteristics curve (tdROC), and decision curve analysis were utilized to evaluate our model's performance by comparing it to traditional tumor node metastasis (TNM) staging for individualized prognosis.

RESULTS

A prognostic model, VETC-HP model, based on risk scores for overall survival (OS) was established. The VETC-HP model demonstrated robust performance, with area under the curve (AUC) values of 0.832 and 0.780 for predicting 3- and 5-year OS in the training cohort, and 0.805 and 0.750 in the validation cohort, respectively. The model showed superior prediction accuracy and discrimination power compared to TNM staging, with C-index values of 0.753 and 0.672 for OS and disease-free survival (DFS) in the training cohort, and 0.728 and 0.615 in the validation cohort, respectively, compared to 0.626 and 0.573 for TNM staging in the training cohort, and 0.629 and 0.511 in the validation cohort. Thus, VETC-HP model had higher C-index than TNM stage system(p < 0.01).Furthermore, in the high-risk group, lenvatinib alone appeared to offer less clinical benefit but better disease-free survival time.

CONCLUSIONS

The VETC-HP model enhances DFS and OS prediction in HCC compared to traditional TNM staging systems. This model enables personalized temporal survival estimation, potentially improving clinical decision-making in surveillance management and treatment strategies.

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.

Role of microvascular invasion in early recurrence of hepatocellular carcinoma after liver resection: A literature review

Hepatectomy is widely considered a potential treatment for hepatocellular carcinoma (HCC). Unfortunately, one-third of HCC patients have tumor recurrence within 2 years after surgery (early recurrence), accounting for more than 60% of all recurrence patients. Early recurrence is associated with a worse prognosis. Previous studies have shown that microvascular invasion (MVI) is one of the key factors for early recurrence and poor prognosis in patients with HCC after surgery. This paper reviews the latest literature and summarizes the predictors of MVI, the correlation between MVI and early recurrence, the identification of suspicious nodules or subclinical lesions, and the treatment strategies for MVI-positive HCC. The aim is to explore the management of patients with MVI-positive HCC.

Adjuvant Transarterial Chemoembolization Plus Immunotherapy for Huge Hepatocellular Carcinoma: A Propensity Score Matching Cohort Study

Purpose

The prognosis of patients with huge hepatocellular carcinoma (huge HCC, diameter ≥10 cm) is poor owing to the high early recurrence rate. This study aimed to explore the clinical value of postoperative adjuvant transarterial chemoembolization (PA-TACE) plus programmed cell death-1 (PD-1) inhibitors for huge HCC.

Patients and Methods

Data from consecutive huge HCC patients treated with hepatectomy during June 2017 and July 2022 were retrospectively collected. Baseline differences were balanced between huge HCC patients who underwent PA-TACE with (AIT group) or without PD-1 inhibitors (AT group) by propensity-score matching (PSM). We compared recurrence-free survival (RFS), overall survival (OS) and recurrence patterns between the two groups. Independent risk factors for RFS and OS were confirmed by Cox regression analysis, and subgroup analysis was also conducted.

Results

A total of 294 patients were enrolled, and 77 pairs of patients in the AIT and AT groups were matched by PSM. The 1-year and 2-year RFS were 49.9% and 35.7% in the AIT group compared to 24.7% and 15.5% in the AT group respectively (p<0.001). The 1-year and 2-year OS were 83.6% and 66.9% in the AIT group compared to 50.6% and 36.8% in the AT group respectively (p<0.001). There were no significant differences in recurrence patterns between the two groups. Multivariable analysis demonstrated that combined therapy of PA-TACE plus PD-1 inhibitors was a protective factor related to both RFS and OS.

Conclusion

PA-TACE plus PD-1 inhibitors could improve survival outcomes for huge HCC patients.

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.

Optimizing hepatocellular carcinoma disease staging systems by incorporating tumor micronecrosis: A multi-institutional retrospective study

Tumor micronecrosis is a pathological feature that reflects malignant biological behavior in hepatocellular carcinoma (HCC). However, whether micronecrosis can optimize HCC staging systems remains unilluminated. A total of 1632 HCC patients who underwent curative hepatectomy in four institutions from January 2014 to December 2021 were enrolled in this study. Independent prognostic factors were identified, and optimized staging models were established using a training cohort (n = 934). The performance of optimized staging models was validated using an external cohort consisting of cases from three other institutions (n = 232). In addition, patients from our prospectively collected database (n = 379) tested the application effectiveness of the models. Harrel's c-statistics and the corrected Akaike information criterion (AICc) were used to assess the performance of staging models. In most of Barcelona Clinic Liver Cancer (BCLC) and tumor (T) stages, HCC patients with tumor micronecrosis showed poorer prognosis than those without. Tumor micronecrosis, microvascular invasion, multiple tumors and tumor size >2 cm were independent prognostic-related factors. The BCLC and T staging models incorporating tumor micronecrosis showed better performance than the original systems (c-statistic, 0.712 and 0.711 vs. 0.664 and 0.679; AICc, 2314.8 and 2322.3 vs. 2338.2 and 2338.1; respectively). Furthermore, the external validation cohort confirmed that the optimized staging models had improved efficiency compared with the original ones. Moreover, the prospective cohort demonstrated the applicability of the optimized staging systems. Tumor micronecrosis plays a stage-ascending role in HCC patients. The BCLC and T staging systems incorporating tumor micronecrosis can improve the prognosis stratification efficiency of patients.

Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma: Machine learning model based on contrast-enhanced computed tomography

BACKGROUND

Recently, vessels encapsulating tumor clusters (VETC) was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner, and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma (HCC).

AIM

To develop and validate a preoperative nomogram using contrast-enhanced computed tomography (CECT) to predict the presence of VETC+ in HCC.

METHODS

We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers. Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase. Radiomics features, essential for identifying VETC+ HCC, were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set. The model's performance was validated on two separate test sets. Receiver operating characteristic (ROC) analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets. The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features. ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features, the radiomics features and the radiomics nomogram.

RESULTS

The study included 190 individuals from two independent centers, with the majority being male (81%) and a median age of 57 years (interquartile range: 51-66). The area under the curve (AUC) for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825, 0.788, and 0.680 in the training set and the two test sets. A total of 13 features were selected to construct the Rad-score. The nomogram, combining clinical-radiological and combined radiomics features could accurately predict VETC+ in all three sets, with AUC values of 0.859, 0.848 and 0.757. Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models.

CONCLUSION

This study demonstrates the potential utility of a CECT-based radiomics nomogram, incorporating clinical-radiological features and combined radiomics features, in the identification of VETC+ HCC.

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.

Adjuvant sintilimab in resected high-risk hepatocellular carcinoma: a randomized, controlled, phase 2 trial

Hepatocellular carcinoma (HCC), particularly when accompanied by microvascular invasion (MVI), has a markedly high risk of recurrence after liver resection. Adjuvant immunotherapy is considered a promising avenue. This multicenter, open-label, randomized, controlled, phase 2 trial was conducted at six hospitals in China to assess the efficacy and safety of adjuvant sintilimab, a programmed cell death protein 1 inhibitor, in these patients. Eligible patients with HCC with MVI were randomized (1:1) into the sintilimab or active surveillance group. The sintilimab group received intravenous injections every 3 weeks for a total of eight cycles. The primary endpoint was recurrence-free survival (RFS) in the intention-to-treat population. Key secondary endpoints included overall survival (OS) and safety. From September 1, 2020, to April 23, 2022, a total of 198 eligible patients were randomly allocated to receive adjuvant sintilimab (n = 99) or undergo active surveillance (n = 99). After a median follow-up of 23.3 months, the trial met the prespecified endpoints. Sintilimab significantly prolonged RFS compared to active surveillance (median RFS, 27.7 versus 15.5 months; hazard ratio 0.534, 95% confidence interval 0.360-0.792; P = 0.002). Further follow-up is needed to confirm the difference in OS. In the sintilimab group, 12.4% of patients experienced grade 3 or 4 treatment-related adverse events, the most common of which were elevated alanine aminotransferase levels (5.2%) and anemia (4.1%). These findings support the potential of immune checkpoint inhibitors as effective adjuvant therapy for these high-risk patients. Chinese Clinical Trial Registry identifier: ChiCTR2000037655 .

Development and Comparison of Prediction Models Based on Sonovue- and Sonazoid-Enhanced Ultrasound for Pathologic Grade and Microvascular Invasion in Hepatocellular Carcinoma

OBJECTIVE

This study was aimed at developing and comparing prediction models based on Sonovue and Sonazoid contrast-enhanced ultrasound (CEUS) in predicting pathologic grade and microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Also investigated was whether Kupffer phase images have additional predictive value for the above pathologic features.

METHODS

Ninety patients diagnosed with primary HCC who had undergone curative hepatectomy were prospectively enrolled. All patients underwent conventional ultrasound (CUS), Sonovue-CEUS and Sonazoid-CEUS examinations pre-operatively. Clinical, radiologic and pathologic features including pathologic grade, MVI and CD68 expression were collected. We developed prediction models comprising clinical, CUS and CEUS (Sonovue and Sonazoid, respectively) features for pathologic grade and MVI with both the logistic regression and machine learning (ML) methods.

RESULTS

Forty-one patients (45.6%) had poorly differentiated HCC (p-HCC) and 37 (41.1%) were MVI positive. For pathologic grade, the logistic model based on Sonazoid-CEUS had significantly better performance than that based on Sonovue-CEUS (area under the curve [AUC], 0.929 vs. 0.848, p = 0.035), whereas for MVI, these two models had similar accuracy (AUC, 0.810 vs. 0.786, p = 0.068). Meanwhile, we found that well-differentiated HCC tended to have a higher enhancement ratio in 6-12 min during the Kupffer phase of Sonazoid-CEUS, as well as higher CD68 expression compared with p-HCC. In addition, all of these models can effectively predict the risk of recurrence (p < 0.05).

CONCLUSION

Sonovue-CEUS and Sonazoid-CEUS were comparably excellent in predicting MVI, while Sonazoid-CEUS was superior to Sonovue-CEUS in predicting pathologic grade because of the Kupffer phase. The enhancement ratio in the Kupffer phase has additional predictive value for pathologic grade prediction.

Actuality and underlying mechanisms of systemic immune-inflammation index and geriatric nutritional risk index prognostic value in hepatocellular carcinoma

This editorial contains comments on the article "Correlation between preoperative systemic immune inflammation index, nutritional risk index, and prognosis of radical resection of liver cancer" in a recent issue of the World Journal of Gastrointestinal Surgery. It pointed out the actuality and importance of the article and focused primarily on the underlying mechanisms making the systemic immune-inflammation index (SII) and geriatric nutritional risk index (GNRI) prediction features valuable. There are few publications on both SII and GNRI together in hepatocellular carcinoma (HCC) and patient prognosis after radical surgery. Neutrophils release cytokines, chemokines, and enzymes, degrade extracellular matrix, reduce cell adhesion, and create conditions for tumor cell invasion. Neutrophils promote the adhesion of tumor cells to endothelial cells, through physical anchoring. That results in the migration of tumor cells. Pro-angiogenic factors from platelets enhance tumor angiogenesis to meet tumor cell supply needs. Platelets can form a protective film on the surface of tumor cells. This allows avoiding blood flow damage as well as immune system attack. It also induces the epithelial-mesenchymal transformation of tumor cells that is critical for invasiveness. High SII is also associated with macro- and microvascular invasion and increased numbers of circulating tumor cells. A high GNRI was associated with significantly better progression-free and overall survival. HCC patients are a very special population that requires increased attention. SII and GNRI have significant survival prediction value in both palliative treatment and radical surgery settings. The underlying mechanisms of their possible predictive properties lie in the field of essential cancer features. Those features provide tumor nutrition, growth, and distribution throughout the body, such as vascular invasion. On the other hand, they are tied to the possibility of patients to resist tumor progression and development of complications in both postoperative and cancer-related settings. The article is of considerable interest. It would be helpful to continue the study follow-up to 2 years and longer. External validation of the data is needed.

[Prediction of microvascular invasion in hepatocellular carcinoma based on multi-phase dynamic enhanced CT radiomics feature and multi-classifier hierarchical fusion model]

OBJECTIVE

To predict microvascular invasion (MVI) in hepatocellular carcinoma (HCC) using a model based on multiphase dynamic-enhanced CT (DCE-CT) radiomics feature and hierarchical fusion of multiple classifiers.

METHODS

We retrospectively collected preoperative DCE-CT images from 111 patients with pathologically confirmed HCC in Guangzhou First People's Hospital between January, 2016 and April, 2020. The volume of interest was outlined in the early arterial phase, late arterial phase, portal venous phase and equilibrium phase, and radiomics features of these 4 phases were extracted. Seven classifiers based on different algorithms were trained using the filtered feature subsets to obtain multiple base classifiers under each phase. According to the hierarchical fusion strategy, a multi-criteria decision-making-based weight assignment algorithm was used for fusing each base classifier under the same phase with the model after extracting the phase information to obtain the prediction model. The proposed model was evaluated using a 5-fold cross-validation and assessed for area under the ROC curve (AUC), accuracy, sensitivity, and specificity. The prediction model was also compared with the fusion models using a single phase or multiple phases, models based on a single phase with a single classifier, models with different base classifier diversities, and 8 classifier models based on other ensemble methods.

RESULTS

The experimental results showed that the performance of the proposed model for predicting HCCMVI was optimal after incorporating the 4 phases and 7 classifiers, with AUC, accuracy, sensitivity, and specificity of 0.828, 0.766, 0.877, and 0.648, respectively. Comparative experiments showed that this prediction model outperformed the models based on a single phase with a single classifier and other ensemble models.

CONCLUSION

The proposed prediction model is effective for predicting MVI in HCC with superior performance to other models.

Comparison contrast-enhanced CT with contrast-enhanced US in diagnosing combined hepatocellular-cholangiocarcinoma: a propensity score-matched study

OBJECTIVES

To develop and compare noninvasive models for differentiating between combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and HCC based on serum tumor markers, contrast-enhanced ultrasound (CEUS), and computed tomography (CECT).

METHODS

From January 2010 to December 2021, patients with pathologically confirmed cHCC-CCA or HCC who underwent both preoperative CEUS and CECT were retrospectively enrolled. Propensity scores were calculated to match cHCC-CCA and HCC patients with a near-neighbor ratio of 1:2. Two predicted models, a CEUS-predominant (CEUS features plus tumor markers) and a CECT-predominant model (CECT features plus tumor markers), were constructed using logistic regression analyses. Model performance was evaluated by the area under the curve (AUC), sensitivity, specificity, and accuracy.

RESULTS

A total of 135 patients (mean age, 51.3 years ± 10.9; 122 men) with 135 tumors (45 cHCC-CCA and 90 HCC) were included. By logistic regression analysis, unclear boundary in the intratumoral nonenhanced area, partial washout on CEUS, CA 19-9 > 100 U/mL, lack of cirrhosis, incomplete tumor capsule, and nonrim arterial phase hyperenhancement (APHE) volume < 50% on CECT were independent factors for a diagnosis of cHCC-CCA. The CECT-predominant model showed almost perfect sensitivity for cHCC-CCA, unlike the CEUS-predominant model (93.3% vs. 55.6%, p < 0.001). The CEUS-predominant model showed higher diagnostic specificity than the CECT-predominant model (80.0% vs. 63.3%; p = 0.020), especially in the ≤ 5 cm subgroup (92.0% vs. 70.0%; p = 0.013).

CONCLUSIONS

The CECT-predominant model provides higher diagnostic sensitivity than the CEUS-predominant model for CHCC-CCA. Combining CECT features with serum CA 19-9 > 100 U/mL shows excellent sensitivity.

CRITICAL RELEVANCE STATEMENT

Combining lack of cirrhosis, incomplete tumor capsule, and nonrim arterial phase hyperenhancement (APHE) volume < 50% on CECT with serum CA 19-9 > 100 U/mL shows excellent sensitivity in differentiating cHCC-CCA from HCC.

KEY POINTS

1. Accurate differentiation between cHCC-CCA and HCC is essential for treatment decisions. 2. The CECT-predominant model provides higher accuracy than the CEUS-predominant model for CHCC-CCA. 3. Combining CECT features and CA 19-9 levels shows a sensitivity of 93.3% in diagnosing cHCC-CCA.

Impact of preoperative transcatheter arterial chemoembolization (TACE) on postoperative long-term survival in patients with nonsmall hepatocellular carcinoma: a propensity score matching analysis

BACKGROUND

The purpose of this propensity score matching (PSM) analysis was to compare the effects of preoperative transcatheter arterial chemoembolization (TACE) and non-TACE on the long-term survival of patients who undergo radical hepatectomy.

METHODS

PSM analysis was performed for 387 patients with hepatocellular carcinoma (HCC) (single > 3 cm or multiple) who underwent radical resection of HCC at our centre from January 2011 to June 2018. The patients were allocated to a preoperative TACE group (n = 77) and a non-TACE group (n = 310). The main outcome measures were progression-free survival (PFS) and overall survival (OS) since the treatment date.

RESULTS

After PSM, 67 patients were included in each of the TACE and non-TACE groups. The median PFS times in the preoperative TACE and non-TACE groups were 24.0 and 11.3 months, respectively (p = 0.0117). The median OS times in the preoperative TACE and non-TACE groups were 41.5 and 29.0 months, respectively (p = 0.0114). Multivariate Cox proportional hazard regression analysis revealed that preoperative TACE (hazard ratio, 1.733; 95% CI, 1.168-2.570) and tumour thrombosis (hazard ratio, 0.323; 95% CI, 0.141-0.742) were independent risk factors significantly associated with OS.

CONCLUSIONS

Preoperative TACE is related to improving PFS and OS after resection of HCC. Preoperative TACE and tumour thrombus volume were also found to be independent risk factors associated with OS.

Analysis of clinicopathologic and imaging features of dual-phenotype hepatocellular carcinoma

Dual-phenotype hepatocellular carcinoma (DPHCC) is a new subtype of hepatocellular carcinoma (HCC). This study aimed to investigate the relationship between the computerized tomography scan (CT) imaging and clinicopathologic features of DPHCC. The CT imaging and clinicopathologic data of 97 HCC cases who underwent radical resection were collected retrospectively. The CT imaging feature was evaluated by the ratio of the average CT value of tumor to liver (TLR) in the plain scan, arterial, portal vein and delayed phases. The association between CT imaging and clinicopathologic features was analyzed using the t-test or chi-square test. Univariate and multivariate recurrence-free survival (RFS) analysis and overall survival (OS) were performed. The positive rates of cytokeratin 7 (CK7) and CK19 were 35.1% and 20.6% respectively. The positive rate of CK19 was significantly higher in cases with age < 47 years (P = 0.005), tumor diameter > 4 cm (P = 0.016) or AFP ≥ 400 ng/ml (P = 0.007). The TLR in the portal vein phase was significantly lower in CK19 positive group (P = 0.024). The recurrence risk was significantly higher in cases with CK19 positive (HR: 2.17, 95% CI 1.16 to 4.04, P = 0.013), tumor diameter > 4 cm (HR: 2.05, 95% CI 1.11 to 3.78, P = 0.019), AFP ≥ 400 ng/ml (HR: 2.50, 95% CI 1.37 to 4.54, P = 0.002) or CA199 ≥ 37 U/ml (HR: 2.23, 95% CI 1.12 to 4.42, P = 0.020). However, imaging features, pathological subtype, CK7 or CK19 expression were not significantly related to HCC OS in the univariate and multivariate analysis (all P > 0.05). The expression of CK19 may be associated with the enhancement feature of the portal vein phase CT image, and CK19 positive may suggest a worse RFS.

Predicting cancer-specific mortality in T1/2 hepatocellular carcinoma after radiofrequency ablation by competing risk nomogram: A population-based analysis

BACKGROUND

Radiofrequency ablation (RFA) is one of the primary treatment methods for T1/2 hepatocellular carcinoma (HCC), but the risk factors after RFA remain controversial. This study aims to identify the key factors associated with cancer-specific mortality (CSM) in patients with T1/2 HCC after RFA using competing risk analysis and to establish a prognostic nomogram for improved clinical management.

METHODS

A total of 2,135 T1/2 HCC patients treated with RFA were obtained from the Surveillance, Epidemiology, and End Results (SEER) database and randomly categorized into training and validation sets. Univariate and multivariable competing risk analyses were performed to identify risk factors associated with CSM and construct a competing risk nomogram. Receiver operating characteristic (ROC) curves, concordance indices (C-indexes), calibration plots, and decision curve analysis (DCA) were conducted to evaluate the predictive efficiency and clinical applicability of the nomogram in the training and validation sets. Patients were stratified according to their nomogram score, and the different risk groups were compared using cumulative incidence function (CIF) curves and Gray's validation .

RESULTS

The 5-year CSM rate for HCC patients treated with RFA was 30.1 %. Grade, tumor size, tumor number, cirrhosis, and AFP level were identified as independent risk factors for CSM. A prognostic nomogram was developed based on these risk factors. The time-dependent C-indexes (0.65) were greater than those of the AJCC stage model (0.55) during the 12 to 60 months of follow-up. The calibration plots of the competing risk nomograms demonstrated excellent consistency between actual survival and nomogram predictions. ROC analyses showed that the 1-, 3-, and 5-year AUC values in both the training and validation cohorts were all greater than 0.63 and exceeded those of the AJCC stage model. DCA demonstrated the clinical usefulness of the nomogram. Patients were classified into low-, moderate-, and high-risk groups based on the nomogram scores, with the high-risk group showing significantly higher CSM rates after RFA compared to the other two groups.

CONCLUSIONS

We identified Grade, AFP, cirrhosis, tumor size, and tumor number as independent risk factors associated with CSM. The competing risk nomogram exhibited high performance in predicting the probability of CSM for HCC patients undergoing RFA.

Radiomics of Preoperative Multi-Sequence Magnetic Resonance Imaging Can Improve the Predictive Performance of Microvascular Invasion in Hepatocellular Carcinoma

Background

The aim of the study is to demonstrate that radiomics of preoperative multi-sequence magnetic resonance imaging (MRI) can indeed improve the predictive performance of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods

A total of 206 patients with pathologically confirmed HCC who underwent preoperative enhanced MRI were retrospectively recruited. Univariate and multivariate logistic regression analysis identified the independent clinicoradiologic predictors of MVI present and constituted the clinicoradiologic model. Recursive feature elimination (RFE) was applied to select radiomics features (extracted from six sequence images) and constructed the radiomics model. Clinicoradiologic model plus radiomics model formed the clinicoradiomics model. Five-fold cross-validation was used to validate the three models. Discrimination, calibration, and clinical utility were used to evaluate the performance. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to compare the prediction accuracy between models.

Results

The clinicoradiologic model contained alpha-fetoprotein (AFP)_lg10, radiological capsule enhancement, enhancement pattern and arterial peritumoral enhancement, which were independent risk factors of MVI. There were 18 radiomics features related to MVI constructed the radiomics model. The mean area under the receiver operating curve (AUC) of clinicoradiologic, radiomics and clinicoradiomics model were 0.849, 0.925 and 0.950 in the training cohort and 0.846, 0.907 and 0.933 in the validation cohort, respectively. The three models' calibration curves fitted well, and decision curve analysis (DCA) confirmed the clinical usefulness. Compared with the clinicoradiologic model, the NRI of radiomics and clinicoradiomics model increased significantly by 0.575 and 0.825, respectively, and the IDI increased significantly by 0.280 and 0.398, respectively.

Conclusions

Radiomics of preoperative multi-sequence MRI can improve the predictive performance of MVI in HCC.

Grading severity of microscopic vascular invasion was independently associated with recurrence and survival following hepatectomy for solitary hepatocellular carcinoma

Background

Hepatectomy is the preferred treatment for solitary hepatocellular carcinoma (HCC) without macrovascular invasion and distant metastasis, but long-term survival remains unsatisfactory in certain patients. We sought to identify whether the grading severity of microscopic vascular invasion (MVI) was associated with recurrence and survival among patients with solitary HCC.

Methods

Consecutive patients who underwent hepatectomy for solitary HCC were identified from a multicenter prospectively-collected database. Patients were categorized into three groups according to the MVI grading system proposed by the Liver Cancer Pathology Group of China: M0 (no MVI), M1 (1-5 sites of MVI occurring ≤1.0 cm away from the tumor), and M2 (>5 sites occurring ≤1.0 cm or any site occurring >1 cm away from the tumor). Recurrence-free survival (RFS) and overall survival (OS) were compared among the groups.

Results

Among 227 patients, 97 (42.7%), 83 (36.6%), and 47 (20.7%) patients had M0, M1, and M2, respectively. Median RFS rates among patients with M0, M1, and M2 were 38.3, 35.1, 11.6 months, respectively, while OS rates were 66.8, 62.3, 30.6 months, respectively (both P<0.001). Multivariate Cox-regression analyses demonstrated that both M1 and M2 were independent risk factors for RFS (hazard ratio 1.20, 95% CI: 1.03-1.89, P=0.040; and hazard ratio 1.67, 95% CI: 1.06-2.64, P=0.027) and OS (hazard ratio 1.28, 95% CI: 1.05-2.07, P=0.035; and hazard ratio 1.97, 95% CI: 1.15-3.38, P=0.013).

Conclusions

Grading severity of MVI was independently associated with RFS and OS after hepatectomy for solitary HCC. Enhanced surveillance for recurrence and potentially adjuvant therapy may be considered for patients with MVI, especially individuals with more severe MVI grading (M2).

Nomogram based on preoperative clinical and MRI features to estimate the microvascular invasion status and the prognosis of solitary intrahepatic mass-forming cholangiocarcinoma

PURPOSE

To develop a nomogram based on preoperative clinical and magnetic resonance imaging (MRI) features for the microvascular invasion (MVI) status in solitary intrahepatic mass-forming cholangiocarcinoma (sIMCC) and to evaluate whether it could predict recurrence-free survival (RFS).

METHODS

We included 115 cases who experienced MRI examinations for sIMCC with R0 resection. The preoperative clinical and MRI features were extracted. Independent predictors related to MVI+ were evaluated by stepwise multivariate logistic regression, and a nomogram was constructed. A receiver operating characteristic (ROC) curve was used to assess the predictive ability. All patients were classified into high- and low-risk groups of MVI. Then, the correlations of the nomogram with RFS in patents with sIMCC were analyzed by Kaplan-Meier method.

RESULTS

The occurrence rate of MVI+ was 38.3% (44/115). The preoperative independent predictors of MVI+ were carbohydrate antigen 19-9 > 37 U/ml, tumor size > 5 cm, and an ill-defined tumor boundary. Integrating these predictors, the nomogram exerted a favorable diagnostic performance with areas under the ROC curve of 0.767 (95% confidence interval [CI] 0.654-0.881) in the development cohort, and 0.760 (95% CI 0.591-0.929) in the validation cohort. In the RFS analysis, significant differences were observed between the high- and low-risk MVI groups (6-month RFS rates: 64.5% vs. 78.8% and 46.7% vs. 82.4% in the development and validation cohorts, respectively) (P < 0.05).

CONCLUSIONS

A nomogram based on clinical and MRI features is a potential biomarker of MVI and may be a potent method to classify the risk of recurrence in patients with sIMCC.

Microvascular Invasion in Hepatocellular Carcinoma: Some Puzzling Facets

BACKGROUND/AIMS

Hepatocellular carcinoma is the main type of primary liver cancer. Macroscopic vascular invasion is usually identified during imaging, whereas microvascular invasion is usually determined by histopathological evaluation. We aim to identify the association between microvascular invasion and other markers of tumor aggressiveness and to identify the role of microvascular invasion in the prognosis of patients who were treated by liver transplantation for hepatocellular carcinoma.

MATERIALS AND METHODS

This is a single-center retrospective analysis of prospectively collected data. Patients who received liver transplantation for hepatocellular carcinoma were included in the study. Data were collected regarding sociodemographic variables, criteria of selection for liver transplantation, pretransplant alpha-fetoprotein, presence or absence of microvascular invasion, presence or absence of recurrence, overall survival, and disease-free survival. Data were analyzed using Statistical Package for the Social Sciences.

RESULTS

Sociodemographic laboratory values and radiologic tumor characteristics were found to be similar in patients with or without microvascular invasion. Our study revealed that microvascular invasion is associated with increased recurrence, decreased diseasedfree survival, and decreased overall survival, only for patients with hepatocellular carcinoma beyond Milan criteria at the time of liver transplantation.

CONCLUSION

For patients beyond Milan criteria, but not within Milan criteria, microvascular invasion plays a significant role in predicting recurrence and shorter survival after liver transplantation.

A Grading System of Microvascular Invasion for Patients with Hepatocellular Carcinoma Undergoing Liver Resection with Curative Intent: A Multicenter Study

Background

Microvascular invasion (MVI) is closely correlated with poor clinical outcomes in patients with hepatocellular carcinoma (HCC). A grading system of MVI is needed to assist in the management of HCC patient.

Methods

Multicenter data of HCC patients who underwent liver resection with curative intent was analyzed. This grading system was established by detected number and distance from tumor boundary of MVI. Survival outcomes were compared among patients in each group. This system was verified by time-receiver operating characteristic curve, time-area under the curve, calibration curve, and decision curve analyses. Cox regression analysis was performed to study the associated factors of prognosis. Logistic analysis was used to study the predictive factors of MVI.

Results

All patients were classified into 4 groups: M0: no MVI; M1: 1~5 proximal MVIs (≤1 cm from tumor boundary); M2a: >5 proximal MVIs (≤1 cm from tumor boundary); M2b: ≥1 distal MVIs (>1 cm from tumor boundary). The recurrence-free survival (RFS), overall survival (OS), and early RFS rates among all the individual groups were significantly different. Based on the number of proximal MVI (0~5 vs >5), patients in the M2b group were further divided into two subgroups which also showed different prognosis. Multiple methods showed this grading system to be significantly better than the MVI two-tiered system in prognostic evaluation. Four multivariate models for RFS, OS, early RFS, late RFS, and a predictive model of MVI were then established and were shown to satisfactorily evaluate prognosis and have a great discriminatory power, respectively.

Conclusion

This MVI grading system could precisely evaluate prognosis of HCC patients after liver resection with curative intent and it could be employed in routine pathological reports. The severity of MVI from both adjacent and distant from tumor boundary should be stated. A hypothesis about two occurrence modes of distal MVI was proposed.

Prognostic Value of Combined Neutrophil-to-Lymphocyte Ratio and Imaging Tumor Capsule in Solitary Hepatocellular Carcinoma Patients after Narrow-Margin Hepatectomy

BACKGROUND

The study aimed to investigate the clinical value and prognostic patterns of the neutrophil-to-lymphocyte ratio (NLR) and imaging tumor capsule (ITC) in solitary hepatocellular carcinoma (HCC) patients undergoing narrow-margin hepatectomy.

METHODS

Data for solitary HCC patients treated with narrow-margin surgery were extracted from Shanghai General Hospital. Clinical features of recurrence-free survival (RFS), overall survival (OS), and early recurrence were investigated by Cox/logistic regression. The significant variables were subsequently incorporated into the nomogram pattern. Survival analysis stratified by NLR and ITC was also performed.

RESULTS

The study included a cohort of 222 patients, with median RFS and OS of 24.083 and 32.283 months, respectively. Both an NLR ≥ 2.80 and incomplete ITC had a significant impact on prognosis. NLR and ITC independently affected RFS and OS, whereas alpha-fetoprotein (AFP) and ITC were identified as independent factors for early relapse. The RFS and OS nomogram, generated based on the Cox model, demonstrated good performance in validation. The combination of NLR and ITC showed greater predictive accuracy for 5-year RFS and OS. Subgroups with an NLR ≥ 2.80 and incomplete ITC had the worst prognosis.

CONCLUSIONS

Both NLR and ITC significantly affected RFS, OS, and early recurrence among solitary HCC patients who underwent narrow-margin hepatectomy. The combination of NLR and ITC has the potential to guide rational clinical treatment and determine the prognosis.

MRI-based radiomics signature: a potential imaging biomarker for prediction of microvascular invasion in combined hepatocellular-cholangiocarcinoma

PURPOSE

To investigate the potential of radiomics analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in preoperatively predicting microvascular invasion (MVI) in patients with combined hepatocellular-cholangiocarcinoma (cHCC-CC) before surgery.

METHODS

A cohort of 91 patients with histologically confirmed cHCC-CC who underwent preoperative liver DCE-MRI were enrolled and divided into a training cohort (27 MVI-positive and 37 MVI-negative) and a validation cohort (11 MVI-positive and 16 MVI-negative). Clinical characteristics and MR features of the patients were evaluated. Radiomics features were extracted from DCE-MRI, and a radiomics signature was built using the least absolute shrinkage and selection operator (LASSO) algorithm in the training cohort. Prediction performance of the developed radiomics signature was evaluated by utilizing the receiver operating characteristic (ROC) analysis.

RESULTS

Larger tumor size and higher Radscore were associated with the presence of MVI in the training cohort (p = 0.026 and < 0.001, respectively), and theses findings were also confirmed in the validation cohort (p = 0.040 and 0.001, respectively). The developed radiomics signature, composed of 4 stable radiomics features, showed high prediction performance in both the training cohort (AUC = 0.866, 95% CI 0.757-0.938, p < 0.001) and validation cohort (AUC = 0.841, 95% CI 0.650-0.952, p < 0.001).

CONCLUSIONS

The radiomics signature developed from DCE-MRI can be a reliable imaging biomarker to preoperatively predict MVI in cHCC-CC.

Impact of Hepatocellular Carcinoma Tumor Size on Sonazoid Contrast-Enhanced Ultrasound Enhancement Features

OBJECTIVE

The aim of the work described here was to evaluate the impact of hepatocellular carcinoma (HCC) tumor size on Sonazoid contrast-enhanced ultrasound (CEUS) enhancement features, especially in tumors with diameters ≤30 mm and <10 mm.

METHODS

In this retrospective study, we included patients with histopathologically confirmed HCC lesions and divided them into three groups on the basis of tumor size. All patients underwent Sonazoid-enhanced CEUS examinations before surgery. B-mode ultrasound (BMUS) features and CEUS enhancement patterns were evaluated according to current World Federation for Ultrasound in Medicine and Biology Guidelines criteria. The χ2- and Student t-tests were used to compare differences between groups.

RESULTS

We included 132 patients with histopathologically confirmed HCC lesions from November 2020 to September 2022. On the basis of tumor size, patients were divided into group 1 (<10 mm, n = 5), group 2 (10-30 mm, n = 54) and group 3 (>30 mm, n = 73). On BMUS, most HCCs appeared heterogeneous but predominantly hypo-echoic (61.4%, 81/132) with ill-defined margins and irregular shapes. Meanwhile, iso-echoic features were more common in small HCCs ≤30 mm (15.3%, 9/59), but a mixed hyper- and hypo-echoic appearance was more common in HCCs >30 mm (17.8%, 13/73) (p = 0.003). On Sonazoid-enhanced CEUS, all HCCs presented arterial phase hyperenhancement (APHE) (100.0%, 132/132). Most HCCs >30 mm exhibited heterogeneous hyperenhancement (86.3%, 63/73), whereas nearly one-third of small HCCs ≤30 mm exhibited homogeneous hyperenhancement (35.6%, 21/59) (p = 0.003). In the portal venous phase, there was a significantly higher proportion of washout in HCCs >30 mm (84.9%, 62/73) than in small HCCs ≤30 mm (64.4%, 38/59) (p = 0.006). During the Kupffer phase, 11 additional hypo-enhanced lesions (mean size: 14.1 ± 4.1 mm, iso-echoic on BMUS), which were also suspected to be HCC lesions, were detected in 5 patients with small HCCs ≤30 mm and 4 patients with HCCs >30 mm. All 5 cases of HCCs <10 mm exhibited APHE and late washout (>60 s). The majority (3/5, 60%) exhibited washout in the portal venous phase (70, 74 and 75 s), one case did so in the late phase (125 s) and another in the Kupffer phase (420 s).

CONCLUSION

Tumor size had a significant impact on the washout features of HCC lesions on Sonazoid-enhanced CEUS. Small HCC lesions ≤30 mm had a higher proportion of relatively late washout in comparison to larger lesions. Sonazoid-enhanced CEUS might be helpful in the detection and characterization of HCC lesions <10 mm.

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.

Serum immune biomarker levels combined with hepatitis B virus infection status predict early recurrence of early-stage hepatocellular carcinoma with microvascular invasion after liver resection

INTRODUCTION

The tumor immune response plays a vital role in cancer recurrence in patients with malignancies. We aim to clarify the risk factors for early recurrence and investigate the efficacy of blood-based biomarkers to predict the risk of early recurrence in early-stage hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) after hepatectomy.

MATERIALS AND METHODS

A total of 101 cases of HCC with MVI who underwent liver resection were enrolled. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors of early recurrence. We calculated the area under the receiver operating characteristic curve to evaluate the performance of the four biomarkers identified as risk factors for early recurrence.

RESULTS

Multiple logistic regression analysis indicated that complement (C)4, cluster of differentiation (CD)4+, immunoglobulin A (IgA), and hepatitis B virus (HBV) DNA of greater than 500 IU/mL were correlated with early recurrence of HCC. The area under the curve was greater for the combination model than for the HBV DNA, CD4+, IgA, or C4 models alone.

CONCLUSION

Preoperative serum CD4+, C4, IgA, and HBV DNA levels were linked with early recurrence of early-stage HCC with MVI and the combination model was of considerable predictive value for the prognosis of HCC with MVI.

Hypoxia-induced circ-CDYL-EEF1A2 transcriptional complex drives lung metastasis of cancer stem cells from hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is often associated with poor outcomes due to lung metastasis. ICAM-1+ circulating tumor cells, termed circulating cancer stem cells (CCSCs), possess stem cell-like characteristics. However, it is still unexplored how their presence indicates lung metastasis tendency, and particularly, what mechanism drives their lung metastasis. Here, we demonstrated that a preoperative CCSC count in 5 mL of blood (CCSC5) of >3 was a risk factor for lung metastasis in clinical HCC patients. The CSCs overexpressed with circ-CDYL entered the bloodstream and developed lung metastases in mice. Mechanistically, circ-CDYL promoted COL14A1 expression and thus ERK signaling to facilitate epithelial-mesenchymal transition. Furthermore, we uncovered that an RNA-binding protein, EEF1A2, acted as a novel transcriptional (co-) factor to cooperate with circ-CDYL and initiate COL14A1 transcription. A high circ-CDYL level is caused by HIF-1⍺-mediated transcriptional upregulation of its parental gene CDYL and splicing factor EIF4A3 under a hypoxia microenvironment. Hence, the hypoxia microenvironment enables the high-tendency lung metastasis of ICAM-1+ CCSCs through the HIF-1⍺/circ-CDYL-EEF1A2/COL14A1 axis, potentially allowing clinicians to preoperatively detect ICAM-1+ CCSCs as a real-time biomarker for precisely deciding HCC treatment strategies.

An MRI-Based Prognostic Stratification System for Medical Decision-Making of Multinodular Hepatocellular Carcinoma Patients Beyond the Milan Criteria

BACKGROUND

The suitability of hepatectomy among patients with multinodular hepatocellular carcinoma (MHCC) beyond the Milan criteria remains controversial. There is a need for a reliable risk stratification tool among these patients for the selection of ideal candidates of curative resection.

PURPOSE

To determine the clinicoradiological prognostic factors for patients with MHCC beyond the Milan criteria to further develop a stratification system.

STUDY TYPE

Retrospective.

SUBJECTS

176 patients with pathologically confirmed MHCC beyond the Milan criteria.

FIELD STRENGTH/SEQUENCE

The 1.5 T scanner, including T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging.

ASSESSMENT

Conventional MRI features and preoperative laboratory data including aspartate aminotransferase (AST) and α-fetoprotein (AFP) were collected and analyzed. Two nomograms incorporating clinicoradiological variables were independently constructed to predict recurrence-free survival (RFS) and overall survival (OS) with Cox regression analyses and verified with 5-fold cross validation. Based on the nomograms, two prognostic stratification systems for RFS and OS were further developed.

STATISTICAL TESTS

The Cohen's kappa/intraclass correlation coefficient, C-index, calibration curve, Kaplan-Meier curve, log-rank test. A P value <0.05 was considered statistically significant.

RESULTS

AST > 40 U/L, increased tumor burden score, radiological liver cirrhosis and nonsmooth tumor margin were independent predictors for poor RFS, while AST > 40 U/L, AFP > 400 ng/mL and radiological liver cirrhosis were independent predictors for poor OS. The two nomograms demonstrated good discrimination performance with C-index of 0.653 (95% confidence interval [CI], 0.602-0.794) and 0.685 (95% CI, 0.623-0.747) for RFS and OS, respectively. The 5-fold cross validation further validated the discrimination capability of the nomograms. Based on the nomogram models, MHCC patients beyond the Milan criteria were stratified into low-/medium-/high-risk groups with significantly different RFS and OS.

DATA CONCLUSION

The proposed MRI-based prognostic stratification system facilitates the refinement and further subclassification of patients with MHCC beyond the Milan criteria.

EVIDENCE LEVEL

4.

TECHNICAL EFFICACY

2.