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Objectives: To predict microvascular invasion (MVI) status and tumor grading of hepatocellular carcinoma (HCC) by evaluating preoperative non-radiomics ultrasound and contrast-enhanced ultrasound (US-CEUS) features and determine the influences of MVI/tumor grading on the category of CEUS LI-RADS for HCC., Methods: A total of 506 HCC patients who underwent preoperative US-CEUS examinations from 8 hospitals between July 2020 and June 2023 were enrolled. According to the MVI status, all the patients were classified, and HCC differentiation was assessed by using Edmondson-Steiner (ES) grading: MVI-negative (M0) and low-grade ES (GI/II) (MN-L, n = 297) and MVI-positive (M1/M2) and/or high-grade ES (GIII/IV) (MP-H, n = 209). Stratified analysis was performed based on fibrosis stage and tumor size., Results: The results proved that MN-L HCC was more frequently classified into the LR-5 category (p = 0.034), while MP-H HCC was more frequently classified into the LR-TIV (p = 0.010). The heterogeneously arterial phase hyperenhancement (APHE) is significantly correlated with MVI(+)/high grade-ES (p = 0.003). Compared with MN-L HCC, the onset of washout was earlier, washout rate was higher, and tumor-invasion border was larger (all p < 0.01) in MP-H HCC. In addition, fibrosis stage and tumor size significantly influenced the onset of washout and washout rate of HCC (all p < 0.01). The tumor-invasion border was only positively correlated with tumor size (p < 0.001) rather than fibrosis stage (p > 0.05)., Conclusions: MVI status and tumor grading influence the classification of LR-5 and LR-TIV. Heterogeneous APHE, higher washout rate, earlier onset of washout (≤65 s), larger tumor-invasion border (≥3 mm) and higher alpha fetoprotein level indicate the presence of MVI and/or high-grade ES., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To develop and validate a preoperative prediction model based on multimodal ultrasound and biochemical indicator for identifying microvascular invasion (MVI) in patients with a single hepatocellular carcinoma (HCC) ≤ 5 cm., Methods: From May 2022 to November 2023, a total of 318 patients with pathologically confirmed single HCC ≤ 5 cm from three institutions were enrolled. All of them underwent preoperative biochemical, conventional ultrasound (US), and contrast-enhanced ultrasound (CEUS) (Sonazoid, 0.6 mL, bolus injection) examinations. Univariate and multivariate logistic regression analyses on clinical information, biochemical indicator, and US imaging features were performed in the training set to seek independent predictors for MVI-positive. The models were constructed and evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis in both validation and test sets. Subgroup analyses in patients with different liver background and tumor sizes were conducted to further investigate the model's performance., Results: Logistic regression analyses showed that obscure tumor boundary in B-mode US, intra-tumoral artery in pulsed-wave Doppler US, complete Kupffer-phase agent clearance in Sonazoid-CEUS, and biomedical indicator PIVKA-II were independently correlated with MVI-positive. The combined model comprising all predictors showed the highest AUC, which were 0.937 and 0.893 in the validation and test sets. Good calibration and prominent net benefit were achieved in both sets. No significant difference was found in subgroup analyses., Conclusions: The combination of biochemical indicator, conventional US, and Sonazoid-CEUS features could help preoperative MVI prediction in patients with a single HCC ≤ 5 cm., Critical Relevance Statement: Investigation of imaging features in conventional US, Sonazoid-CEUS, and biochemical indicators showed a significant relation with MVI-positivity in patients with a single HCC ≤ 5 cm, allowing the construction of a model for preoperative prediction of MVI status to help treatment decision making., Key Points: MVI status is important for patients with a single HCC ≤ 5 cm. The model based on conventional US, Sonazoid-CEUS and PIVKA-II performs best for MVI prediction. The combined model has potential for preoperative prediction of MVI status., (© 2024. The Author(s).)

Purpose: This study aimed to develop two preoperative magnetic resonance imaging (MRI) based models for detecting and classifying microvascular invasion (MVI) in early-stage small hepatocellular carcinoma (sHCC) patients., Methods: MVI is graded as M0 (no invasion), M1 (invasion of five or fewer vessels located within 1 cm of the tumor's peritumoral region), and M2 (invasion of more than five vessels or those located more than 1 cm from the tumor's surface). This study enrolled 395 early-stage sHCC (≤ 3 cm) patients from three centers who underwent preoperative gadopentetate-enhanced MRI. From the first two centers, 310 patients were randomly divided into training (n = 217) and validation (n = 93) cohorts in a 7:3 ratio to develop the first model for predicting MVI presence. Among these, 153 patients with identified MVI were further divided into training (n = 112) and validation (n = 41) cohorts, using the same ratio, to construct the second model for MVI classification. An independent test cohort of 85 patients from the third center to validate both models. Univariate and multivariate logistic regression analyses identified independent predictors of MVI and its classification in the training cohorts. Based on these predictors, two nomograms were developed and assessed for their discriminative ability, calibration, and clinical usefulness. Besides, considering the two models are supposed applied in a serial fashion in the real clinical setting, we evaluate the performance of the two models together on the test cohorts by applying them simultaneously. Kaplan-Meier survival curve analysis was employed to assess the correlation between predicted MVI status and early recurrence, similar to the association observed with actual MVI status and early recurrence., Results: The MVI detection nomogram, with platelet count (PLT), activated partial thromboplastin time (APTT), rim arterial phase hyperenhancement (Rim APHE) and arterial peritumoral enhancement, achieved area under the curve (AUC) of 0.827, 0.761 and 0.798 in the training, validation, and test cohorts, respectively. The MVI classification nomogram, integrating Total protein (TP), Shape, Arterial peritumoral enhancement and enhancement pattern, achieved AUC of 0.824, 0.772, and 0.807 across the three cohorts. When the two models were applied on the test cohorts in a serial fashion, they both demonstrated good performance, which means the two models had good clinical applicability. Calibration and decision curve analysis (DCA) results affirmed the model's reliability and clinical utility. Notably, early recurrence was more prevalent in the MVI grade 2 (M2) group compared to the MVI-absent and M1 groups, regardless of the actual or predicted MVI status., Conclusions: The nomograms exhibited excellent predictive performance for detecting and classifying MVI in patients with early-stage sHCC, particularly identifying high-risk M2 patients preoperatively., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objectives: To explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI)., Methods: A total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC)., Results: The XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80., Conclusion: Compared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted., Clinical Relevance Statement: The 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region., Key Points: We investigated tumor and different peritumoral regions, as well as their fusion. MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region. The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI., (© 2024. The Author(s).)

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., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: To construct a combined model based on bi-regional quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), as well as clinical-radiological (CR) features for predicting microvascular invasion (MVI) in solitary Barcelona Clinic Liver Cancer (BCLC) stage A hepatocellular carcinoma (HCC), and to assess its ability for stratifying the risk of recurrence after hepatectomy., Methods: Patients with solitary BCLC stage A HCC were prospective collected and randomly divided into training and validation sets. DCE perfusion parameters were obtained both in intra-tumoral region (ITR) and peritumoral region (PTR). Combined DCE perfusion parameters (C DCE ) were constructed to predict MVI. The combined model incorporating C DCE and CR features was developed and evaluated. Kaplan-Meier method was used to investigate the prognostic significance of the model and the survival benefits of different hepatectomy approaches., Results: A total of 133 patients were included. Total blood flow in ITR and arterial fraction in PTR exhibited the best predictive performance for MVI with areas under the curve (AUCs) of 0.790 and 0.792, respectively. C DCE achieved AUCs of 0.868 (training set) and 0.857 (validation set). A combined model integrated with the α-fetoprotein, corona enhancement, two-trait predictor of venous invasion, and C DCE could improve the discrimination ability to AUCs of 0.966 (training set) and 0.937 (validation set). The combined model could stratify the prognosis of HCC patients. Anatomical resection was associated with a better prognosis in the high-risk group (p < 0.05)., Conclusion: The combined model integrating DCE perfusion parameters and CR features could be used for MVI prediction in HCC patients and assist clinical decision-making., Critical Relevance Statement: The combined model incorporating bi-regional DCE-MRI perfusion parameters and CR features predicted MVI preoperatively, which could stratify the risk of recurrence and aid in optimizing treatment strategies., Key Points: Microvascular invasion (MVI) is a significant predictor of prognosis for hepatocellular carcinoma (HCC). Quantitative DCE-MRI could predict MVI in solitary BCLC stage A HCC; the combined model improved performance. The combined model could help stratify the risk of recurrence and aid treatment planning., (© 2024. The Author(s).)

Objectives: Impeded diffusion fraction (IDF) is a novel and promising diffusion-weighted imaging (DWI) technique that allows for the detection of various diffusion compartments, including macromolecular coordinated water, free diffusion, perfusion, and cellular free water. This study aims to investigate the clinical potential of IDF-DWI in detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC)., Methods: 66 patients were prospectively included. Metrics derived from IDF-DWI and the apparent diffusion coefficient (ADC) were calculated. Multivariate logistic regression was employed to identify clinical risk factors. Diagnostic performance was evaluated using the area under the receiver operating characteristics curve (AUC-ROC), the area under the precision-recall curve (AUC-PR), and the calibration error (cal-error). Additionally, a power analysis was conducted to determine the required sample size., Results: The results suggested a significantly higher fraction of impeded diffusion (F ID ) originating from IDF-DWI in MVI-positive HCCs (p < 0.001). Moreover, the ADC was found to be significantly lower in MVI-positive HCCs (p = 0.019). Independent risk factors of MVI included larger tumor size and elevated alpha-fetoprotein (AFP) levels. The nomogram model incorporating ADC, F ID , tumor size, and AFP level yielded the highest diagnostic accuracy for MVI (AUC-PR = 0.804, AUC-ROC = 0.783, cal-error = 0.044), followed by F ID (AUC-PR = 0.693, AUC-ROC = 0.760, cal-error = 0.060) and ADC (AUC-PR = 0.570, AUC-ROC = 0.651, cal-error = 0.164)., Conclusion: IDF-DWI shows great potential in noninvasively, accurately, and preoperatively detecting MVI in HCC and may offer clinical benefits for prognostic prediction and determination of treatment strategy., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: Microvascular invasion (MVI) is a critical factor in predicting the recurrence and prognosis of hepatocellular carcinoma (HCC) after liver transplantation (LT). However, there is a lack of reliable preoperative predictors for MVI. The purpose of this study is to evaluate the potential of an 18 F-FDG PET/CT-based nomogram in predicting MVI before LT for HCC., Methods: 83 HCC patients who obtained 18 F-FDG PET/CT before LT were included in this retrospective research. To determine the parameters connected to MVI and to create a nomogram for MVI prediction, respectively, Logistic and Cox regression models were applied. Analyses of the calibration curve and receiver operating characteristic (ROC) curves were used to assess the model's capability to differentiate between clinical factors and metabolic data from PET/CT images., Results: Among the 83 patients analyzed, 41% were diagnosed with histologic MVI. Multivariate logistic regression analysis revealed that Child-Pugh stage, alpha-fetoprotein, number of tumors, CT Dmax, and Tumor-to-normal liver uptake ratio (TLR) were significant predictors of MVI. A nomogram was constructed using these predictors, which demonstrated strong calibration with a close agreement between predicted and actual MVI probabilities. The nomogram also showed excellent differentiation with an AUC of 0.965 (95% CI 0.925-1.000)., Conclusion: The nomogram based on 18 F-FDG PET/CT metabolic characteristics is a reliable preoperative imaging biomarker for predicting MVI in HCC patients before undergoing LT. It has demonstrated excellent efficacy and high clinical applicability., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: Varying diffusion curvature (VDC) MRI is an emerging diffusion-weighted imaging (DWI) technique that can capture non-Gaussian diffusion behavior and reflect tissue heterogeneity. However, its clinical utility has hardly been evaluated. We aimed to investigate the value of the VDC technique in noninvasively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC)., Methods: 74 patients with HCCs, including 39 MVI-positive and 35 MVI-negative HCCs were included into this prospective study. Quantitative metrics between subgroups, clinical risk factors, as well as diagnostic performance were evaluated. The power analysis was also carried out to determine the statistical power., Results: MVI-positive HCCs exhibited significantly higher VDC-derived structural heterogeneity measure, D 1 (0.680 ± 0.100 × 10 -3 vs 0.572 ± 0.148 × 10 -3  mm 2 /s, p = 0.001) and lower apparent diffusion coefficient (ADC) (1.350 ± 0.166 × 10 -3 vs 1.471 ± 0.322 × 10 -3  mm 2 /s, p = 0.0495) compared to MVI-negative HCCs. No statistical significance was observed for VDC-derived diffusion coefficient, D 0 between the subgroups (p = 0.562). Tumor size (odds ratio (OR) = 1.242) and alpha-fetoprotein (AFP) (OR = 2.527) were identified as risk factors for MVI. A predictive nomogram was constructed based on D 1 , ADC, tumor size, and AFP, which exhibited the highest diagnostic accuracy (AUC = 0.817), followed by D 1 (AUC = 0.753) and ADC (AUC = 0.647). The diagnostic performance of the nomogram-based model was also validated by the calibration curve and decision curve., Conclusion: VDC can aid in the noninvasive and preoperative diagnosis of HCC with MVI, which may result in the clinical benefit in terms of prognostic prediction and clinical decision-making., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: We assessed the predictive capacity of computed tomography (CT)-enhanced radiomics models in determining microvascular invasion (MVI) for isolated hepatocellular carcinoma (HCC) ≤ 5 cm within peritumoral margins of 5 and 10 mm., Methods: Radiomics software was used for feature extraction. We used the least absolute shrinkage and selection operator (LASSO) algorithm to establish an effective model to predict patients' preoperative MVI status., Results: The area under the curve (AUC) values in the validation sets for the 5- and 10-mm radiomics models concerning arterial tumors were 0.759 and 0.637, respectively. In the portal vein phase, they were 0.626 and 0.693, respectively. Additionally, the combined radiomics model for arterial tumors and the peritumoral 5-mm margin had an AUC value of 0.820. The decision curve showed that the combined tumor and peritumoral radiomics model exhibited a somewhat superior benefit compared to the traditional model, while the fusion model demonstrated an even greater advantage, indicating its significant potential in clinical application., Conclusion: The 5-mm peritumoral arterial model had superior accuracy and sensitivity in predicting MVI. Moreover, the combined tumor and peritumoral radiomics model outperformed both the individual tumor and peritumoral radiomics models. The most effective combination was the arterial phase tumor and peritumor 5-mm margin combination. Using a fusion model that integrates tumor and peritumoral radiomics and clinical data can aid in the preoperative diagnosis of the MVI of isolated HCC ≤ 5 cm, indicating considerable practical value., Critical Relevance Statement: The radiomics model including a 5-mm peritumoral expansion is a promising noninvasive biomarker for preoperatively predicting microvascular invasion in patients diagnosed with a solitary HCC ≤ 5 cm., Key Points: • Radiomics features extracted at a 5-mm distance from the tumor could better predict hepatocellular carcinoma microvascular invasion. • Peritumoral radiomics can be used to capture tumor heterogeneity and predict microvascular invasion. • This radiomics model stands as a promising noninvasive biomarker for preoperatively predicting MVI in individuals., (© 2024. The Author(s).)

Purpose: Microvascular invasion (MVI) is a significant prognostic factor in combined hepatocellular cholangiocarcinoma (cHCC-CCA). However, its diagnosis relies on postoperative histopathologic analysis. This study aims to identify preoperative inflammatory biomarkers and MR-imaging features that can predict MVI in cHCC-CCA., Methods: This retrospective study enrolled 119 patients with histopathologically confirmed cHCC-CCA between January 2016 and December 2021. Two radiologists, unaware of the clinical data, independently reviewed all MR image features. Univariable and multivariable analyses were performed to determine the independent predictors for MVI among inflammatory biomarkers and MRI characteristics. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic performance., Results: Multivariable logistic regression analysis identified four variables significantly associated with MVI (p < 0.05), including two inflammatory biomarkers [albumin-to-alkaline phosphatase ratio (AAPR) and aspartate aminotransferase-to-neutrophil ratio index (ANRI)] and two MRI features (non-smooth tumor margin and arterial phase peritumoral enhancement). A combined model for predicting MVI was constructed based on these four variables, with an AUC of 0.802 (95% CI 0.719-0.870). The diagnostic efficiency of the combined model was higher than that of the imaging model., Conclusion: Inflammatory biomarkers and MRI features could be potential predictors for MVI in cHCC-CCA. The combined model, derived from inflammatory biomarkers and MRI features, showed good performance in preoperatively predicting MVI in cHCC-CCA patients., (© 2023. The Author(s).)

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., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

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., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Relapse of hepatocellular carcinoma (HCC) due to vascular invasion is common, but the genomic mechanisms remain unclear, and molecular determinants of high-risk relapse cases are lacking. We aimed to reveal the evolutionary trajectory of microvascular invasion (MVI) and develop a predictive signature for relapse in HCC., Methods: Whole-exome sequencing was performed on tumor and peritumor tissues, portal vein tumor thrombus (PVTT), and circulating tumor DNA (ctDNA) to compare the genomic profiles between 5 HCC patients with MVI and 5 patients without MVI. We conducted an integrated analysis of exome and transcriptome to develop and validate a prognostic signature in two public cohorts and one cohort from Zhongshan Hospital, Fudan University., Results: Shared genomic landscapes and identical clonal origins among tumor, PVTT, and ctDNA were observed in MVI ( +) HCC, suggesting that genomic changes favoring metastasis occur at the primary tumor stage and are inherited in metastatic lesions and ctDNA. There was no clonal relatedness between the primary tumor and ctDNA in MVI ( - ) HCC. HCC had dynamic mutation alterations during MVI and exhibited genetic heterogeneity between primary and metastatic tumors, which can be comprehensively reflected by ctDNA. A relapse-related gene signature named RGS HCC was developed based on the significantly mutated genes associated with MVI and shown to be a robust classifier of HCC relapse., Conclusions: We characterized the genomic alterations during HCC vascular invasion and revealed a previously undescribed evolution pattern of ctDNA in HCC. A novel multiomics-based signature was developed to identify high-risk relapse populations., (© 2023. Asian Pacific Association for the Study of the Liver.)

Objective: To investigate the diagnostic value of early dynamic 18 F-FDG PET/CT(ED 18 F-FDG PET/CT) combined with conventional whole-body 18 F-FDG PET/CT(WB 18 F-FDG PET/CT) in hepatocellular carcinoma (HCC), as well as the difference of early dynamic blood flow parameters and maximum standardized uptake value (SUVmax) in HCC patients with/without liver cirrhosis or microvascular invasion (MVI)., Methods: Twenty-two consecutive patients (mean age 57.8 years) with 28 established HCC lesions (mean size 4.5 cm) underwent a blood flow study with an 18 F-FDG dynamic scan divided into 24 sequences of 5 s each and a standard PET/CT scan. On the ED PET/CT study, an experienced PET/CT physician obtained volumes of interest (VOIs) where three blood flow estimates (time to peak [TTP], blood flow [BF], and hepatic perfusion index [HPI]) were calculated. On the WB PET/CT study, a VOI was placed on the fused scan for each HCC and maximum standardized uptake value (SUVmax) was obtained. Comparison of blood flow estimates, SUVmax, and tumor/background ratio (TNR) was performed among HCCs with and without angioinvasion, as well as HCCs in cirrhotic and non-cirrhotic liver., Results: Compared with WB 18 F-FDG PET/CT alone, ED combined with WB 18 F-FDG PET/CT can significantly increase the detection rate of moderately differentiated and poorly differentiated HCCs (both P < 0.05). HPI was higher in HCCs in patients with liver cirrhosis than those without liver cirrhosis (P = 0.044). There was no significant difference in TTP, BF, SUVmax, or TNR between HCCs in patients with liver cirrhosis and those without liver cirrhosis. There was no significant difference in blood flow estimates or SUVmax in background liver parenchyma between patients with and those without cirrhosis. TTP was shorter in HCCs with MVI than without MVI (P = 0.046). There was no significant difference in BF, HPI, SUVmax, or TNR between HCCs with MVI and without MVI. There was no significant difference in blood flow estimates or SUVmax in background liver parenchyma between patients with and those without MVI., Conclusion: ED combined with WB 18 F-FDG PET/CT can significantly increase the detection rate of moderately differentiated and poorly differentiated HCCs. HPI was significantly higher in HCCs in patients with liver cirrhosis than those without liver cirrhosis. TTP was significantly shorter in HCCs with MVI than without MVI., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: The aim of this retrospective study was to develop and validate a preoperative nomogram for predicting microvascular invasion (MVI) in patients with intrahepatic mass-forming cholangiocarcinoma (IMCC) based on magnetic resonance imaging (MRI)., Methods: In this retrospective study, 224 consecutive patients with clinicopathologically confirmed IMCC were enrolled. Patients whose data were collected from February 2010 to December 2020 were randomly divided into the training (131 patients) and internal validation (51 patients) datasets. The data from January 2021 to November 2021 (42 patients) were allocated to the time-independent validation dataset. Univariate and multivariate forward logistic regression analyses were used to identify preoperative MRI features that were significantly related to MVI, which were then used to develop the nomogram. We used the area under the receiver operating characteristic curve (AUC) and calibration curve to evaluate the performance of the nomogram., Results: Interobserver agreement of MRI qualitative features was good to excellent, with κ values of 0.613-0.882. Multivariate analyses indicated that the following variables were independent predictors of MVI: multiple tumours (odds ratio [OR]) = 4.819, 95% confidence interval [CI] 1.562-14.864, P = 0.006), ill-defined margin (OR = 6.922, 95% CI 2.883-16.633, P < 0.001), and carbohydrate antigen 19-9 (CA 19-9) > 37 U/ml (OR = 2.890, 95% CI 1.211-6.897, P = 0.017). A nomogram incorporating these factors was established using well-fitted calibration curves. The nomogram showed good diagnostic efficacy for MVI, with AUC values of 0.838, 0.819, and 0.874 for the training, internal validation, and time-independent validation datasets, respectively., Conclusion: A nomogram constructed using independent factors, namely the presence of multiple tumours, ill-defined margins, and CA 19-9 > 37 U/ml could predict the presence of MVI. This can facilitate personalised therapeutic strategy and clinical management in patients with IMCC., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: This study aimed to analyze imaging features based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the identification of vessels encapsulating tumor clusters (VETC)-microvascular invasion (MVI) in hepatocellular carcinoma (HCC), VM-HCC pattern., Methods: Patients who underwent hepatectomy and preoperative DCE-MRI between January 2015 and March 2021 were retrospectively analyzed. Clinical and imaging features related to VM-HCC (VETC + /MVI-, VETC-/MVI +, VETC + /MVI +) and Non-VM-HCC (VETC-/MVI-) were determined by multivariable logistic regression analyses. Early and overall recurrence were determined using the Kaplan-Meier survival curve. Indicators of early and overall recurrence were identified using the Cox proportional hazard regression model., Results: In total, 221 patients (177 men, 44 women; median age, 60 years; interquartile range, 52-66 years) were evaluated. The multivariable logistic regression analyses revealed fetoprotein > 400 ng/mL (odds ratio [OR] = 2.17, 95% confidence interval [CI] 1.07, 4.41, p = 0.033), intratumor vascularity (OR 2.15, 95% CI 1.07, 4.31, p = 0.031), and enhancement pattern (OR 2.71, 95% CI 1.17, 6.03, p = 0.019) as independent predictors of VM-HCC. In Kaplan-Meier survival analysis, intratumor vascularity was associated with early and overall recurrence (p < 0.05)., Conclusion: Based on DCE-MRI, intratumor vascularity can be used to characterize VM-HCC and is of prognostic significance for recurrence in patients with HCC., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: Microvascular invasion (MVI) is a known risk factor for prognosis after R0 liver resection for hepatocellular carcinoma (HCC). The aim of this study was to develop a deep learning prognostic prediction model by incorporating a new factor of MVI area to the other independent risk factors., Methods: Consecutive patients with HCC who underwent R0 liver resection from January to December 2016 at the Eastern Hepatobiliary Surgery Hospital were included in this retrospective study. For patients with MVI detected on resected specimens, they were divided into two groups according to the size of the maximal MVI area: the small-MVI group and the large-MVI group., Results: Of 193 patients who had MVI in the 337 HCC patients, 130 patients formed the training cohort and 63 patients formed the validation cohort. The large-MVI group of patients had worse overall survival (OS) when compared with the small-MVI group (p = 0.009). A deep learning model was developed based on the following independent risk factors found in this study: MVI stage, maximal MVI area, presence/absence of cirrhosis, and maximal tumor diameter. The areas under the receiver operating characteristic of the deep learning model for the 1-, 3-, and 5-year predictions of OS were 80.65, 74.04, and 79.44, respectively, which outperformed the traditional COX proportional hazards model., Conclusion: The deep learning model, by incorporating the maximal MVI area as an additional prognostic factor to the other previously known independent risk factors, predicted more accurately postoperative long-term OS for HCC patients with MVI after R0 liver resection., (© 2022. Asian Pacific Association for the Study of the Liver.)

Purpose: To analyze the long-term oncological outcomes of Barcelona Clinic Liver Cancer (BCLC) stages 0-A hepatocellular carcinoma (HCC) patients associated with or without microvascular invasion (MVI) treated with laparoscopic versus laparotomic liver resection., Methods: Clinicopathological data of HCC patients with BCLC stages 0-A from four medical centers were retrospectively reviewed. The survival outcomes of patients who underwent laparoscopic hepatectomy were compared with those who underwent laparotomic hepatectomy. Subgroup analyses in terms of MVI were further performed to explore the effect of surgical approaches on the long-term survival outcomes. Propensity score matching (PSM) analysis was used to match patients between the laparoscopic and laparotomic resection groups in a 1:1 ratio., Results: 495 HCC patients at BCLC stages 0-A were enrolled, including 243 in the laparoscopic resection group and 252 in the laparotomic resection group. Laparoscopic resection group had a shorter operation time, less blood loss, a lower frequency of blood transfusion and postoperative complication rates. The laparoscopic resection group had a significantly better overall survival (OS) and recurrence-free survival (RFS) than the laparotomic resection group before and after PSM. Subgroup analysis demonstrated that OS and RFS of patients without MVI were remarkably better in the laparoscopic resection group compared with the laparotomic resection group. However, no significant differences in OS and RFS between the two groups were found in patients with MVI after PSM., Conclusions: Pure laparoscopic hepatectomy for patients with BCLC stages 0-A HCC can be performed safely with favorable perioperative and long-term oncological outcomes at high-volume liver cancer centers, regardless of the presence of MVI., (© 2022. Asian Pacific Association for the Study of the Liver.)

Purpose: Evaluation of perfusion CT and dual-energy CT (DECT) quantitative parameters for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) prior to surgery., Methods: This prospective single-center study included fifty-six patients (44 men; median age 67; range 31-84) who provided written informed consent. Inclusion criteria were (1) treatment-naïve patients with a diagnosis of HCC, (2) an indication for hepatic resection, and (3) available arterial DECT phase and perfusion CT (GE revolution HD-GSI). Iodine concentrations (IC), arterial density (AD), and 9 quantitative perfusion parameters for HCC were correlated to pathological results. Radiological parameters based principal component analysis (PCA), corroborated by unsupervised heatmap classification, was meant to deliver a model for predicting MVI in HCC. Survival analysis was performed using univariable log-rank test and multivariable Cox model, both censored at time of relapse., Results: 58 HCC lesions were analyzed (median size 42.3 mm; range of 20-140). PCA showed that the radiological model was predictive of tumor grade (p = 0.01), intratumoral MVI (p = 0.004), peritumoral MVI (p = 0.04), MTM (macrotrabecular-massive) subtype (p = 0.02), and capsular invasion (p = 0.02) in HCC. Heatmap classification of HCC showed tumor heterogeneity, stratified into three main clusters according to the risk of relapse. Survival analysis confirmed that permeability surface-area product (PS) was the only significant independent parameter, among all quantitative tumoral CT parameters, for predicting a risk of relapse (Cox p value = 0.004)., Conclusion: A perfusion CT and DECT-based quantitative imaging profile can provide a diagnosis of histological MVI in HCC. PS is an independent parameter for relapse., Clinical Trials: ClinicalTrials.gov: NCT03754192., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies., Methods: Patients with a single HCC of 2-5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop (n = 230) and test (n = 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR (n = 118) and NAR (n = 85) via propensity score matching using patient data from another 2 centers for external validation., Results: The CRR model showed higher area under the curve values (0.835-0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796-0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group (P = 0.005) but not in the clinico-radiologic model predicted high-risk MVI group (P = 0.31)., Conclusions: The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR., (© 2022. Society of Surgical Oncology.)

Purpose: To investigate whether systemic inflammatory biomarkers compared with the imaging features interpreted by radiologists can offer complementary value for predicting the risk of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC)., Methods: A total of 156 patients with histologically confirmed HCC between Jan 2018 and Dec 2020 were retrospectively enrolled in the primary cohort. Preoperative clinical-inflammatory biomarkers and MR imaging of the patients were recorded and then evaluated as an inflammatory score (Inflam-score) and imaging feature score (Radio-score). Six Inflam-scores and 12 Radio-scores were determined from each patient by univariate analysis. Logistic regression was performed to select risk factors for MVI and establish a predictive nomogram. Decision curve analysis was applied to estimate the incremental value of the Inflam-score to the Radio-score for predicting MVI., Results: Four Radio-scores and 2 Inflam-scores, namely, larger tumor size, non-smooth tumor margin, presence of satellite nodules, presence of peritumoral enhance, higher neutrophil-lymphocyte ratio (NLR), and lower prognostic nutritional index (PNI), were significantly associated with MVI (p < 0.05). An MVI risk prediction nomogram was then constructed with an area under the curve (AUC) of 0.868 (95% CI 0.806-0.931). Adding Inflam-scores to Radio-scores improved the sensitivity of the model from 60.9 to 80.4% in receiver operating characteristic (ROC) curve analysis and led to a net benefit in decision curve analysis., Conclusion: Systemic inflammatory biomarkers are complementary tools that provide additional benefit to conventional imaging estimation for predicting MVI in HCC patients., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Microvascular invasion (MVI) is a prominent risk factor of postoperative recurrence for hepatocellular carcinoma (HCC). The MVI detection rate of conventional pathological examination approaches is relatively low and unsatisfactory., Methods: By integrating pathological macro-slide with whole-mount slide imaging, we first created a novel pathological examination method called image-matching digital macro-slide (IDS). Surgical samples from eligible patients were collected to make IDS. The MVI detection rates, tumor recurrence rates and recurrence-free survival were compared among conventional 3-Point and 7-Point baseline sampling protocols and IDS. Additionally, biomarkers to recognize MVI false negative patients were probed via combining conventional pathological sampling protocols and IDS. Receiver operating characteristic curve (ROC) analysis was used to obtain the optimal cutoff of biomarkers to distinguish MVI false negative patients., Results: The MVI detection rates were 21.98%, 32.97% and 63.74%, respectively, in 3-Point, 7-Point baseline sampling protocols and IDS (p < 0.001). Tumor recurrence rate of patients with MVI negative status in IDS (6.06%) was relatively lower than that of patients with MVI negative status in 3-Point (16.90%) and 7-Point (16.39%) sampling protocols. Alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II) were selected as potential biomarkers to distinguish MVI false negative patients., Conclusions: Our study demonstrated that IDS can help enhance the detection rate of MVI in HCC and refine the prediction of HCC prognosis. Alpha-fetoprotein is identified as a suitable and robust biomarker to recognize MVI false-negative patients in conventional pathological protocols., (© 2022. The Author(s).)

Objective: To evaluate the predictive value of gadoxetic acid-enhanced MRI features (focused on Liver Imaging Reporting and Data System (LI-RADS) v2018 features and non-LI-RADS imaging features) for microvascular invasion (MVI) of hepatocellular carcinoma (HCC)., Methods: From October 2018 to December 2020, 134 patients who underwent gadoxetic acid-enhanced MRI with a pathological diagnosis of HCC after hepatectomy were enrolled in this retrospective study. Two radiologists assessed the pre-hepatectomy LI-RADS v2018 imaging features and non-LI-RADS features to identify independent predictors of MVI of HCC with a logistic regression model., Results: Four MRI features were found to be independent predictors of MVI: corona enhancement [odds ratio (OR) 5.787; 95% confidence interval (CI) 1.180, 28.369; p = 0.030], mosaic architecture (OR 7.097; 95% CI 1.299, 38.783; p = 0.024), nonsmooth tumor margin (OR 13.131; 95% CI 3.950, 43.649; p < 0.001), and peritumoral hypointensity on hepatobiliary phase (HBP) (OR 33.123; 95% CI 2.897, 378.688; p = 0.005). When one of four imaging features was present, the sensitivity was 93.2% (41/44), and the specificity was 71.1% (64/90)., Conclusion: The four imaging features including corona enhancement, mosaic architecture, nonsmooth tumor margin, and peritumoral hypointensity on HBP can be used as preoperative imaging biomarkers for predicting MVI in patients at high risk for HCC. When one of the four imaging features is present, MVI can be predicted with a sensitivity > 90%., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: We assessed the prognostic accuracy of ADV score (α-fetoprotein [AFP]-des-γ-carboxyprothrombin [DCP]-tumor volume [TV] score) following resection of hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT)., Methods: This was a retrospective observational study. This study included 147 patients who underwent hepatic resection for HCC with PVTT. They were followed up for ≥ 66 months or until patient death., Results: The grades of PVTT were Vp1 in 121 (14.3%), Vp2 in 41 (27.9%), Vp3 in 71 (48.3%), and Vp4 in14 (9.5%) cases. Preoperative HCC treatment was performed in 48 (32.7%) patients. R0 and R1 resections were performed in 119 (81.0%) and 28 (19.0%) cases, respectively. The 5-year tumor recurrence, HCC-specific survival, and post-recurrence survival rates were 79.2%, 43.5%, and 25.4%, respectively. Neither PVTT grade nor history of preoperative HCC treatment was a significant prognostic indicator. Stratification in accordance with ADV scores of 1log- and 3log-intervals resulted in high prognostic accuracy in predicting tumor recurrence and patient survival. Following cluster analysis, the cutoff for ADV score was determined at 9log and was more prognostically significant in terms of tumor recurrence and patient survival than surgical curability or microvascular invasion. Further comparisons revealed that prognostic prediction with an ADV score cutoff at 9log was more accurate than that using the Eastern Hepatobiliary Surgery Hospital-PVTT score., Conclusions: ADV score is an integrated surrogate biomarker for post-resection prognosis in HCC with PVTT. Our prognostic prediction model using ADV scores provides reliable post-resection prognosis for patients with various grades of these tumors., (© 2020. The Society for Surgery of the Alimentary Tract.)

Background: Microvascular invasion (MVI) is a risk factor for postoperative survival outcomes for hepatocellular carcinoma (HCC) after liver resection (LR). This study aims to investigate the actual long-term survival and its associated prognostic factors after LR for HCC patients with MVI., Methods: This study was conducted on HCC patients with MVI who underwent LR from January 2009 to December 2012 at five major hospitals in China. The patients were divided into the 'long-term survivor group' and the 'short-term survivor group'. The clinicopathologic characteristics, perioperative data and survival outcomes were compared between these two groups. Univariate and multivariate regression analyses were performed to identify predictive factors associated with long-term survival outcomes., Results: The study included 1517 patients with an actual 5-year survival rate of 33.3%. Multivariate regression analysis revealed that HBV DNA > 10 4  IU/mL, alanine aminotransferase > 44 U/L, alpha-fetoprotein > 400 ng/ml, anatomical hepatectomy, varices, intraoperative blood loss > 400 ml, tumor diameter > 5 cm, tumor number, satellite nodules, tumor encapsulation, wide resection margin and adjuvant transarterial chemoembolization (TACE) were independent prognostic factors associated with actual long-term survival., Conclusions: One-third of HCC patients with MVI reached the long-term survival milestone of 5 years after resection. Anatomical hepatectomy, controlling intraoperative blood loss, a wide resection margin, and postoperative adjuvant TACE should be considered for patients to achieve better long-term survival outcomes., (© 2021. Asian Pacific Association for the Study of the Liver.)

Background: Vessels that encapsulate tumor clusters (VETC) is a novel described vascular pattern different from microvascular invasion (MVI) for patients with hepatocellular carcinoma (HCC). The prognostic value of integrating VETC and MVI (VETC-MVI model) in HCC patients after resection remains unclear., Methods: From January 2013 to December 2016, 498 HCC patients who underwent curative resection were enrolled from five academic centers and stratified into different groups according to their VETC and MVI statuses. Overall survival (OS), disease-free survival (DFS), and early and late recurrence rates were evaluated., Results: The patients were divided into four subgroups: VETC - /MVI - (n = 277, 55.6%), VETC - /MVI + (n = 110, 22.1%), VETC + /MVI - (n = 53, 10.6%), and VETC + /MVI + (n = 58, 11.6%). The patients in the VETC + /MVI - and VETC - /MVI + groups had similar long-term outcomes (OS: p = 0.402; DFS: p = 0.990), VETC - /MVI - patients showed the best prognosis, and VETC + /MVI + patients had the worst prognosis. Further analysis revealed that the VETC-MVI model showed a similar stratification ability for early recurrence but not for late recurrence. The area under the curve values for early recurrence was 0.70, 0.63 and 0.64 for the VETC-MVI model, VETC, and MVI, respectively (VETC-MVI model vs VETC: p < 0.001; VETC-MVI model vs MVI: p = 0.004; VETC vs MVI: p = 0.539). Multivariate Cox regression analysis showed that the VETC-MVI model successfully predicted OS, DFS and early recurrence., Conclusions: VETC status provides additional discriminative information for patients with either MVI - or MVI + . A combination of VETC and MVI may help classify subtypes and predict the prognosis of HCC patients., (© 2021. Asian Pacific Association for the Study of the Liver.)

Background: Few studies have focused on risk factors which may predict an intrahepatic local recurrence (LR) on the surgical edge rather than a distant recurrence (DR) in other liver segments after surgery for hepatocarcinoma (HCC). The purpose of this study was to assess the risk factors for both patterns of recurrence., Methods: An international, multicentre, retrospective study was conducted by collecting data on all consecutive patients with a first diagnosis of HCC who were treated between 2010 and 2017. The presence of macrovascular invasion was an exclusion criteria., Results: About 376 patients were enrolled, and, among them, 62 presented LR, while 90 had DR. Baseline characteristics were comparable between the two groups, but the DR group had a much higher rate of HCV infection (48.9% vs 29%, p 0.014) and a higher median nodule size (3.40 cm IQR 2.2-5.5 versus 3.0 cm IQR 2.0-5.0 in the LR group, p 0.025). A positive surgical margin (R1, HR 4.721; 95% CI 1.83-12.17; p 0.001) was the only independent risk factor for LR, while MVI (HR 1.837; 95% CI 1.03-3.77; p 0.039) and satellitosis (HR 2.440, 95% CI 1.43-3.77, p 0.001) were the only predictive factors for DR., Conclusion: MVI and satellitosis are predictive factors of intrahepatic distant recurrence, configuring a probable hallmark of advanced systemic disease, regardless of the treatment. LR has to be considered the expression of surgical failure.

Microvascular invasion (mVI) is the most significant independent predictor of recurrence for hepatocellular carcinoma (HCC), but its pre-operative assessment is challenging. In this study, we investigate the use of multi-parametric MRI radiomics to predict mVI status before surgery. We retrospectively collected pre-operative multi-parametric liver MRI scans for 99 patients who were diagnosed with HCC. These patients received surgery and pathology-confirmed diagnosis of mVI. We extracted radiomics features from manually segmented HCC regions and built machine learning classifiers to predict mVI status. We compared the performance of such classifiers when built on five MRI sequences used both individually and combined. We investigated the effects of using features extracted from the tumor region only, the peritumoral marginal region only, and the combination of the two. We used the area under the receiver operating characteristic curve (AUC) and accuracy as performance metrics. By combining features extracted from multiple MRI sequences, AUCs are 86.69%, 84.62%, and 84.19% when features are extracted from the tumor only, the peritumoral region only, and the combination of the two, respectively. For tumor-extracted features, the T2 sequence (AUC = 80.84%) and portal venous sequence (AUC = 79.22%) outperform other MRI sequences in single-sequence-based models and their combination yields the highest AUC of 86.69% for mVI status prediction. Our results show promise in predicting mVI from pre-operative liver MRI scans and indicate that information from multi-parametric MRI sequences is complementary in identifying mVI.

Background and Aims: Microvascular invasion (MVI) is a key pathological factor that severely affects the postoperative prognosis of patients with hepatocellular carcinoma (HCC). However, no MVI classification schemes based on standardized gross sampling protocols of HCC are available at present., Methods: 119 HCC specimens were sampled at multiple sites (3-, 7-, and 13 points) for the optimum MVI detection rate. 16,144 resected HCCs were graded as M0, M1 or M2 by adopting three-tiered MVI grading (MVI-TTG) scheme based on the seven-point sampling protocol (SPSP). Survival analyses were performed on 2573 patients to explore the advantages of MVI-TTG., Results: The MVI detection rate determined by SPSP was significantly higher than that determined by the 3-point sampling method (34.5% vs. 47.1%, p = 0.048), but was similar to that determined by the 13-point sampling method (47.1% vs. 51.3%, p = 0.517). Among 16,144 resected HCCs, the proportions of M0, M1 and M2 specimens according to SPSP were 53.4%, 26.2% and 20.4%, respectively. Postoperative survival analysis in 2573 HCC patients showed that the 3-year recurrence rates in M0, M1 and M2 MVI groups were 62.5%, 71.6% and 86.1%, respectively (p < 0.001), and the corresponding 3-year overall survival (OS) rates were 94.1%, 87.5% and 67.0%, respectively (p < 0.001). M1 grade was associated with early recurrence, while M2 grade was associated with both early and late recurrence. MVI-TTG had a larger area under the curve and net benefit rate than the two-tiered MVI grading scheme for predicting time to recurrence and OS., Conclusions: SPSP is a practical method to balance the efficacy of sampling numbers and MVI detection rates. MVI-TTG based on SPSP is a better prognostic predictor than the two-tiered MVI scheme. The combined use of SPSP and MVI-TTG is recommended for the routine pathological diagnosis of HCC.

Background: Large, multinodular (> 3 nodules and/or > 3 cm) hepatocellular carcinoma (HCC) is not an indication for liver resection based on the Barcelona Clinic Liver Cancer (BCLC) staging classification. We hypothesize that microvascular invasion (MVI) is a strong indication for surgery in these patients., Methods: Between December 2009 and December 2010, a retrospective cohort of the patients with BCLC intermediate stage HCC undergoing surgical resection at Eastern Hepatobiliary Surgery Hospital was analyzed. Propensity score matching (PSM) was conducted to balance the patients with regard to their baseline characteristics. Survival analysis was performed according to the Kaplan-Meier method. Logistic regression was conducted to identify the predictors of MVI. Risk factors were evaluated using the Cox proportional hazards model., Results: Among 323 patients, the MVI-negative group (26.0%) had a more favorable prognosis than did the MVI-positive group (5-year recurrence-free survival: 25.2% vs. 7.8%; 5-year overall survival: 49.5% vs. 24.0%). Similar results were identified after PSM. Compared with MVI-negative patients, MVI-positive patients experienced more early recurrence (< 2 years, P = 0.006), multinodular recurrence (P = 0.004), and extrahepatic recurrence (P = 0.026). Total bilirubin levels > 17.1 μmol/L, alpha fetal protein levels > 400 ng/mL, the presence of > 2 nodules, and the lack of a capsule were independent predictors of MVI., Conclusions: In BCLC intermediate stage HCC, MVI predicted an adverse recurrence pattern and poor prognosis and has the potential to be used as a reference index when deciding whether to operate. Factors predictive of MVI could assist in choosing preoperative treatment and postoperative surveillance.

The objective of this study was to determine the clinical value of computed tomography (CT) image-based texture analysis in predicting microvascular invasion of primary hepatocellular carcinoma (HCC). CT images of patients with HCC from May 2017 to May 2019 confirmed by surgery and histopathology were retrospectively analyzed. Image features including tumor margin, tumor capsule, peritumoral enhancement, hypoattenuating halo, intratumoral arteries, and tumor-liver differences were assessed. All patients were divided into microvascular invasion (MVI)-negative group (n = 34) and MVI-positive group (n = 68). Preoperative CT images were further imported into MaZda software, where the regions of interest of the lesions were manually delineated. Texture features of lesions based on pre-contrast, arterial, portal, and equilibrium phase CT images were extracted. Thirty optimal texture parameters were selected from each phase by Fisher's coefficient (Fisher), classification error probability combined with average correlation coefficient (POE+ACC), and mutual information (MI). Finally, receiver operating characteristic curve analysis was performed. The results showed that the Edmonson-Steiner grades, tumor size, tumor margin, and intratumoral artery characteristics were significantly different between the two groups (P = 0.012, < 0.001, < 0.001, = 0.003, respectively). There were 58 parameters with significant differences between the MVI-negative and MVI-positive groups (P < 0.001 for all). Among them, 12, 14, 17, and 15 parameters were derived from the pre-contrast phase, arterial phase, portal phase, and equilibrium phase respectively. According to the ROC analysis, optimal texture parameters based on the pre-contrast, arterial, portal, and equilibrium phases were 135dr&#95;GLevNonU (AUC, 0.766; the cutoff value, 1055.00), Vertl&#95;RLNonUni (AUC, 0.764; the cutoff value, 5974.38), 45dgr&#95;GLevNonU (AUC, 0.762; the cutoff value, 924.34), and Vertl&#95;RLNonUni (AUC, 0.754; the cutoff value, 4868.80), respectively. Texture analysis of preoperative CT images may be used as a non-invasive method to predict microvascular invasion in patients with primary hepatocellular carcinomas, and further to guide the treatment and evaluate prognosis. The most valuable parameters were derived from the gray-level run-length matrix.

Background: Hepatocellular carcinoma (HCC) is subclassified into five gross types, namely, vaguely nodular (VN), single nodular (SN), single nodular with extranodular growth (SNEG), confluent multinodular (CM), and infiltrative (INF) type. However, the pathological background underlying differences in biological behavior of different gross types of HCC remains unclear., Methods: The histopathological features, clinical outcomes of HCC gross types, and their relationships with stemness-related marker status and fibrotic/hypoxic tumor microenvironment (TME) were evaluated in 266 resected HCCs. The stemness-related markers (CD24, CD44, CD133, SALL4, YAP1, K19 and EpCAM), fibrous tumor stroma (αSMA), and hypoxia (CAIX) were evaluated with immunohistochemistry., Results: Poorer differentiation, reduced capsule formation, higher microvascular invasion, larger tumor size and larger area of necrosis were observed in order of VN-SN-SNEG-CM-INF type (p = 0.005 for all, linear-by-linear association). The expression of summed stemness-related markers and hypoxic/fibrotic TME showed an increasing trend in order of VN-SN-SNEG-CM-INF type (p < 0.005), and their expression well correlated with each other. INF type was found only in HCCs with hypoxic/fibrotic TME or high expression of stemness-related markers. CAIX expression and tumor necrosis ≥ 30% were independent prognostic markers for disease-specific survival. Early recurrence-free survival showed a significant difference based on gross types, revealing best outcome with VN type and worst outcome with INF type., Conclusion: The marker expression of stemness-related and hypoxic/fibrotic TME of HCC showed an increasing trend in order of VN-SN-SNEG-CM-INF gross types, and their cross-talk may be involved in the determination of various gross-morphological features and their distinct biological behavior.

Background: Microvascular invasion (MVI) relates to poor survival in hepatocellular carcinoma (HCC) patients. In this study, we aim at developing a nomogram for MVI prediction and potential assistance in surgical planning., Methods: A total of 357 patients were assigned to training (n = 257) and validation (n = 100) cohort. Univariate and multivariate analyses were used to reveal preoperative predictors for MVI. A nomogram incorporating independent predictors was constructed and validated. Disease-free survival was compared between patients, and the potential of the predicted MVI in making surgical procedure was also explored., Results: Pathological examination confirmed MVI in 140 (39.2%) patients. Imaging features including larger tumor, intra-tumoral artery, tumor type, and higher serum AFP independently correlated with MVI. The nomogram showed desirable performance with an AUROC of 0.803 (95% CI, 0.746-0.860) and 0.814 (95% CI, 0.720-0.908) in the training and validation cohorts, respectively. Good calibration were also revealed by calibration curve in both cohorts. The decision curve analysis indicated that the prediction nomogram was of promising usefulness in clinical work. In addition, survival analysis revealed that patients with positive-predicted MVI suffered a higher risk of early recurrence (P < 0.01). There was no difference in disease-free survival between anatomic or non-anatomic resection in large HCC or small HCC without nomogram-predicted MVI. However, anatomic resection improved disease-free survival in small HCC with nomogram-predicted MVI., Conclusions: The nomogram obtained desirable results in predicting MVI. Patients with predicted MVI were associated with early recurrence and anatomic resection was recommended for small HCC patients with predicted MVI.

Purpose: Microvascular invasion (MVI), which is difficult to diagnose before surgery, is a major factor affecting postoperative recurrence in patients with hepatocellular carcinoma (HCC). The relationship between the radiological tumor capsule and MVI is controversial. This study aimed to evaluate the association between the tumor capsule and MVI., Methods: We searched Medline (by PubMed) and Embase (by OvidSP). Two review authors independently screened titles and abstracts, selected studies about MVI prediction with radiologic tumor capsule and studies with enough data for extracted, assessed the methodological quality and collected data. Summary results were presented as the diagnostic odds ratio (DOR), sensitivity, specificity, and 95% confidence interval., Results: Fifteen studies with 2038 patients were included; fourteen studies, including 1331 patients, with no significant heterogeneity indicated no relationship between absent tumor capsule and MVI [DOR = 0.90 (0.64, 1.26)]. Six studies, including 541 patients, with no significant heterogeneity showed incomplete capsule could be used to predict MVI of HCC preoperatively [DOR = 1.85 (1.13, 3.04)]. The overall sensitivity and specificity estimate were 0.50 (0.37, 0.64) and 0.64 (0.53, 0.74), respectively. Eight studies, including 1349 patients, with highly significant heterogeneity revealed that complete capsule could be a protective factor for MVI [DOR = 1.97 (1.01, 3.86)]., Conclusions: For MVI of HCC, incomplete tumor capsule is a risk factor, while a complete tumor capsule might be a protective factor. However, absent capsule doesn't show significant relationship with MVI. This might be due to combination of the risk and protective effects of present capsule in MVI.

Purpose: To assess major and ancillary parameters that could be correlated with Microvascular Invasion (MIV) and with histologic grade of HCC., Materials and Methods: In this retrospective study, we assessed 62 patients (14 women-48 men; mean age, 63 years; range 38-80 years) that underwent hepatic resection for HCC. All patients were subject to Multidetector computed tomography (MDCT); 40 to Magnetic Resonance (MR) study. The radiologist assessed major and ancillary features according to LIRADS (v. 2018) and reported any radiological accessory findings if detected., Results: No major feature showed statistically significant differences and correlation with grading. Mean ADC value was correlated with grading and with MIV status. No major feature was correlated to MIV; progressive contrast enhancement and satellite nodules showed statistically different percentages with respect to the presence of MIV, so as at the monovariate correlation analysis, satellite nodules were correlated with the presence of MIV. At multivariate regression analysis, no factor proved to be strong predictors of grading while progressive contrast enhancement and satellite nodules were significantly associated with the MIV., Conclusion: Mean ADC value is correlated to HCC grading and MIV status. Progressive contrast enhancement and the presence of satellite nodules are correlated to MIV status.

Background: Microvascular invasion (MVI) is recognized as a risk factor for early recurrence of hepatocellular carcinoma (HCC) within the Milan criteria after curative treatment., Methods: One hundred eleven consecutive patients with HCC within the Milan criteria who underwent hepatic resection were retrospectively reviewed. Independent preoperative predictors of MVI were identified, and a scoring system was developed using significant predictors., Results: MVI was identified in 51 of 111 patients (46%). Multivariate analysis identified the following independent predictors of MVI: alpha-fetoprotein (AFP) of > 95 ng/mL (odds ratio [OR], 9.87; 95% confidence interval [95% CI], 2.24-56.8; P = 0.002), des-γ-carboxy prothrombin (DCP) of > 55 mAU/mL (OR, 5.50; 95% CI, 2.09-15.4; P < 0.001), tumor size of > 2.8 cm (OR, 6.10; 95% CI, 2.07-20.0; P < 0.001), and non-smooth tumor margin in the hepatobiliary phase of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) (OR, 5.34; 95% CI, 1.84-16.9; P = 0.002). A clinical scoring system was developed using these four variables. Within a total possible score of 0 to 4, the prevalence of MVI with a score of 0, 1, 2, 3, and 4 was 4.5%, 24.0%, 45.5%, 91.7%, and 100%, respectively (P < 0.001). The area under the curve of the scoring system was 0.865 based on the receiver operating characteristic curve analysis of the prediction score., Conclusions: Our clinical scoring system, consisting of AFP, DCP, tumor size, and tumor margin in Gd-EOB-DTPA-enhanced MRI, can be valuable for predicting MVI in HCC within the Milan criteria before curative treatment.

Purpose: To investigate whether pre-operative gadoxetic acid-enhanced MRI can predict early recurrence after curative resection of single HCC using image features and texture analysis., Materials and Methods: 179 patients with single HCC and who underwent pre-operative MRI were included. Two reviewers analyzed MR findings, including the tumor margin, peritumoral enhancement, peritumoral hypointensity on the hepatobiliary phase (HBP), diffusion restriction, capsule, tumoral fat, washout, portal-vein thrombus, signal intensity on HBP, and satellite nodule. Texture analysis on the HBP was also quantified. A multivariate analysis was used to identify predictive factors for early recurrence, microvascular invasion (MVI), and the tumor grade., Results: For early recurrence, satellite nodule, peritumoral hypointensity, absence of capsule, and GLCM ASM were predictors (P < 0.05). For MVI, satellite nodule, peritumoral hypointensity, washout, and sphericity were predictors (P < 0.05). Satellite nodules, peritumoral hypointensity, diffusion restriction, and iso to high signal intensity on HBP were predictor for higher tumor grade (P < 0.05). Satellite nodules and peritumoral hypointensity were important showed common predictors for early recurrence, MVI, and grade (P < 0.05). The sensitivity and specificity for satellite nodule were 47.36% and 96.25%. When added texture variables to MRI findings, the diagnostic performance for predicting early recurrence is improved from 0.7 (SD 0.604-0.790) to 0.83 (SD 0.787-0.894)., Conclusion: MR finding, including satellite nodule and peritumoral hypointensity on the HBP, as well as the texture parameters are useful to predict not only early recurrence, but also MVI and higher grade.

Background: Histologic microvascular invasion (MVI) substantially worsens the prognosis of patients with hepatocellular carcinoma, and can only be diagnosed postoperatively. Preoperative assessment of MVI by imaging has been focused on tumor-related features, while peritumoral imaging features have been indicated elsewhere to be more accurate. The aim of the present study is to evaluate the association between peritumoral imaging features and MVI., Methods: Literature search was performed using the PubMed, Embase, and Cochrane Library databases. Summary results of the association between peritumoral imaging features and MVI were presented as the odds ratio (OR) and the 95% confidence interval. Meta-regression and subgroup analyses were performed when heterogeneity was detected. Diagnostic accuracy analysis was also conducted for identified features., Results: Ten studies were included in the analysis. Moderate and low heterogeneities were found among the seven studies on peritumoral enhancement and four studies on peritumoral hypointensity on HBP, respectively. Summary results revealed a significant association between MVI and peritumoral enhancement (OR 4.04 [2.23, 7.32], p < 0.05), and peritumoral hypointensity on HBP (OR 10.62 [5.31, 21.26], p < 0.05). Diagnostic accuracy analysis revealed high specificity (0.90-0.94) but low sensitivity (0.29-0.40) for both features to assess MVI., Conclusion: The two peritumoral imaging features are significantly associated with MVI. The two features highly suggest MVI only when present with a high false negative rate. Promotion of their diagnostic efficiency can be a worthwhile task for future research.

Purpose: This study aimed to investigate whether ADC similarity can predict microvascular invasion (MVI) in patients with bifocal hepatocellular carcinoma (HCC)., Materials and Methods: Between January 2015 and September 2015, 51 patients with two HCC lesions were included. All patients underwent conventional magnetic resonance imaging including diffusion-weighted imaging (DWI) before the HCC lesions were surgically resected; the tumor specimens were examined histopathologically. Similarity between two HCC lesions regarding DWI signal intensity (SI) and ADC value was calculated as the difference between the two lesions: Value Similarity = [1-(|value large lesion -value small lesion |)/(value large lesion  + value small lesion )] × 100%. Univariate and multivariate logistic regression analyses were performed to assess the presence of MVI., Results: Risk factors significantly related to MVI of bifocal HCC in univariate analysis were cirrhosis (P = 0.010), histological grade (P = 0.040), DWI SI similarity (P = 0.027) and ADC similarity (P = 0.003). In multivariate analysis, cirrhosis (odds ratio 0.068, P = 0.022) and ADC similarity (odds ratio 1.204, P = 0.008) were independent risk factors for MVI of bifocal HCC., Conclusion: In patients with two HCC lesions, highly similar ADC values for the two HCC lesions may be a preoperative predictor of MVI.

Recurrence of HCC reduces survival rates in patients treated with surgery, and one of the most relevant risk factors for tumour recurrence is microvascular invasion (mVI). The identification of mVI on preoperative examinations could improve surgical planning's and techniques so as to reduce the risk of tumour recurrence. During our study, we have revised 101 CT examinations of the liver performed on patients diagnosed with solitary HCC who had surgical treatment and pathological analysis of the specimens for mVI in order to detect CT signs which could be reliable in mVI prediction. On CT examinations, the tumours were evaluated for margins, capsule, size, contrast enhancement, halo sign and Thad. From our statistical analysis, we found out that irregularity in tumour margins and defects in peritumoural capsule are the most significant characteristics predicting mVI in HCC. Every report on CT examinations performed on surgical candidate patients should include suggestions about mVI probability in order to tailor procedures, reduce tumour recurrence risk and improve survival rates.

Background: We hypothesized that microvascular invasion (MVI) and post-resection prognosis in patients with solitary hepatocellular carcinoma (HCC) could be predicted using blood tumor markers and tumor volume (TV). We intended to identify a simple surrogate marker of HCC via a combination of clinical variables., Methods: This retrospective study used the strictly selected development cohort (n = 1176) and validation cohort (n = 551) containing patients who underwent curative resection of solitary HCC., Results: In the development cohort study, the median values were 13.7 mL for TV, 24.2 ng/mL for α-fetoprotein (AFP), and 75 mAU/mL for des-γ-carboxy prothrombin (DCP); there was no correlation among these three factors (r 2  ≤ 0.237, p < 0.001). The 1-, 3-, and 5-year rates were 22.4, 41.7, and 46.8 % for tumor recurrence and 93.6, 84.0, and 78.2 % for patient survival, respectively. Independent risk factors for both tumor recurrence and patient survival were tumor diameter >5 cm or TV >50 mL, MVI, satellite nodules, and high DCP. Multiplication of AFP, DCP, and TV (ADV score) resulted in prediction of MVI at a cutoff of 5log with sensitivity of 73.9 % and specificity of 66.7 %. Patient stratifications according to ADV score with cutoffs of 5log alone, 6log and 9log, and its combination with MVI showed significant prognostic differences (all p < 0.001). These prognostic significances were reliably reproduced in the validation cohort study (all p < 0.001)., Conclusions: We suggest that ADV score is an integrated surrogate marker of HCC prognosis. We believe that it can be used to predict MVI and post-resection prognosis for solitary HCC.

Purpose: This study was to evaluate the role of quantitative perfusion analysis of 3-dimensional (3D) contrast-enhanced ultrasound (CEUS) in detecting microvascular invasion (MVI) of liver tumor in vivo., Methods: VX2 tumors were implanted in the livers of sixteen New Zealand rabbits. On day 10, real-time 3D CEUS was performed, and the real-time dynamic images were analyzed using online quantification software. The animals were sacrificed and sent for pathology examinations. According to the gold standard of pathology, the animals were divided into an MVI group and a group without MVI (non-MVI group). Time-intensity curves (TICs) were obtained for the VX2 tumors and the surrounding liver parenchyma, and the parameters peak intensity (PI), mean transit time (MTT), and time to peak (TTP) were compared within and between the MVI and non-MVI groups., Results: The TTP and MTT of the VX2 tumors were significantly faster than those of the surrounding liver parenchyma in both MVI and non-MVI groups. The PI of the VX2 tumors was significantly lower than that of the surrounding liver parenchyma in the non-MVI group but not the MVI group. The TTP and MTT of the VX2 tumors and surrounding liver parenchyma were not significantly different in the MVI group compared with the non-MVI group, whereas the ΔPI (the PI ratio between the VX2 liver tumors and the reference liver parenchyma) of the VX2 tumors in the MVI group was larger than that in the non-MVI group. VX2 tumors with MVI present different hemodynamic parameters, with a larger ΔPI than tumors without MVI., Conclusions: Our data suggest that quantitative perfusion analysis of 3D CEUS might be a promising method for predicting MVI in liver tumors.

Purpose: Microvascular invasion of hepatocellular carcinoma (HCC) is considered a poor prognostic factor of liver resection (LR) and liver transplantation (LT), but its significance for lesions within the up-to-7 criteria is unclear. This study investigated the survival benefit of primary LT against LR for HCC with microvascular invasion and within the up-to-7 criteria., Methods: Adult patients who underwent LR or LT as the primary treatment for HCC were included for study. Patients with prior local ablation, neoadjuvant systemic chemotherapy, targeted therapy, positive resection margin, or metastatic spread were excluded., Results: There were 471 LR patients and 95 LT recipients (70 with living donor, 25 with deceased donor). Seventy-seven (81.1%) LT recipients had HCC within the up-to-7 criteria. Twenty-five (26.3%) LT recipients had HCC with either macrovascular ( n  = 4) or microvascular ( n  = 21) invasion. The 5-year survival rate was 85.7% for LT recipients with HCC within the up-to-7 criteria, unaffected by the presence or absence of vascular invasion (88.2 vs. 85.1%). The rate was comparable with that of LR patients with HCC without vascular invasion (81.2%, p 0.227), but far superior to that of LR patients with lesions with vascular invasion (50.0%, p  < 0.0001). Overall survivals were compromised by multiple tumors [odds ratio (OR) 1.902, confidence interval (CI) 1.374-2.633, p  = 0.0001], vascular invasion (OR 2.678, CI 1.952-3.674, p  < 0.0001), blood transfusion (OR 2.046, CI 1.337-3.131, p  = 0.001), and being beyond the up-to-7 criteria (OR 1.457, CI 1.041-2.037, p  = 0.028). LT was a favorable factor for survival (OR 0.243, CI 0.130-0.454, p  < 0.0001)., Conclusion: Primary LT for HCC with microvascular invasion and within the up-to-7 criteria doubled the chance of cure as compared with LR.