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Microvascular invasion (MVI) diagnosis relies on postoperative pathological examinations, underscoring the urgent need for a novel diagnostic method. C-Reactive Protein (CRP), has shown significant relevance to hepatocellular carcinoma (HCC) prognosis. This study aims to explore the relationship between preoperative serum CRP levels and microvascular invasion in hepatocellular carcinoma and develop a nomogram model for predicting MVI. Patients were categorized into MVI-positive and MVI-negative groups for analysis. Serum CRP levels were compared between the two groups. And then use LASSO regression to screen variables and build a nomogram. CRP levels showed significant differences between the MVI-positive and MVI-negative groups. Multivariable logistic regression analysis identified CRP (OR = 4.85, P < 0.001), lnAFP (OR = 3.11, P < 0.001), WBC count (OR = 2.73, P = 0.003), and tumor diameter (OR = 2.38, P = 0.01) as independent predictors of MVI. A nomogram based on these variables showed good predictive performance in both the training and validation cohorts with dual validation. The clinical prediction nomogram model, which includes serum CRP levels, WBC count, tumor diameter, and serum AFP levels, showed good performance in predicting MVI in both the training and validation cohorts. [ABSTRACT FROM AUTHOR]

Background: This study aims to investigate the clinicopathological and ultrasonography characteristics of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and its correlation with microvascular invasion (MVI), as well as the predictive value of contrast-enhanced ultrasound (CEUS) imaging. Methods: A retrospective analysis was conducted on 57 patients diagnosed with cHCC-CCA between November 2017 and May 2023 at Guizhou Provincial People's Hospital. Among them, 27 patients were MVI-positive and 30 patients were MVI-negative, all of whom underwent preoperative CEUS within 2 weeks. Clinical data, ultrasonographic findings, and CEUS features were compared between the two groups to analyze the influencing factors and predictive value of MVI in cHCC-CCA patients. Results: Compared to the MVI-negative group, the MVI-positive group showed a higher proportion of tumors with a maximum diameter greater than 5 cm, elevated alpha-fetoprotein (AFP) levels, low echo halo around the tumor, non-smooth tumor contour, peripheral irregular rim-like enhancement and early washout (≤60s) with nodular patterns on CEUS (P<0.05). Multivariate logistic regression analysis revealed that low echo halo, peripheral irregular rim-like enhancement, and early washout were independent risk factors for MVI in cHCC-CCA patients. The receiver operating characteristic (ROC) curve analysis demonstrated an area under the curve (AUC) of 0.8056 for these factors. Conclusions: Ultrasonographic and CEUS features have a certain correlation with MVI in cHCC-CCA patients. Low echo halo, peripheral irregular rim-like enhancement, and early washout are independent risk factors for MVI in patients with cHCC-CCA. These features have a predictive value in determining the presence of MVI in patients with cHCC-CCA. [ABSTRACT FROM AUTHOR]

Background/Objectives: The oncological importance of lymphatic, microvascular, and perineural invasions and their association with outcomes in patients with non-functioning pancreatic neuroendocrine neoplasm (NF-PanNEN) remains unclear. We aimed to investigate the role of these factors in the prognosis of patients with NF-PanNEN. Methods: We retrospectively analyzed 115 patients who underwent curative resection and were pathologically and clinically diagnosed with NF-PanNEN. We evaluated the relationship between clinicopathological factors and recurrence. Results: Thirty (26%), 38 (33%), and 11 (10%) patients had lymphatic, microvascular, and nerve invasions, respectively. Twenty-one patients (18%) experienced recurrence, with a median time to recurrence of 2.6 years (range: 0.3–8.2). The 3-, 5-, and 10-year recurrence-free survival (RFS) rates were 88.3%, 84.4%, and 79.1%, respectively. In multivariate analyses, World Health Organization Grade G2–3 (vs. G1, hazard ratio (HR): 16.2), T factor T3–4 (vs. T1-2, HR: 5.2), and the presence of microvascular invasion (vs. absence, HR: 5.6) were significant risk factors for RFS. When these risk factors were assigned as risk score of three, one, and one points depending on the HR, the 5-year recurrence rates in patients with risk score groups 0–1 and 2–5 were 98.6% and 53.3%, (P < 0.001). Moreover, only the presence of microvascular invasion significantly increased the likelihood of recurrence within 3 years. Conclusions: The presence of microvascular invasion is an independent risk factor for recurrence in patients with NF-PanNEN. Our risk scoring system, which includes "the presence of microvascular invasion," may be useful for predicting recurrence. [ABSTRACT FROM AUTHOR]

Assessment of recurrence risk after liver resection (LR) is critical in hepatocellular carcinoma (HCC), particularly with the advent of effective adjuvant therapy. The aim of this study was to analyze the clinical and pathological factors associated with recurrence, aggressive recurrence, and survival after LR. We performed a retrospective study in which all single HCC (BCLC-0/A) patients treated with LR between February 2000 and November 2020 were included. The main clinical variables were recorded. Histological features were blindly evaluated by two independent pathologists. Aggressive recurrence was defined as those that exceeded the Milan criteria at 1st recurrence. A total of 218 patients were included (30% BCLC 0 and 70% BCLC A), median (IQR) tumor size of 28 (19-42 mm). The prevalence of microvascular invasion and/or satellitosis (mVI/S) was 39%, with a kappa-index between both pathologists of 0.8. After a median follow-up of 49 (23-85) months, 61/218 (28%) patients died, 32/218 (15%) underwent liver transplantation, 127 (58%) developed HCC recurrence. The prevalence of aggressive recurrence was 35% (44/127 Milan-out, with 20 cases at advanced stage), and the 5-year survival rate was 81%. The presence of mVI/S was the only independent predictor of recurrence (hazard ratio [HR] 1.83, 95% CI 1.28-2.61, p < 0.001), aggressive recurrence (HR 3.31, 95% CI 1.74–6.29, p < 0.001) and mortality (HR 2.23, 95% CI 1.27–3.91, p = 0.005). The macrotrabecular-massive subtype was significantly associated with a higher prevalence of mVI/S, Edmonson Steiner grade III-IV, AFP values and vessels that encapsulate tumor clusters, but not with recurrence, aggressive recurrence, or overall survival. The presence of mVI/S was the only independent risk factor for aggressive recurrence and mortality. This has important implications for early-stage patient management, especially in the setting of adjuvant immunotherapy or ab initio LT. Assessment of recurrence risk after liver resection is crucial in patients with hepatocellular carcinoma. Patients with a high risk of recurrence are candidates for liver transplantation as an ab initio indication or for the potential use of adjuvant therapy. Aggressive recurrences, defined as those exceeding the Milan criteria at first recurrence, have a significant impact on overall survival (OS). Fifty-eight percent of patients experienced hepatocellular carcinoma recurrence, with a prevalence of aggressive recurrence at the first occurrence standing at 35%. After a median follow-up of 49 (23-85) months, 61 (28%) patients died, and 32 (15%) underwent liver transplantation, resulting in a 5-year OS rate of 81%. Microvascular invasion and/or satellitosis was present in 39% of our cohort and was the only independent predictor of recurrence, aggressive recurrence, and OS on multivariate analysis. This is important as it could be used to guide therapeutic management. [Display omitted] • Fifty-eight percent of patients experienced HCC recurrence, 35% of them exceeding Milan criteria (aggressive recurrences). • Exceeding the Milan criteria at first recurrence had a significant impact on overall survival. • After a 49-month median follow-up, the 5-year overall survival rate was 81%. • Microvascular invasion and/or satellitosis was the only independent predictor of (aggressive) recurrence and overall survival. [ABSTRACT FROM AUTHOR]

The prognosis of patients with hepatocellular carcinoma (HCC) undergoing hepatectomy is unsatisfactory, especially for those with microvascular invasion (MVI). This study aimed to determine the impact of adjuvant transcatheter arterial chemoembolization (TACE) and Lenvatinib on the prognosis of patients with HCC and MVI after hepatectomy. Patients diagnosed with HCC and MVI were reviewed, and stratified into four groups according to adjuvant TACE and/or Lenvatinib. Multivariate Cox regression analyses are used to determine independent risk factors. 346 patients were included, and divided into four groups (Group I, TACE+ Lenvatinib; Group II, Lenvatinib; Group III, TACE; Group IV, without adjuvant therapy). Multivariable analysis showed that compared to Group IV, Group I had the best effect on improving the overall survival (OS, HR 0.321, 95%CI 0.099–0.406, P = 0.001) and recurrence-free survival (RFS, HR 0.319, 95%CI 0.129–0.372, P = 0.001). Additionally, compared with Group II or Group III, Group I also can significantly improve the OS and RFS. There is no significant difference between Group II and Group III in OS and RFS. The combination of TACE and Lenvatinib should be considered for anti-recurrence therapy for patients with HCC and MVI after hepatectomy. • The results showed that for high-risk patients, adjuvant TACE combined with Lenvatinib is better than single-agent. • Adjuvant TACE combined with Lenvatinib which can effectively reduce recurrence and improve long-term prognosis. • There was no significant survival difference between TACE and Lenvatinib. [ABSTRACT FROM AUTHOR]

Background: Pretreatment identification of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is important when selecting treatment strategies. Purpose: To improve models for predicting MVI and recurrence‐free survival (RFS) by developing nomograms containing three‐dimensional (3D) MR elastography (MRE). Study Type: Prospective. Population: 188 patients with HCC, divided into a training cohort (n = 150) and a validation cohort (n = 38). In the training cohort, 106/150 patients completed a 2‐year follow‐up. Field Strength/Sequence: 1.5T 3D multifrequency MRE with a single‐shot spin‐echo echo planar imaging sequence, and 3.0T multiparametric MRI (mp‐MRI), consisting of diffusion‐weighted echo planar imaging, T2‐weighted fast spin echo, in‐phase out‐of‐phase T1‐weighted fast spoiled gradient‐recalled dual‐echo and dynamic contrast‐enhanced gradient echo sequences. Assessment: Multivariable analysis was used to identify the independent predictors for MVI and RFS. Nomograms were constructed for visualization. Models for predicting MVI and RFS were built using mp‐MRI parameters and a combination of mp‐MRI and 3D MRE predictors. Statistical Tests: Student's t‐test, Mann–Whitney U test, chi‐squared or Fisher's exact tests, multivariable analysis, area under the receiver operating characteristic curve (AUC), DeLong test, Kaplan–Meier analysis and log rank tests. P < 0.05 was considered significant. Results: Tumor c and liver c were independent predictors of MVI and RFS, respectively. Adding tumor c significantly improved the diagnostic performance of mp‐MRI (AUC increased from 0.70 to 0.87) for MVI detection. Of the 106 patients in the training cohort who completed the 2‐year follow up, 34 experienced recurrence. RFS was shorter for patients with MVI‐positive histology than MVI‐negative histology (27.1 months vs. >40 months). The MVI predicted by the 3D MRE model yielded similar results (26.9 months vs. >40 months). The MVI and RFS nomograms of the histologic‐MVI and model‐predicted MVI‐positive showed good predictive performance. Data Conclusion: Biomechanical properties of 3D MRE were biomarkers for MVI and RFS. MVI and RFS nomograms were established. Level of Evidence: 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Microvascular invasion (MVI) is a key prognostic factor for hepatocellular carcinoma (HCC). The predictive models for solitary HCC could potentially integrate more comprehensive tumor information. Owing to the diverse findings across studies, we aimed to compare radiomic and non-radiomic methods for preoperative MVI detection in solitary HCC. Articles were reviewed from databases including PubMed, Embase, Web of Science, and the Cochrane Library until April 7, 2023. The pooled sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated using a random-effects model within a 95% confidence interval (CI). Diagnostic accuracy was assessed using summary receiver-operating characteristic curves and the area under the curve (AUC). Meta-regression and Z-tests identified heterogeneity and compared the predictive accuracy. Subgroup analyses were performed to compare the AUC of two methods according to study type, study design, tumor size, modeling methods, and imaging modality. The analysis incorporated 26 studies involving 3539 patients with solitary HCC. The radiomics models showed a pooled sensitivity and specificity of 0.79 (95%CI: 0.72–0.85) and 0.78 (95%CI: 0.73–0.82), with an AUC at 0.85 (95%CI: 0.82–0.88). Conversely, the non-radiomics models had sensitivity and specificity of 0.74 (95%CI: 0.65–0.81) and 0.88 (95%CI: 0.82–0.92) and an AUC of 0.88 (95%CI: 0.85–0.91). Subgroups with preoperative MRI, larger tumors, and functional imaging had higher accuracy than those using preoperative CT, smaller tumors, and conventional imaging. Non-radiomic methods outperformed radiomic methods, but high heterogeneity calls across studies for cautious interpretation. [ABSTRACT FROM AUTHOR]

Background and aims: The prognosis of patients with hepatocellular carcinoma (HCC) undergoing hepatectomy is unsatisfactory, especially for those with microvascular invasion (MVI). This study aimed to determine the impact of adjuvant transcatheter arterial chemoembolization (TACE) and Lenvatinib on the prognosis of patients with HCC and MVI after hepatectomy. Methods: Patients diagnosed with HCC and MVI were reviewed, and stratified into four groups according to adjuvant TACE and/or Lenvatinib. Multivariate Cox regression analyses are used to determine independent risk factors. Results: 346 patients were included, and divided into four groups (Group I, TACE+ Lenvatinib; Group II, Lenvatinib; Group III, TACE; Group IV, without adjuvant therapy). Multivariable analysis showed that compared to Group IV, Group I had the best effect on improving the overall survival (OS, HR 0.321, 95%CI 0.099–0.406, P = 0.001) and recurrence-free survival (RFS, HR 0.319, 95%CI 0.129–0.372, P = 0.001). Additionally, compared with Group II or Group III, Group I also can significantly improve the OS and RFS. There is no significant difference between Group II and Group III in OS and RFS. Conclusion: The combination of TACE and Lenvatinib should be considered for anti-recurrence therapy for patients with HCC and MVI after hepatectomy.

Abstract 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. Graphical Abstract

Abstract Purpose To conduct a head-to-head comparison between deep learning (DL) and radiomics models across institutions for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and to investigate the model robustness and generalizability through rigorous internal and external validation. Methods This retrospective study included 2304 preoperative images of 576 HCC lesions from two centers, with MVI status determined by postoperative histopathology. We developed DL and radiomics models for predicting the presence of MVI using B-mode ultrasound, contrast-enhanced ultrasound (CEUS) at the arterial, portal, and delayed phases, and a combined modality (B + CEUS). For radiomics, we constructed models with enlarged vs. original regions of interest (ROIs). A cross-validation approach was performed by training models on one center’s dataset and validating the other, and vice versa. This allowed assessment of the validity of different ultrasound modalities and the cross-center robustness of the models. The optimal model combined with alpha-fetoprotein (AFP) was also validated. The head-to-head comparison was based on the area under the receiver operating characteristic curve (AUC). Results Thirteen DL models and 25 radiomics models using different ultrasound modalities were constructed and compared. B + CEUS was the optimal modality for both DL and radiomics models. The DL model achieved AUCs of 0.802–0.818 internally and 0.667–0.688 externally across the two centers, whereas radiomics achieved AUCs of 0.749–0.869 internally and 0.646–0.697 externally. The radiomics models showed overall improvement with enlarged ROIs (P 0.05 for all modalities, 1.6–2.1% differences in AUC for the optimal modality), whereas the radiomics models had relatively limited robustness across the two centers (12% drop-off in AUC for the optimal modality). Adding AFP improved the DL models (P 0.05). Conclusion Cross-institutional validation indicated that DL demonstrated better robustness than radiomics for preoperative MVI prediction in patients with HCC, representing a promising solution to non-standardized ultrasound examination procedures.

Abstract Background Hepatocellular carcinoma (HCC) is the most frequent primary liver tumor globally and a leading cause of mortality in cirrhotic patients. Our study aimed to estimate the diagnostic performance of triphasic CT and inter-observer reliability in the preoperative detection of microvascular invasion (MVI) in HCC. Two independent radiologists accomplished a retrospective analysis for 99 patients with HCC to assess the CT features for MVI in each lesion. Postoperative histopathology was considered the gold standard. Results Multivariate regression analysis revealed that incomplete or absent tumor capsules, presence of TTPV, and absence of hypodense halo were statistically significant independent predictors of MVI. There was excellent agreement among observers in evaluating peritumoral enhancement, identifying intratumoral arteries, hypodense halo, TTPV, and macrovascular invasion. Also, our results revealed moderate agreement in assessing the tumor margin and tumor capsule. Conclusion Triphasic CT features of MVI are reliable imaging predictors that may be helpful for standard preoperative interpretation of HCC.

Abstract Background Postoperative recurrence is a vital reason for poor 5-year overall survival in hepatocellular carcinoma (HCC) patients. The ADV score is considered a parameter that can quantify HCC aggressiveness. This study aimed to identify HCC patients at high-risk of recurrence early using the ADV score. Methods The medical data of consecutive HCC patients undergoing hepatectomy from The First Affiliated Hospital of Nanjing Medical University (TFAHNJMU) and Nanjing Drum Tower Hospital (NJDTH) were retrospectively reviewed. Based on the status of microvascular invasion and the Edmondson-Steiner grade, HCC patients were divided into three groups: low-risk group (group 1: no risk factor exists), medium-risk group (group 2: one risk factor exists), and high-risk group (group 3: coexistence of two risk factors). In the training cohort (TFAHNJMU), the R package nnet was used to establish a multi-categorical unordered logistic regression model based on the ADV score to predict three risk groups. The Welch’s T-test was used to compare differences in clinical variables in three predicted risk groups. NJDTH served as an external validation center. At last, the confusion matrix was developed using the R package caret to evaluate the diagnostic performance of the model. Results 350 and 405 patients from TFAHNJMU and NJDTH were included. HCC patients in different risk groups had significantly different liver function and inflammation levels. Density maps demonstrated that the ADV score could best differentiate between the three risk groups. The probability curve was plotted according to the predicted results of the multi-categorical unordered logistic regression model, and the best cut-off values of the ADV score were as follows: low-risk ≤ 3.4 log, 3.4 log 5.7 log. The sensitivities of the ADV score predicting the high-risk group (group 3) were 70.2% (99/141) and 78.8% (63/80) in the training and external validation cohort, respectively. Conclusion The ADV score might become a valuable marker for screening patients at high-risk of HCC recurrence with a cut-off value of 5.7 log, which might help surgeons, pathologists, and HCC patients make appropriate clinical decisions.

Abstract Background In this study, we aimed to establish nomograms to predict the microvascular invasion (MVI) and early recurrence in patients with small hepatocellular carcinoma (SHCC), thereby guiding individualized treatment strategies for prognosis improvement. Methods This study retrospectively analyzed 326 SHCC patients who underwent radical resection at Wuhan Union Hospital between April 2017 and January 2022. They were randomly divided into a training set and a validation set at a 7:3 ratio. The preoperative nomogram for MVI was constructed based on univariate and multivariate logistic regression analysis, and the prognostic nomogram for early recurrence was constructed based on univariate and multivariate Cox regression analysis. We used the receiver operating characteristic (ROC) curves, area under the curves (AUCs), and calibration curves to estimate the predictive accuracy and discriminability of nomograms. Decision curve analysis (DCA) and Kaplan-Meier survival curves were employed to further confirm the clinical effectiveness of nomograms. Results The AUCs of the preoperative nomogram for MVI on the training set and validation set were 0.749 (95%CI: 0.684–0.813) and 0.856 (95%CI: 0.805–0.906), respectively. For the prognostic nomogram, the AUCs of 1-year and 2-year RFS respectively reached 0.839 (95%CI: 0.775–0.903) and 0.856 (95%CI: 0.806–0.905) in the training set, and 0.808 (95%CI: 0.719–0.896) and 0.874 (95%CI: 0.804–0.943) in the validation set. Subsequent calibration curves, DCA analysis and Kaplan-Meier survival curves demonstrated the high accuracy and efficacy of the nomograms for clinical application. Conclusions The nomograms we constructed could effectively predict MVI and early recurrence in SHCC patients, providing a basis for clinical decision-making.

Abstract 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. Graphical Abstract

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. [ABSTRACT FROM AUTHOR]

Background: In recent years, studies have confirmed the predictive capability of spectral computer tomography (CT) in determining microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Discrepancies in the predicted MVI values between conventional CT imaging features and spectral CT parameters necessitate additional validation. Methods: In this retrospective study, 105 cases of small HCC were reviewed, and participants were divided into MVI-negative (n=53, Male:48 (90.57%); mean age, 59.40 ± 11.79 years) and MVI-positive (n=52, Male:50(96.15%); mean age, 58.74 ± 9.21 years) groups using pathological results. Imaging features and iodine density (ID) obtained from three-phase enhancement spectral CT scans were gathered from all participants. The study evaluated differences in imaging features and ID values of HCC between two groups, assessing their diagnostic accuracy in predicting MVI occurrence in HCC patients. Furthermore, the diagnostic efficacy of imaging features and ID in predicting MVI was compared. Results: Significant differences were noted in the presence of mosaic architecture, nodule-in-nodule architecture, and corona enhancement between the groups, all with p-values < 0.001. There were also notable disparities in IDs between the two groups across the arterial phase, portal phase, and delayed phases, all with p-values < 0.001. The imaging features of nodule-in-nodule architecture, corona enhancement, and nonsmooth tumor margin demonstrate significant diagnostic efficacy, with area under the curve (AUC) of 0.761, 0.742, and 0.752, respectively. In spectral CT analysis, the arterial, portal, and delayed phase IDs exhibit remarkable diagnostic accuracy in detecting MVI, with AUCs of 0.821, 0.832, and 0.802, respectively. Furthermore, the combined models of imaging features, ID, and imaging features with ID reveal substantial predictive capabilities, with AUCs of 0.846, 0.872, and 0.904, respectively. DeLong test results indicated no statistically significant differences between imaging features and IDs. Conclusions: Substantial differences were noted in imaging features and ID between the MVI-negative and MVI-positive groups in this study. The ID and imaging features exhibited a robust diagnostic precision in predicting MVI. Additionally, our results suggest that both imaging features and ID showed similar predictive efficacy for MVI. [ABSTRACT FROM AUTHOR]

Background: This retrospective cohort study and meta-analysis aims to explore the association between microvascular invasion (MVI) and clinicopathologiccal features, as well as survival outcomes of patients with renal cell carcinoma (RCC). Material and methods: The retrospective cohort study included 30 RCC patients with positive MVI and another 75 patients with negative MVI as controls. Clinicopathological features and follow-up data were compiled. The metaanalysis conducted searches on PubMed, Cochrane Library, Web of Science, Embase, and WanFang Data from the beginning to 30 September 2023, for comparative studies relevant to MVI patients. The Newcastle-Ottawa Scale and Egger Test were used to assess the risk of biases and certainty of evidence in the included studies. Results: The cohort study showed that MVI was associated with advanced primary tumor stage, high pathological grades, high tumor size, high clinical symptoms and lymph node invasion (P <0.05). Kaplan-Meier analyses demonstrated MVI was associated with worse CSS rates when compared to MVI negative group (P <0.05). However, in the multivariate analysis it was not presented as an independent predictor of cancer survival mortality (P >0.05). The meta-analysis part included 11 cohort studies. The results confirmed that patients with MVI positive had worse 12 and 60 mo CSS rates (HR12mo = 0.86, 95%CI 0.80-0.92; HR60mo = 0.63, 95% CI 0.55-0.72; P < 0.00001). Moreover, the metaanalysis also confirmed that MVI group was associated with higher rate of advanced tumor stage, pathological grades, tumor size diameter, higher rate of clinical symptoms and lymph node invasion (P <0.05). Conclusions: The presence of MVI in renal cell carcinoma patients is linked to poorer survival outcomes and worse clinicopathological features. In spite of this, it does not seem to be an independent predictor for cancer survival mortality in renal cell carcinoma. [ABSTRACT FROM AUTHOR]

Intrahepatic cholangiocarcinoma is a rare disease associated with a poor prognosis, primarily due to early recurrence and metastasis. An important feature of this condition is microvascular invasion (MVI). However, current predictive models based on imaging have limited efficacy in this regard. This study employed a random forest model to construct a predictive model for MVI identification and uncover its biological basis. Single-cell transcriptome sequencing, whole exome sequencing, and proteome sequencing were performed. The area under the curve of the prediction model in the validation set was 0.93. Further analysis indicated that MVI-associated tumor cells exhibited functional changes related to epithelial–mesenchymal transition and lipid metabolism due to alterations in the nuclear factor-kappa B and mitogen-activated protein kinase signaling pathways. Tumor cells were also differentially enriched for the interleukin-17 signaling pathway. There was less infiltration of SLC30A1+ CD8+ T cells expressing cytotoxic genes in MVI-associated intrahepatic cholangiocarcinoma, whereas there was more infiltration of myeloid cells with attenuated expression of the major histocompatibility complex II pathway. Additionally, MVI-associated intercellular communication was closely related to the SPP1–CD44 and ANXA1–FPR1 pathways. These findings resulted in a brilliant predictive model and fresh insights into MVI. [ABSTRACT FROM AUTHOR]

Background and Aim: There is a pressing need for non‐invasive preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). This study investigates the potential of exosome‐derived mRNA in plasma as a biomarker for diagnosing MVI. Methods: Patients with suspected HCC undergoing hepatectomy were prospectively recruited for preoperative peripheral blood collection. Exosomal RNA profiling was conducted using RNA sequencing in the discovery cohort, followed by differential expression analysis to identify candidate targets. We employed multiplexed droplet digital PCR technology to efficiently validate them in a larger sample size cohort. Results: A total of 131 HCC patients were ultimately enrolled, with 37 in the discovery cohort and 94 in the validation cohort. In the validation cohort, the expression levels of RSAD2, PRPSAP1, and HOXA2 were slightly elevated while CHMP4A showed a slight decrease in patients with MVI compared with those without MVI. These trends were consistent with the findings in the discovery cohort, although they did not reach statistical significance (P > 0.05). Notably, the expression level of exosomal PRPSAP1 in plasma was significantly higher in patients with more than 5 MVI than in those without MVI (0.147 vs 0.070, P = 0.035). Conclusion: This study unveils the potential of exosome‐derived PRPSAP1 in plasma as a promising indicator for predicting MVI status preoperatively. [ABSTRACT FROM AUTHOR]

Background: Tumors are heterogenous and consist of subregions, also known as tumoral habitats, each exhibiting varied biological characteristics. Each habitat corresponds to a cluster of tissue sharing similar structural, metabolic, or functional characteristics. The habitat imaging technique facilitates both the visualization and quantification of these tumoral habitats. Purpose: To evaluate the microvascular invasion (MVI) in hepatocellular carcinoma (HCC) (≤5 cm) and assess the recurrence‐free survival (RFS) using gadoxetate disodium‐enhanced MRI‐based habitat imaging. Study Type: Retrospective. Subjects: 180 patients (52.9 years ± 11.7, 156 men) with HCC. Field Strength/Sequence: 1.5T/contrast‐enhanced T1‐weighted gradient‐echo sequence. Assessment: The enhancement ratio of signal intensity at the arterial phase (AER) and hepatobiliary phase (HBPER) were calculated. The HCC lesions and their peritumoral tissues of 3, 5, and 7 mm were encoded into four habitats. The volume fraction of each habitat was then quantified. The diagnostic performance was assessed using the receiver operating characteristic analysis with 5‐fold cross‐validation. The RFS was evaluated with Kaplan–Meier curves. Results: Habitat 2 (with median to high AER and low HBPER) within the peritumoral tissue of 3 mm (f2‐P3) and tumor diameter could serve as independent risk factors for MVI and showed the statistical significance (odds ratio (OR) of f2‐P3 = 1.170, 95% CI = 1.099–1.246; OR of tumor diameter: 6.112, 95% CI = 2.162–17.280). A nomogram was developed by incorporating f2‐P3 and tumor diameter, demonstrating high diagnostic accuracy. The area under the curve from 5‐fold cross‐validation ranged from 0.880 to 1.000. Additionally, the nomogram model demonstrated high efficacy in risk stratification for RFS. Conclusion: Habitat imaging of HCC and its peritumoral microenvironment has the potential for noninvasive and preoperative identification of MVI and prognostic assessment. Level of Evidence: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Background: Postoperative recurrence is a vital reason for poor 5-year overall survival in hepatocellular carcinoma (HCC) patients. The ADV score is considered a parameter that can quantify HCC aggressiveness. This study aimed to identify HCC patients at high-risk of recurrence early using the ADV score. Methods: The medical data of consecutive HCC patients undergoing hepatectomy from The First Affiliated Hospital of Nanjing Medical University (TFAHNJMU) and Nanjing Drum Tower Hospital (NJDTH) were retrospectively reviewed. Based on the status of microvascular invasion and the Edmondson-Steiner grade, HCC patients were divided into three groups: low-risk group (group 1: no risk factor exists), medium-risk group (group 2: one risk factor exists), and high-risk group (group 3: coexistence of two risk factors). In the training cohort (TFAHNJMU), the R package nnet was used to establish a multi-categorical unordered logistic regression model based on the ADV score to predict three risk groups. The Welch's T-test was used to compare differences in clinical variables in three predicted risk groups. NJDTH served as an external validation center. At last, the confusion matrix was developed using the R package caret to evaluate the diagnostic performance of the model. Results: 350 and 405 patients from TFAHNJMU and NJDTH were included. HCC patients in different risk groups had significantly different liver function and inflammation levels. Density maps demonstrated that the ADV score could best differentiate between the three risk groups. The probability curve was plotted according to the predicted results of the multi-categorical unordered logistic regression model, and the best cut-off values of the ADV score were as follows: low-risk ≤ 3.4 log, 3.4 log < medium-risk ≤ 5.7 log, and high-risk > 5.7 log. The sensitivities of the ADV score predicting the high-risk group (group 3) were 70.2% (99/141) and 78.8% (63/80) in the training and external validation cohort, respectively. Conclusion: The ADV score might become a valuable marker for screening patients at high-risk of HCC recurrence with a cut-off value of 5.7 log, which might help surgeons, pathologists, and HCC patients make appropriate clinical decisions. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the predominant form of primary liver cancer, accounting for approximately 90% of liver cancer cases. It currently ranks as the fifth most prevalent cancer worldwide and represents the third leading cause of cancer-related mortality. As a malignant disease with surgical resection and ablative therapy being the sole curative options available, it is disheartening that most HCC patients who undergo liver resection experience relapse within five years. Microvascular invasion (MVI), defined as the presence of micrometastatic HCC emboli within liver vessels, serves as an important histopathological feature and indicative factor for both disease-free survival and overall survival in HCC patients. Therefore, achieving accurate preoperative noninvasive prediction of MVI holds vital significance in selecting appropriate clinical treatments and improving patient prognosis. Currently, there are no universally recognized criteria for preoperative diagnosis of MVI in clinical practice. Consequently, extensive research efforts have been directed towards preoperative imaging prediction of MVI to address this problem and the relative research progresses were reviewed in this article to summarize its current limitations and future research prospects. [ABSTRACT FROM AUTHOR]

Objective: To explore the application value of magnetic resonance imaging (MRI) multi-sequence scan in the diagnosis of hepatocellular carcinoma (HCC) and evaluation of microvascular invasion (MVI). Methods: A retrospective collection was performed on the clinical data of 100 patients with suspected HCC in the hospital between October 2019 and October 2022. All completed MRI multi-sequence scan and pathological examination. Taking pathological examination as the golden standard, the consistency between MRI multi-sequence scan and pathological examination in the diagnosis of HCC and evaluation of MVI was analyzed by Kappa test. Results: Among the 100 patients, pathological examination showed that there were 51 cases (51.00%) with HCC and 49 cases (49.00%) with benign liver lesions. In the 51 HCC patients, there were 17 cases (33.33%) with MVI. Taking pathological examination as the golden standard, sensitivity, specificity and Kappa values of T2WI in the diagnosis of HCC and MVI were (82.35%, 79.59%, 0.620) and (64.71%, 85.29%, 0.507), respectively. The sensitivity, specificity and Kappa values of TIWI in the diagnosis of HCC and MVI were (76.47%, 81.63%, 0.580) and (58.82%, 88.24%, 0.492), respectively. The sensitivity, specificity and Kappa values of LAVA in the diagnosis of HCC and MVI were (84.31%, 83.67%, 0.580) and (64.71%, 91.18%, 0.585), respectively. The sensitivity, specificity and Kappa values of MRI multi-sequence scan in the diagnosis of HCC and MVI were (96.08%, 79.59%, 0.759) and (94.12%, 82.35%, 0.712), respectively. The sensitivity of MRI multi-sequence scan was higher than that of single sequence (P<0.05). The proportions of unsmooth tumor edge and peritumoral enhancement in patients with MVI positive were higher than those with MVI negative (P<0.05). Conclusion: MRI multi-sequence scan is conductive to clinical diagnosis of HCC and evaluation of MVI. Unsmooth tumor edge and peritumoral enhancement have predictive significance in HCC and MVI. [ABSTRACT FROM AUTHOR]

Objective: To validate a risk score model to predict MVI using Total tumor volume (TTV) and AFP. Study Design: Cross-sectional. Setting: Department of Gastroenterology, Liaquat National Hospital, Karachi, Pakistan. Period: June 2022 to December, 2023. Methods: Patients of either gender, older than 18 years and above with confirmed diagnosis of HCC were enrolled. When there were several HCC tumors, the largest tumor’s axis was measured and used as the representative HCC diameter. When microscopic tumor invasion was detected in the portal, hepatic vein, or biliary vein of the surrounding liver tissue that was adjacent to the tumor, it was referred to as micro vascular invasion. Results: Total 302 patients were studied with mean age of 62.1 ± 9.2 years. Majority of patients were males (64.2%). Around one-fifth patients had more than one tumor (19.9%). Out of 302 patients, MVI was seen in 30.1% patients. In multivariable analysis number of tumors (aOR=220.65, 95% CI: 128.91-922.67), tumor volume (aOR=1.01, 95% CI: 1.01-1.02), and AFP (aOR=1.01, 95% CI: 1-1.02) were found to be significant predictors of MVI. Conclusion: This study validated a prediction model for forecasting of MVI in HCC patients with highly significant variables including number of tumors, tumor volume and alpha feto protein. Timely decision making could be done using this model. [ABSTRACT FROM AUTHOR]

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). 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. 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%. 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. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is the most frequent primary liver tumor globally and a leading cause of mortality in cirrhotic patients. Our study aimed to estimate the diagnostic performance of triphasic CT and inter-observer reliability in the preoperative detection of microvascular invasion (MVI) in HCC. Two independent radiologists accomplished a retrospective analysis for 99 patients with HCC to assess the CT features for MVI in each lesion. Postoperative histopathology was considered the gold standard. Results: Multivariate regression analysis revealed that incomplete or absent tumor capsules, presence of TTPV, and absence of hypodense halo were statistically significant independent predictors of MVI. There was excellent agreement among observers in evaluating peritumoral enhancement, identifying intratumoral arteries, hypodense halo, TTPV, and macrovascular invasion. Also, our results revealed moderate agreement in assessing the tumor margin and tumor capsule. Conclusion: Triphasic CT features of MVI are reliable imaging predictors that may be helpful for standard preoperative interpretation of HCC. [ABSTRACT FROM AUTHOR]

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

Objective To investigate the efficacy and safety of drug-eluting bead transarterial chemoembolization (DEB- TACE) as neoadjuvant therapy before liver transplantation (LT) in patients with hepatocellular carcinoma (HCC) beyond Milan criteria with microvascular invasion (MVI) and its impact on the prognosis after LT. Methods From May 2016 to December 2022, 141 patients with HCC beyond Milan criteria underwent LT. A total of 55 patients with MVI were enrolled in the study and were divided into DEB-TACE before LT group (n=26) and control group (n=29) that did not receive any treatment before LT. The Kaplan-Meier method was utilized to estimate the overall survival (OS) rate and recurrence-free survival (RFS) rate after LT after potential prognostic factors for RFS and OS were identified. Results The objective response rate after DEB-TACE was 88%, and the main adverse event was embolization syndrome. The 1-, 2- and 3-year RFS rates in DEB-TACE group (88.5%, 79.2% and 73.9%) were higher than control group (69%, 50% and 44.4%). The 3-year RFS rate was significantly different between the two groups (χ²= 4.428, P=0.035). The 1-, 2- and 3-year OS rates in DEB-TACE group (100%, 91.7% and 82.6%) were not significantly (χ²=3.224, P=0.073) higher than control group (96.6%, 82.1% and 59.3%). Conclusion Preoperative DEB-TACE neoadjuvant therapy can improve the prognosis of LT in patients with HCC beyond Milan criteria with MVI. [ABSTRACT FROM AUTHOR]

Background: Microvascular invasion (MVI) stands as a pivotal pathological hallmark of hepatocellular carcinoma (HCC), closely linked to unfavorable prognosis, early recurrence, and metastatic progression. However, the precise mechanistic underpinnings governing its onset and advancement remain elusive. Methods: In this research, we downloaded bulk RNA-seq data from the TCGA and HCCDB repositories, single-cell RNA-seq data from the GEO database, and spatial transcriptomics data from the CNCB database. Leveraging the Scissor algorithm, we delineated prognosis-related cell subpopulations and discerned a distinct MVI-related malignant cell subtype. A comprehensive exploration of these malignant cell subpopulations was undertaken through pseudotime analysis and cell-cell communication scrutiny. Furthermore, we engineered a prognostic model grounded in MVI-related genes, employing 101 algorithm combinations integrated by 10 machine-learning algorithms on the TCGA training set. Rigorous evaluation ensued on internal testing sets and external validation sets, employing C-index, calibration curves, and decision curve analysis (DCA). Results: Pseudotime analysis indicated that malignant cells, showing a positive correlation with MVI, were primarily concentrated in the early to middle stages of differentiation, correlating with an unfavorable prognosis. Importantly, these cells showed significant enrichment in the MYC pathway and were involved in extensive interactions with diverse cell types via the MIF signaling pathway. The association of malignant cells with the MVI phenotype was corroborated through validation in spatial transcriptomics data. The prognostic model we devised demonstrated exceptional sensitivity and specificity, surpassing the performance of most previously published models. Calibration curves and DCA underscored the clinical utility of this model. Conclusions: Through integrated multi-transcriptomics analysis, we delineated MVI-related malignant cells and elucidated their biological functions. This study provided novel insights for managing HCC, with the constructed prognostic model offering valuable support for clinical decision-making. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

OBJECTIVE: This study aimed to investigate the feasibility of using dual-layer spectral CT multi-parameter feature to predict microvascular invasion of hepatocellular carcinoma. METHODS: This retrospective study enrolled 50 HCC patients who underwent multiphase contrast-enhanced spectral CT studies preoperatively. Combined clinical data, radiological features with spectral CT quantitative parameter were constructed to predict MVI. ROC was applied to identify potential predictors of MVI. The CT values obtained by simulating the conventional CT scans with 70 keV images were compared with those obtained with 40 keV images. RESULTS: 50 hepatocellular carcinomas were detected with 30 lesions (Group A) with microvascular invasion and 20 (Group B) without. There were significant differences in AFP,tumer size, IC, NIC,slope and effective atomic number in AP and ICrr in VP between Group A ((1000(10.875,1000),4.360±0.3105, 1.7750 (1.5350,1.8825) mg/ml, 0.1785 (0.1621,0.2124), 2.0362±0.2108,8.0960±0.1043,0.2830±0.0777) and Group B (4.750(3.325,20.425),3.190±0.2979,1.4700 (1.4500,1.5775) mg/ml, 0.1441 (0.1373,0.1490),1.8601±0.1595, 7.8105±0.7830 and 0.2228±0.0612) (all p < 0.05). Using 0.1586 as the threshold for NIC, one could obtain an area-under-curve (AUC) of 0.875 in ROC to differentiate between tumours with and without microvascular invasion. AUC was 0.625 with CT value at 70 keV and improved to 0.843 at 40 keV. CONCLUSION: Dual-layer spectral CT provides additional quantitative parameters than conventional CT to enhance the differentiation between hepatocellular carcinoma with and without microvascular invasion. Especially, the normalized iodine concentration (NIC) in arterial phase has the greatest potential application value in determining whether microvascular invasion exists, and can offer an important reference for clinical treatment plan and prognosis assessment. [ABSTRACT FROM AUTHOR]

Background: Microvascular invasion (MVI) is a risk factor for postoperative recurrence of hepatocellular carcinoma (HCC), even in early-stage HCC. In small HCC ≤ 3 cm, treatment options include anatomical resection or non-anatomical resection, and MVI has a major effect on treatment decisions. We aimed to identify the predictors of MVI in small HCC ≤ 3 cm. Methods: We retrospectively studied 129 patients with very early or early-stage HCC ≤ 3 cm who had undergone 18F-fluorodeoxyglucose positron emission tomography/computed tomography and subsequent hepatic resection from January 2016 to August 2023. These patients were divided into the derivation cohort (n = 86) and validation cohort (n = 43). We examined the risk factors for MVI using logistic regression analysis, and established a predictive scoring system in the derivation cohort. We evaluated the accuracy of our scoring system in the validation cohort. Results: In the derivation cohort, a Lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3), prothrombin induced by vitamin K deficiency or antagonist-II (PIVKA-II), and metabolic tumor volume (MTV) were independent predictors of MVI. We established the scoring system using these three factors. In the validation test, there were no MVI-positive cases with a score of 0 and 1, and all cases were MVI-positive with a score of 4. Moreover, with a score ≥ 2, the sensitivity, specificity, and accuracy of our scoring system were 100%, 71.4%, and 81.4%, respectively. Conclusions: Our scoring system can accurately predict MVI in small HCC ≤ 3 cm, and could contribute to establishing an appropriate treatment strategy. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: In this study, we aimed to establish nomograms to predict the microvascular invasion (MVI) and early recurrence in patients with small hepatocellular carcinoma (SHCC), thereby guiding individualized treatment strategies for prognosis improvement. Methods: This study retrospectively analyzed 326 SHCC patients who underwent radical resection at Wuhan Union Hospital between April 2017 and January 2022. They were randomly divided into a training set and a validation set at a 7:3 ratio. The preoperative nomogram for MVI was constructed based on univariate and multivariate logistic regression analysis, and the prognostic nomogram for early recurrence was constructed based on univariate and multivariate Cox regression analysis. We used the receiver operating characteristic (ROC) curves, area under the curves (AUCs), and calibration curves to estimate the predictive accuracy and discriminability of nomograms. Decision curve analysis (DCA) and Kaplan-Meier survival curves were employed to further confirm the clinical effectiveness of nomograms. Results: The AUCs of the preoperative nomogram for MVI on the training set and validation set were 0.749 (95%CI: 0.684–0.813) and 0.856 (95%CI: 0.805–0.906), respectively. For the prognostic nomogram, the AUCs of 1-year and 2-year RFS respectively reached 0.839 (95%CI: 0.775–0.903) and 0.856 (95%CI: 0.806–0.905) in the training set, and 0.808 (95%CI: 0.719–0.896) and 0.874 (95%CI: 0.804–0.943) in the validation set. Subsequent calibration curves, DCA analysis and Kaplan-Meier survival curves demonstrated the high accuracy and efficacy of the nomograms for clinical application. Conclusions: The nomograms we constructed could effectively predict MVI and early recurrence in SHCC patients, providing a basis for clinical decision-making. [ABSTRACT FROM AUTHOR]

Background: The accurate identification of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) is of great clinical importance. Purpose: To develop a radiomics nomogram based on susceptibility-weighted imaging (SWI) and T2-weighted imaging (T2WI) for predicting MVI in early-stage (Barcelona Clinic Liver Cancer stages 0 and A) HCC patients. Materials and methods: A prospective cohort of 189 participants with HCC was included for model training and testing, and an additional 34 participants were enrolled for external validation. ITK-SNAP was used to manually segment the tumour, and PyRadiomics was used to extract radiomic features from the SWI and T2W images. Variance filtering, student's t test, least absolute shrinkage and selection operator regression and random forest (RF) were applied to select meaningful features. Four machine learning classifiers, including K-nearest neighbour, RF, logistic regression and support vector machine-based models, were established. Independent clinical and radiological risk factors were also determined to establish a clinical model. The best radiomics and clinical models were further evaluated in the validation set. In addition, a nomogram was constructed from the radiomic model and independent clinical factors. Diagnostic efficacy was evaluated by receiver operating characteristic curve analysis with fivefold cross-validation. Results: AFP levels greater than 400 ng/mL [odds ratio (OR) 2.50; 95% confidence interval (CI) 1.239–5.047], tumour diameter greater than 5 cm (OR 2.39; 95% CI 1.178–4.839), and absence of pseudocapsule (OR 2.053; 95% CI 1.007–4.202) were found to be independent risk factors for MVI. The areas under the curve (AUCs) of the best radiomic model were 1.000 and 0.882 in the training and testing cohorts, respectively, while those of the clinical model were 0.688 and 0.6691. In the validation set, the radiomic model achieved better diagnostic performance (AUC = 0.888) than the clinical model (AUC = 0.602). The combination of clinical factors and the radiomic model yielded a nomogram with the best diagnostic performance (AUC = 0.948). Conclusion: SWI and T2WI-derived radiomic features are valuable for noninvasively and accurately identifying MVI in early-stage HCC. Furthermore, the integration of radiomics and clinical factors yielded a predictive nomogram with satisfactory diagnostic performance and potential clinical benefits. [ABSTRACT FROM AUTHOR]

BackgroundThis study aims to investigate the clinicopathological and ultrasonography characteristics of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and its correlation with microvascular invasion (MVI), as well as the predictive value of contrast-enhanced ultrasound (CEUS) imaging.MethodsA retrospective analysis was conducted on 57 patients diagnosed with cHCC-CCA between November 2017 and May 2023 at Guizhou Provincial People’s Hospital. Among them, 27 patients were MVI-positive and 30 patients were MVI-negative, all of whom underwent preoperative CEUS within 2 weeks. Clinical data, ultrasonographic findings, and CEUS features were compared between the two groups to analyze the influencing factors and predictive value of MVI in cHCC-CCA patients.ResultsCompared to the MVI-negative group, the MVI-positive group showed a higher proportion of tumors with a maximum diameter greater than 5 cm, elevated alpha-fetoprotein (AFP) levels, low echo halo around the tumor, non-smooth tumor contour, peripheral irregular rim-like enhancement and early washout (≤60s) with nodular patterns on CEUS (P

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.

Abstract Background Hepatocellular carcinoma (HCC) is one of the deadliest malignant tumors in China. Microvascular invasion (MVI) often indicates poor prognosis and metastasis in HCC patients. 18F-FDG PET–CT is a new imaging method commonly used to screen for tumor occurrence and evaluate tumor stage. Purpose This study attempted to predict the occurrence of MVI in early-stage HCC through 18F-FDG positron emission tomography (PET)/computed tomography (CT) imaging findings and laboratory data. Patients and methods A total of 113 patients who met the inclusion criteria were divided into two groups based on postoperative pathology: the MVI-positive group and MVI-negative group. We retrospectively analyzed the imaging findings and laboratory data of 113 patients. Imaging findings included tumor size, tumor maximum standard uptake value (SUVmaxT), and normal liver maximum standard uptake value (SUVmaxL). The ratios of SUVmaxT to SUVmaxL (SUVmaxT/L) and an SUVmaxT/L > 2 were defined as active tumor metabolism. The tumor size was indicated by the maximum diameter of the tumor, and a diameter greater than 5 cm was defined as a mass lesion. The laboratory data included the alpha-fetoprotein (AFP) level and the HBeAg level. An AFP concentration > 20 ng/mL was defined as a high AFP level. A HBeAg concentration > 0.03 NCU/mL was defined as HB-positive. Results The SUVmaxT/L (p = 0.003), AFP level (p = 0.008) and tumor size (p = 0.015) were significantly different between the two groups. Patients with active tumor metabolism, mass lesions and high AFP levels tended to be MVI positive. Binary logistic regression analysis verified that active tumor metabolism (OR = 4.124, 95% CI, 1.566–10.861; p = 0.004) and high AFP levels (OR = 2.702, 95% CI, 1.214–6.021; p = 0.015) were independent risk factors for MVI. The sensitivity of the combination of these two independent risk factors predicting HCC with MVI was 56.9% (29/51), the specificity was 83.9% (52/62) and the accuracy was 71.7% (81/113). Conclusion Active tumor metabolism and high AFP levels can predict the occurrence of MVI in HCC patients.

Robin Schmidt,1,2 Charlie Alexander Hamm,1,3 Christopher Rueger,1 Han Xu,1 Yubei He,1,2 Luzie Alexandra Gottwald,4 Bernhard Gebauer,1 Lynn Jeanette Savic1– 3 1Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, 13353, Germany; 2Experimental Clinical Research Center (ECRC) at Charité - Universitätsmedizin Berlin and Max-Delbrück-Centrum für Molekulare Medizin (MDC), Berlin, 13125, Germany; 3Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, 10117, Germany; 4Vivantes Humboldt-Klinikum, Berlin, 13509, GermanyCorrespondence: Lynn Jeanette Savic, Charité Universitätsmedizin Berlin, Campus Virchow Klinikum, Klinik für Radiologie, Augustenburger Platz 1, Berlin, D-13353, Germany, Email lynn-jeanette.savic@charite.dePurpose: Histological microvascular invasion (MVI) is a risk factor for poor survival and early recurrence in hepatocellular carcinoma (HCC) after surgery. Its prognostic value in the setting of locoregional therapies (LRT), where no tissue samples are obtained, remains unknown. This study aims to establish CT-derived indices indicative of MVI on liver MRI with superior soft tissue contrast and evaluate their association with patient survival after ablation via interstitial brachytherapy (iBT) versus iBT combined with prior conventional transarterial chemoembolization (cTACE).Patients and Methods: Ninety-five consecutive patients, who underwent ablation via iBT alone (n = 47) or combined with cTACE (n = 48), were retrospectively included between 01/2016 and 12/2017. All patients received contrast-enhanced MRI prior to LRT. Overall (OS), progression-free survival (PFS), and time-to-progression (TTP) were assessed. Decision-tree models to determine Radiogenomic Venous Invasion (RVI) and Two-Trait Predictor of Venous Invasion (TTPVI) on baseline MRI were established, validated on an external test set (TCGA-LIHC), and applied in the study cohorts to investigate their prognostic value for patient survival. Statistics included Fisher’s exact and t-test, Kaplan–Meier and cox-regression analysis, area under the receiver operating characteristic curve (AUC-ROC) and Pearson’s correlation.Results: OS, PFS, and TTP were similar in both treatment groups. In the external dataset, RVI showed low sensitivity but relatively high specificity (AUC-ROC = 0.53), and TTPVI high sensitivity but only low specificity (AUC-ROC = 0.61) for histological MVI. In patients following iBT alone, positive RVI and TTPVI traits were associated with poorer OS (RVI: p < 0.01; TTPVI: p = 0.08), PFS (p = 0.04; p = 0.04), and TTP (p = 0.14; p = 0.03), respectively. However, when patients with combined cTACE and iBT were stratified by RVI or TTPVI, no differences in OS (p = 0.75; p = 0.55), PFS (p = 0.70; p = 0.43), or TTP (p = 0.33; p = 0.27) were observed.Conclusion: The study underscores the role of non-invasive imaging biomarkers indicative of MVI to identify patients, who would potentially benefit from embolotherapy via cTACE prior to ablation rather than ablation alone.Keywords: cancer imaging, hepatocellular carcinoma, microvascular invasion, magnetic resonance tomography, predictive imaging biomarkers

Abstract Aim Tumor budding (TB) has excellent prognostic value in many solid tumors, but there is little research on it in hepatocellular carcinoma (HCC). This study assessed the prognostic value of TB in patients with HCC who received hepatectomy. Methods This retrospective study included 210 patients with HCC who received curative hepatectomy at the First Affiliated Hospital of Xi'an Jiaotong University, between 2016 and 2018. TB was evaluated on hematoxylin‐ and eosin‐stained slides according to the criteria established by the 2016 International Tumor Budding Consensus Conference. t‐tests, Chi‐squared tests, and rank‐sum tests were used to correlate the extent of TB with clinicopathological parameters. Prognostic analysis was performed using Cox regression models and the Kaplan–Meier method. Results The positive detection rate of TB was 45.2% (95/210) in 210 patients with HCC. Patients positive for TB always exhibit lower tumor differentiation, higher hepatitis B virus DNA levels, and more severe liver fibrosis. Multivariate Cox analysis identified TB (hazard ratio [HR]: 2.232, 95% confidence interval [CI]: 1.479–3.368, p

Zhao Zhang, Xiu-Fen Jia, Xiao-Yu Chen, Yong-Hua Chen, Ke-Hua Pan Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of ChinaCorrespondence: Ke-Hua Pan, Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, No. 1 of Xuefu North Road, Wenzhou, Ouhai District, 325000, People’s Republic of China, Tel +86-577-8806 9618, Fax +86-577-8806 9655, Email pankehuapan@126.comObjective: The aim of this study is to develop and verify a magnetic resonance imaging (MRI)-based radiomics model for predicting the microvascular invasion grade (MVI) before surgery in individuals diagnosed with nodular hepatocellular carcinoma (HCC).Methods: A total of 198 patients were included in the study and were randomly stratified into two groups: a training group consisting of 139 patients and a test group comprising 59 patients. The tumor lesion was manually segmented on the largest cross-sectional slice using ITK SNAP, with agreement reached between two radiologists. The selection of radiomics features was carried out using the LASSO (Least Absolute Shrinkage and Selection Operator) algorithm. Radiomics models were then developed through maximum correlation, minimum redundancy, and logistic regression analyses. The performance of the models in predicting MVI grade was assessed using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix.Results: There were no notable statistical differences in sex, age, BMI (body mass index), tumor size, and location between the training and test groups. The AP and PP radiomic model constructed for predicting MVI grade demonstrated an AUC of 0.83 (0.75– 0.88) and 0.73 (0.64– 0.80) in the training group and an AUC of 0.74 (0.61– 0.85) and 0.62 (0.48– 0.74) in test group, respectively. The combined model consists of imaging data and clinical data (age and AFP), achieved an AUC of 0.85 (0.78– 0.91) and 0.77 (0.64– 0.87) in the training and test groups, respectively.Conclusion: A radiomics model utilizing-contrast-enhanced MRI demonstrates strong predictive capability for differentiating MVI grades in individuals with nodular HCC. This model could potentially function as a dependable and resilient tool to support hepatologists and radiologists in their preoperative decision-making processes.Keywords: hepatocellular carcinoma, magnetic resonance imaging, microvascular invasion, radiomics

Abstract 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