Risk Factors For Microvascular Invasion Research Articles

The value of varying diffusion curvature MRI for assessing the microvascular invasion of hepatocellular carcinoma.

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). 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. MVI-positive HCCs exhibited significantly higher VDC-derived structural heterogeneity measure, D1 (0.680 ± 0.100 × 10-3 vs 0.572 ± 0.148 × 10-3mm2/s, p = 0.001) and lower apparent diffusion coefficient (ADC) (1.350 ± 0.166 × 10-3 vs 1.471 ± 0.322 × 10-3mm2/s, p = 0.0495) compared to MVI-negative HCCs. No statistical significance was observed for VDC-derived diffusion coefficient, D0 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 D1, ADC, tumor size, and AFP, which exhibited the highest diagnostic accuracy (AUC = 0.817), followed by D1 (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. 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.

Preoperative prediction of microvascular invasion in hepatocellular carcinoma using diffusion-weighted imaging-based habitat imaging.

Habitat imaging allows for the quantification and visualization of various subregions within the tumor. We aim to develop an approach using diffusion-weighted imaging (DWI)-based habitat imaging for preoperatively predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Sixty-five patients were prospectively included and underwent multi-b DWI examinations. Based on the true diffusion coefficient (Dt), perfusion fraction (f), and mean kurtosis coefficient (MK), which respectively characterize cellular density, perfusion, and heterogeneity, the HCCs were divided into four habitats. The volume fraction of each habitat was quantified. The logistic regression was used to explore the risk factors from habitat fraction and clinical variables. Clinical, habitat, and nomogram models were constructed using the identified risk factors from clinical characteristics, habitat fraction, and their combination, respectively. The diagnostic accuracy was evaluated using the area under the receiver operating characteristic curves (AUCs). MVI-positive HCC exhibited a significantly higher fraction of habitat 4 (f4) and a significantly lower fraction of habitat 2 (f2) (p < 0.001), which were selected as risk factors. Additionally, tumor size and elevated alpha-fetoprotein (AFP) were also included as risk factors for MVI. The nomogram model demonstrated the highest diagnostic performance (AUC = 0.807), followed by the habitat model (AUC = 0.777) and the clinical model (AUC = 0.708). Decision curve analysis indicated that the nomogram model offered more net benefit in identifying MVI compared to the clinical model. DWI-based habitat imaging shows clinical potential for noninvasively and preoperatively determining the MVI of HCC with high accuracy. The proposed strategy, diffusion-weighted imaging-based habitat imaging, can be applied for preoperatively and noninvasively identifying microvascular invasion in hepatocellular carcinoma, which offers potential benefits in terms of prognostic prediction and clinical management. • This study proposed a strategy of DWI-based habitat imaging for hepatocellular carcinoma. • The habitat imaging-derived metrics can serve as diagnostic markers for identifying the microvascular invasion. • Integrating the habitat-based metric and clinical variable, a predictive nomogram was constructed and displayed high accuracy for predicting microvascular invasion.

The value of nomogram for predicting microvascular invasion based on clinical and Gd-EOB-DTPA-enhanced magnetic resonance imaging features

Objective: To investigate the risk factors of microvascular invasion (MVI) in China liver cancer staging system stage Ⅰa (CNLC Ⅰa) hepatocellular carcinoma (HCC), and develop a nomogram for predicting MVI based on clinical and radiographic data. Methods: This retrospective study focused on CNLC Ⅰa HCC patients who underwent radical resection at the Cancer Hospital, Chinese Academy of Medical Sciences from January 2016 to December 2020. Patients' clinical characteristics and laboratory test results and pre-surgery gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging results were collected. The clinical and radiographic risk factors for MVI were identified by univariate and multivariate logistic regression analyses and used for the construction of the predictive nomogram. The nomogram model was then internally validated, and its performance was assessed. Results: A total of 104 patients were divided into the MVI-positive group (n=28) and the MVI-negative group (n=76). Multivariate logistic regression analysis at the P<0.1 level identified serum alpha-ferroprotein >7 ng/ml, total bilirubin >21 μmol/L, prothrombin time >12.5 s, non-smooth margin, and incomplete or absent capsule as risk factors of MVI, based on which a nomogram model was built. The model achieved an area under the curve (AUC) value of 0.867 (95% confidence interval, 0.791-0.944) in the internal validation. The sensitivity and specificity of the nomogram model were 0.786 and 0.829, respectively, with the prediction curve nearly overlapping the ideal curve. Based on the Hosmer-Lemeshow test, the predicted and real results were not significantly different (P=0.956). Conclusions: The probability of MVI of CNLC Ⅰa HCC can be objectively predicted by the monogram model that quantifies the clinical and radiographic risk factors. The model can also help clinicians select individualized surgical plans to improve the long-term prognosis of patients.

Prognostic analysis of postoperative pathological microvascular invasion in hepatocellular carcinoma and the effect of surgical margin on prognosis.

52 Background: To analyze the impact of different MVI grades and surgical margins on patient survival through analyzing the presence of microvascular invasion (MVI) after liver resection of hepatocellular carcinoma (HCC). Methods: The clinical and follow-up data of 513 HCC patients who underwent hepatectomy in our department from January 2016 to December 2020 were analyzed retrospectively. All the patients signed the informed consent form, complying with the medical ethics regulations. Risk factors of MVI in patients with HCC were analyzed by univariate and multivariate analysis, and effect of different MVI grades on postoperative complications was explored. The effects of different MVI grades and different surgical margins on tumor-free survival and overall survival were also analyzed. Results: There were 332 cases in M0 group, 123 cases in M1 group and 58 cases in M2 group. Univariate analysis showed that tumor diameter, tumor number, CNCL stage and alpha-fetoprotein were risk factors for MVI in patients with HCC, and multivariate analysis showed that tumor maximum diameter, tumor number and CNLC stage were independent influencing factors for MVI. There was no significant difference in the incidence of postoperative complications among different groups. The 1-year, 2-year, 3-year disease-free survival rate of M0 group was 79.6%, 71.0%, 63.4%, which was significantly higher than that in M1 group (59.6%, 48.0%，43.3%) and M2 group (31.0%, 27.5%, 25.2%). The 1-year, 2-year, 3-year overall survival rate of M0 group was 97.3%, 88.2%, 84.6%, which was significantly higher than that in M1 group (87.0%, 71.5%, 66.1%), and M2 group (79.3%, 61.9%, 52.6%),respectively. In the aspect of surgical margin, in MVI negative group, the disease-free survival rate of wide margin resection for 1-year, 2-year, 3-year was 82.6%, 70.7%, 65.4%, while that of narrow margin resection was 79.4%, 64.7% and 60.5% (p=0.322).The 1-year, 2-year, 3-year overall survival rate of patients who received wide margin resection was 97.5%, 89.6%, 85.2%, while that of patients who received narrow margin resection was 97.1%, 86.0%，82.8%. (p= 0.822). In the MVI positive group, the 1-year, 2-year and 3-year disease-free survival rate was 58.1%, 45.4%, 40.3% in the wide margin group and 42.9%, 37.3%, 36.1% in the narrow margin group (p=0. 044). The 1-year, 2-year, 3-year overall survival rate of the wide margin group was 88.8%, 71.9%, 64.3%, which was higher than that of the narrow margin group, 82.6%, 64.8%, 61.0% (p = 0.032). Conclusions: Tumor size, number and stage are independent risk factors for MVI positive patients.The higher the MVI grade, the worse the prognosis.In patients with MVI, the long-term prognosis of patients with wide margin is better than that of patients with narrow margin. Therefore, for patients with high risk of MVI before operation, wide margin should be selected as far as possible.

Retracted: Analysis of Related Risk Factors of Microvascular Invasion in Hepatocellular Carcinoma.

[This retracts the article DOI: 10.1155/2022/8195512.].

Parameters Predicting Microvascular Invasion and Poor Differentiation in Hepatocellular Carcinoma Patients with Normal Alpha-fetoprotein Level Before Liver Transplantation.

The aim of this study is to evaluate the parameters that might be associated with pathologically diagnosed microvascular invasion and poor differentiation, using complete blood count and routine clinical biochemistry test results, in hepatocellular carcinoma patients before liver transplantation. The data of patients who underwent liver transplantation for hepatocellular carcinoma at our institute, between March 2006 and November 2021, was researched retrospectively. The incidence of microvascular invasion was 28.6%, poor differentiation rate was 9.3%, hepatocellular carcinoma recurrence rate after liver transplantation was 12.1%, and median time to recurrence was 13 months, in the patients with normal alpha-fetoprotein levels. After univariate and multivariate analysis, maximum tumor diameter > 4.5 cm and the number of nodules (n > 5) were found to be independent risk factors for microvascular invasion, and number of nodules > 4 and mean platelet volume ≤8.6 fL were found to be independent risk factors for poor differentiation. Serum alpha-fetoprotein levels were still within the normal range at the recurrence time, in 53% of the patients who had recurrence after liver transplantation, but surprisingly were elevated in 47% of the patients at time of hepatocellular carcinoma recurrence. In hepatocellular carcinoma patients with normal alpha-fetoprotein levels before liver transplantation, independent risk factors of the presence of microvascular invasion were maximum tumor diameter and number of nodules, and independent risk factors of poor differentiation were mean platelet volume and number of nodules. Furthermore, serum alpha-fetoprotein levels were still normal at time of recurrence in 53% of hepatocellular carcinoma patients whose alpha-fetoprotein levels were normal before liver transplantation but were elevated in 47% of the patients at recurrence time, despite having normal levels before liver transplantation.

Analysis of Related Risk Factors of Microvascular Invasion in Hepatocellular Carcinoma.

Objective To forecast the onset of microvascular invasion (MVI) in patients with hepatoma by evaluating the preoperative aspartate aminotransferase-to-platelet ratio index (APRI), alpha-fetoprotein (AFP), neutrophil-to-lymphocyte ratio (NLR), and other clinicopathological data. Methods In this study, we retrospectively analysed the clinical data of 62 patients who received radical surgery for hepa toma from 2019 to 2021. Patients were separated into the MVI-negative group and the MVI-positive group according to the postoperative pathological diagnosis. The relationships between MVI and NLR, APRI, AFP, tumor size, and other clinical data were assessed using the univariate analysis, receiver operating characteristic (ROC) curve, least absolute shrinkage and selection operator (LASSO) analysis, and logistic analysis. Results The ROC curve determined that the cutoff values of NLR, platelet-to-lymphocyte ratio (PLR), and APRI were 1.520, 98, and 0.275, respectively. The univariate analysis showed that the MVI-positive result was associated with five factors: tumor size (χ2 = 10.620, p = 0.001), AFP (χ2 = 10.524, p = 0.001), Edmondson grade (χ2 = 20.736, p < 0.001), NLR (χ2 = 8.744, p = 0.003), and APRI (χ2 = 4.849, p = 0.028). The LASSO analysis indicated that the risk factors were the number of tumors, PLR, APRI, NLR, AFP, Edmondson grade, and tumor size. The multivariate logistic regression analysis showed that NLR ≥ 1.520 (OR 11.119, p = 0.006), APRI ≥ 0.275 (OR 12.515, p = 0.009), AFP ≥ 200 μg/mL (OR 7.823, p = 0.016), and tumor size > 3 cm (OR 7.689, p = 0.022) were independent risk factors for MVI in patients with hepatoma. Conclusion Preoperative NLR, APRI, AFP, and tumor size are reliable indicators for predicting the appearance of MVI in patients with hepatoma and are of great value in making detailed and reliable treatment protocols for these patients before surgery.

Effect of Microvascular Invasion on the Prognosis in Hepatocellular Carcinoma and Analysis of Related Risk Factors: A Two-Center Study

Objective: Microvascular invasion is considered to initiate intrahepatic metastasis and postoperative recurrence of hepatocellular carcinoma (HCC). We aimed to analyze the effect of MVI on the prognosis in HCC and identify related risk factors for microvascular invasion (MVI).Methods: The clinical data of 553 HCC patients who underwent liver surgery at Qingdao University from January 2014 to December 2018 and 89 patients at Beijing Tsinghua Changgung Hospital treated between October 2014 and October 2019 were collected retrospectively. We explored the impact of MVI on the prognosis of patients with HCC using Kaplan-Meier analysis. We conducted logistic regression analysis to identify variables significantly related to MVI.Results: Pathological examination confirmed the presence of MVI in 265 patients (41.3%). Six factors independently correlated with MVI were incorporated into the multivariate logistic regression analysis: Edmondson-Steiner grade [odds ratio (OR) = 3.244, 95%CI: 2.243–4.692; p < 0.001], liver capsule invasion (OR = 1.755; 95%CI: 1.215–2.535; p = 0.003), bile duct tumor thrombi (OR = 20.926; 95%CI: 2.552–171.553; p = 0.005), α-fetoprotein (> 400 vs. < 400 ng/ml; OR = 1.530; 95%CI: 1.017–2.303; p = 0.041), tumor size (OR = 1.095; 95%CI: 1.027–1.166; p = 0.005), and neutrophil-lymphocyte ratio (OR = 1.086; 95%CI: 1.016–1.162; p = 0.015). The area under the receiver operating characteristic curve (AUC) was 0.743 (95%CI: 0.704–0.781; p < 0.001), indicating that our logistic regression model had significant clinical usefulness.Conclusions: We analyzed the effect of MVI on the prognosis in HCC and evaluated the risk factors for MVI, which could be helpful in making decisions regarding patients with a high risk of recurrence.

Prediction of HCC microvascular invasion with gadobenate-enhanced MRI: correlation with pathology.

To assess the accuracy of gadobenate-enhanced MRI for predicting microvascular invasion (MVI) in patients operated for hepatocellular carcinoma (HCC). The 164 patients who met the inclusion criteria were assigned to one of two groups: the MVI-positive group and the MVI-negative group. Imaging results were compared between the two groups using the Kruskal test, chi-square test, independent sample t test, and logistic regression analysis. Differences in the capsule (p = 0.037) and margin (p = 0.004) of the tumor, rim enhancement (p = 0.002), peritumoral enhancement in the arterial phase (p < 0.001), and peritumoral hypointensity in the hepatobiliary phase (HBP) (p < 0.001) were statistically significant. The results of multivariate analysis identified rim enhancement in the arterial phase (odds ratio (OR) = 2.115; 95% confidence interval (CI), 1.002-4.464; p = 0.049) and peritumoral hypointensity in the HBP (OR = 5.836; 95% CI, 2.442-13.948; p < 0.001) as independent risk factors for MVI. Use of the two predictors in combination identified 32.79% (20/61) of HCCs with MVI with a specificity of 95.15% (98/103). Rim enhancement in the arterial phase and peritumoral hypointensity in the HBP were identified as independent risk factors for MVI in patients with HCC. • Rim enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase were independent risk factors for microvascular invasion in patients with HCC. • Use of the two predictors in combination had a sensitivity of 32.79% and a specificity of 95.15% for predicting microvascular invasion.

Integrated Nomograms for Preoperative Prediction of Microvascular Invasion and Lymph Node Metastasis Risk in Hepatocellular Carcinoma Patients.

The aim of the present work is to develop and validate accurate preoperative nomograms to predict microvascular invasion (MVI) and lymph node metastasis (LNM) in hepatocellular carcinoma. A total of 268 patients with resected hepatocellular carcinoma (HCC) were divided into a training set (n = 180), in an earlier period, and a validation set (n = 88), thereafter. Risk factors for MVI and LNM were assessed based on logistic regression. Blood signatures were established using the least absolute shrinkage and selection operator algorithm. Nomograms were constructed by combining risk factors and blood signatures. Performance was evaluated using the training set and validated using the validation set. The clinical values of the nomograms were measured by decision curve analysis. The risk factors for MVI were hepatitis B virus (HBV) DNA loading, portal hypertension, Barcelona liver clinic (BCLC) stage, and three computerized tomography (CT) imaging features, namely tumor number, size, and encapsulation, while only BCLC stage, Child-Pugh classification, and tumor encapsulation were associated with LNM. The nomogram incorporating both risk factors and blood signatures achieved better performance in predicting MVI in the training and validation sets (C-indexes of 0.828 and 0.804) than the LNM nomogram (C-indexes of 0.765 and 0.717). Calibration curves also demonstrated a good fit. The decision curves indicate significant clinical usefulness. The novel validated nomograms for HCC patients presented herein are noninvasive preoperative tools that can effectively predict the individualized risk of MVI and LNM, and this predictive power can aid doctors in explaining the illness for patient counseling.

The establishment and application of a preoperative predictive nomogram for hepatocellular carcinoma with microvascular invasion

Objective To establish a preoperative nomogram model in predicting microvascular invasion (MVI) and to test its predictive effectiveness in hepatocellular carcinoma (HCC). Methods This retrospective study was conducted on 798 patients with HCC, including 690 males and 108 females, aged (49.8±10.9) years old who underwent curative hepatectomy in the Guangxi Medical University Affiliated Tumor Hospital between January 2014 and December 2017 were retrospectively analyzed. The patients were divided into the model group (n=579) and the validation group (n=219) according to the periods of the operation time. Independent risk factors of MVI were identified by univariate and multivariate logistic regression analysis in the model group, and a nomogram model was established according to the independent risk factors. The accuracy of the nomogram model in predicting MVI was detected in the two groups by the computer consistency coefficient (C-index) and calibration graph method. The predictive value was evaluated by receiver operating characteristic curve. Results Histopathological diagnosis revealed 278 patients with MVI and no MVI in the 301 patients of HCC out of the 579 patients in the model group. In the validation group, there were 119 patients with MVI and 100 patients with no MVI out of the 219 patients. Total bilirubin >15 μmol/L(OR=1.519, 95%CI: 1.041~2.217), alkaline phosphatase >60 U/L(OR=1.681, 95%CI: 1.059~2.670), alpha-fetoprotein >200 ng/L (OR=2.192, 95%CI: 1.531~3.134) and tumor maximum diameter (OR=1.120, 95%CI: 1.057~1.187) were the independent risk factors of MVI on multivariate analysis. After establishment of the nomogram model using the independent risk factors, the C-indexes were 0.680 and 0.773 respectively in the model group and the validation group. In the calibration graph, the standard curve properly fitted with the predicting calibration curve. The predicted value of MVI obtained was in good agreement with the observed value. The ROC curve analysis nomogram model predicted the low performance of MVI. Conclusion The nomogram model in predicting MVI in patients with HCC was successfully established. The model offered certain guiding significance in the clinical treatment of HCC. Key words: Carcinoma, hepatocellular; Risk factors; Microvascular invasion; Nomogram

Radiomic features to predict microvascular invasion in hepatocellular carcinoma based on conventional MRI: preliminary findings

Objective To identify the preoperative MRI findings for predicting microvascular invasion (MVI) using texture analysis (TA) on multiple MRI sequences. Methods Two hundred and fifty patients with HCC pathologically confirmed by surgery in Zhongshan Hospital from October 2015 to October 2016 were analyzed retrospectively. All patients underwent conventional MRI plain scan and dynamic contrast-enhanced examination within 2 weeks before operation. According to the ratio of 1∶1, the patients were divided into a training set (125 cases) and a test set (125 cases).The training set was used to establish a classifier to predict MVI of HCCs via the TA, and the test set was used to evaluate the performance of the classifier. An image analysis was performed using an in-house software contained a set of 2 415 features which were generated from all conventional axial sequences, including the T2WI, DWI, ADC map, and dynamic enhancement images.. A four-fold cross validation (FFCV) and sequential forward floating feature selection strategy (SFFS) were employed to select an optimal subset of features and a linear discriminant analysis (LDA) was employed to establish a classifier. The clinical laboratory examination, morphologic characteristics and quantitative analysis of conventional MR were used to compare the performance of predicting MVI with the classifier. A Chi-squared test or Fisher exact probablities test were used for categorical variables, and independent t test or Mann-Whitney U test were used for used for continuous variables. Factors with a P value less than 0.05 at univariate analyses were entered into the multivariate model to identify independent predictors. The Hosmer-Lemeshow test was performed to explain the goodness of fit of the multivariate logistic model. A receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance. Results The classifier set up by the training set consists of 13 texture features. When conventional MRI texture features of test set were used to judge whether there was MVI or not, the AUC of all texture features of arterial phase (AP) was the highest (0.506 3). Univariate regression analysis showed that there were significant differences in pathological grade (P=0.026), AFP level (P=0.033), lesion edge shape (P=0.038), AP enhancement (P=0.038), and AP peritumoral enhancement (P=0.008). Multivariate binary logistic regression analysis showed that peritumoral enhancement and texture classifier assessed MVI with P values of 0.005 and 0.001,which were independent risk factors for MVI. The significance level of Hosmer Lemeshow test was 0.796, indicating the goodness of fit of acceptable models. The AUCs of single variable, combined variable (including of AFP level, irregular tumor margin, enhancement intensity in AP and peritumoral enhancement in AP) and texture classifier for MVI were 0.588 to 0.627, 0.798 and 0.733, respectively. When compared the AUC of the combination features (including of AFP level, irregular tumor margin, enhancement intensity in AP and peritumoral enhancement in AP) with the classifier to identify MVI of HCC in the test set, no significant difference was found(P=0.108 6). However, although the sensitivity of them were same as 70.73%, the specificity of the combination features was mildly higher than that of classifier (82.14% vs. 78.57%). Conclusions Combination features of AFP level, tumor margin, enhancement intensity in AP and peritumoral enhancement in AP can be used to predict MVI of HCCs. It is a new method of noninvasive evaluation of MVI before operation. The performance of the classifier made by TA was not superior to that of combination features based on clinic and conventional MR sequences. Key words: Liver neoplasms; Magnetic resonance imaging; Radiomics; Microvascular invasion

Influencing factors analysis of microvascular invasion in patients with hepatocellular carcinoma

Objective To evaluate the correlation between microvascular invasion(MVI ) and prognosis in patients with hepatocellular carcinoma (HCC), and to analyse the influencing factors of MVI in patients with HCC. Methods Total of 81 patients with hepatocellular carcinoma treated in Beijing Hospital from January 2014 to December 2016 were retrospectively studied. There were 65 males and 16 females. The mean age was 59.6±12.7 years, and the age ranged from 21 to 87 years old. Pathological examination showed presence of MVI in 35 patients. Results Total of seventy-six patients with hepatocellular carcinoma were followed-up. The 1-, 2-, 3- and 4-year overall survival rates in the 35 patients with microvascular invasion of hepatocellular carcinoma were 78.6%, 55.4%, 38.3%, and 32.2%, respectively. The 1-, 2-, 3-, and 4-year overall survival rates of the 41 patients without microvascular invasion were 93.4%, 76.5%, 68.2% and 68.2%, respectively. The difference was significant (P 0.05). Multivariate logistic regression analysis showed the maximum diameter of tumor >5 cm (OR=6.340, 95%CI: 2.000~20.096), preoperative total bilirubin (TBil)>17 μmol/L (OR=5.067, 95%CI: 1.386~18.525), and preoperative alpha-fetoprotein (AFP)>400 μg/L (OR=6.042, 95%CI: 1.435~25.444) were independent risk factors of microvascular invasion (P<0.05). Conclusion Hepatocellular carcinoma patients with microvascular invasion had poor prognosis. Preoperative AFP, preoperative TBil, and diameter of tumor were independent risk factors of microvascular invasion in patients with hepatocellular carcinoma. Key words: Carcinoma, hepatocellular; Prognosis; Microvascular invasion; Influencing factors

Nomograms for Preoperative Prediction of Microvascular Invasion and Lymph Node Metastasis Risk in Hepatocellular Carcinoma

Background: To develop and validate accurate preoperative nomograms to predict microvascular invasion (MVI) and lymph node metastasis (LNM) in hepatocellular carcinoma. Methods: A total of 302 patients with resected HCC were divided into a training set (n=202) in an earlier period and a validation set (n=100) thereafter. Risk factors for MVI and LNM were assessed based on logistic regression. The blood signatures were established with the least absolute shrinkage and selection operator algorithm. Nomograms were constructed by combining risk factors and blood signatures. Performance was evaluated in the training set and validated in the validation set. The clinical values of the nomograms were measured by decision curve analysis. Findings: The risk factors for MVI were hepatitis B virus history and three CT imaging features, namely, tumor number, size and encapsulation, while only tumor number and size were associated with LNM. The blood signatures achieved favorable prediction efficacy with C-indexes of 0.725 and 0.709 in MVI and LNM nomograms. The nomograms incorporating the risk factors and the blood signatures also achieved good C-indexes of 0.792 and 0.771 in predicting MVI in the training and validation sets, while 0.784 and 0.844 of the LNM nomogram. Calibration curves demonstrated good fit. The decision curves indicated significant clinical usefulness. Interpretation: Our novel validated nomograms for HCC patients are noninvasive preoperative prediction tools that can effectively predict the individualized risk of MVI and LNM, and this predictive power can help doctors formulate rational individual treatments. Funding Statement: This work was supported in part by the National Natural Science Foundation of China (No. 81572407, 81602112, 81672405, 81702404 ); Key project of Natural Science Foundation of Guangdong Province, China (No. 4210016041); Science and Technology Program of Guangdong Province, China (No.2015A030313096, 2016A030313184, 2017A030313536); Natural Science Foundation of Guangzhou, China (No. 4250016043). Declaration of Interests: The authors declare that they have no conflicts of interest. Ethics Approval Statement: The retrospective study with anonymous data was approved by the institutional Ethics Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University.

Risk factors of microvascular invasion in patients with hepatocellular carcinoma

Background: It is suggested that microvascular invasion (MVI) is one of the strongest predictors of prognosis and recurrence of hepatocellular carcinoma (HCC). This study analyzes the related influence factors of MVI, and further discusses these factors to the occurrence of MVI. Method: Retrospective clinical data of HCC patients which are collected, including the general clinical data and postoperative pathological data associated with MVI are performed. According to the postoperative pathological report, data will be divided into MVI group and control group. Logistic regression analysis was performed on the statistically significant factors. Results: A total of 170 patients with HCC are selected. There are MVI group (51 cases) and control group (97 cases). There were no significantly differences in age, gender, history of hepatitis B, history of hepatitis C, hepatic cirrhosis, diabetes and hepatitis B virus deoxyribonucleic acid titer, γ- glutamyltranspeptidas, alanine transaminase, aspartate transaminase, total bilirubin, albumin, platelet count, tumor numberand tumor capsule (P>0.05). Tumor size (P=0.000), differentiation degree (P=0.028) and alpha-fetoprotein (P=0.003) was statistically significant difference. Multivariate logistic regression analysis shows that tumor size (P=0.004) and AFP (P=0.022) are independent risk factors for MVI. Conclusion: Tumor size, low differentiation, tact capsule and alpha-fetoprotein are independent risk factors of MVI. According to the risk factors of MVI, we can judge the possibility of MVI, and further guide the clinical treatment.

Predictive model for microvascular invasion of hepatocellular carcinoma among candidates for either hepatectomy or liver transplantation.

4079 Background: Microvascular invasion (MVI) is the strongest prognostic factor following surgery of hepatocellular carcinoma (HCC). However, it is usually not available on the preoperative setting. A predictive model of MVI in patients scheduled for hepatic resection (HR) or liver transplantation (LT) would thus help guiding treatment strategy. The aim of this study was to develop a predictive model for MVI of HCC before either HR or LT. Methods: HCC patients who consecutively performed HR or LT from January 1994 to June 2016 at a single institution were subdivided into a training and validation cohort. Risk factors for MVI in the training cohort were used to develop a predictive model for MVI, to be validated in the validation cohort. The outcomes of the HR and LT patients with high or low MVI probability based on the model, were compared using propensity score matching (PSM). Cut-off values for continuous factors were determined based on ROC curve analysis. Results: A total of 910 patients (425 HR, 485 LT) were included in the training (n = 637) and validation (n = 273) cohorts. In the training cohort, multivariate analysis demonstrated that alpha-fetoprotein ≥100ng/ml ( p &lt; 0.0001), largest tumor size ≥40mm ( p = 0.0002), non-boundary HCC type on contrast-enhanced CT ( p = 0.001), neutrophils-to-lymphocytes ratio ≥3.2 ( p = 0.002), aspartate aminotransferase ≥62U/l ( p = 0.02) were independently associated with MVI. Combinations of these 5 factors varied the MVI probability from 15.5% to 91.1%. This predictive model achieved a good c-index of 0.76 in the validation cohort. In PSM (109 HR, 109 LT), there was no difference in survival between HR and LT patients among the high MVI probability (≥50%) patients, (5y-OS; 46.3% vs 42.2%, p = 0.77, 5y-RFS; 54.0% vs 28.8%, p = 0.21). Among the low probability ( &lt; 50%), survival was significantly decreased following HR compared with LT (5y-OS; 54.1% vs 78.8%, p = 0.007, 5y-RFS; 17.3% vs 86.1%, p&lt; 0.0001). Conclusions: This model developed from preoperative data allows reliable prediction of MVI, and may thus help with preoperative decisions about the suitability of HR or LT in patients with HCC.

Prognostic value of a novel risk classification of microvascular invasion in patients with hepatocellular carcinoma after resection.

ObjectivesThe present research aimed to evaluate the prognostic value of a novel risk classification of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) after resection.MethodsA total of 295 consecutive HCC patients underwent hepatectomy were included in our study. We evaluated the degree of MVI according to the following three features: the number of invaded microvessels (≤5 vs >5), the number of invading carcinoma cells (≤ 50 vs >50), the distance of invasion from tumor edge (≤1 cm vs >1 cm).ResultsAll patients were divided into three groups according to the three risk factors of MVI: non-MVI group (n=180), low-MVI group (n=60) and high-MVI group (n=55). The overall survival (OS) and recurrence-free survival (RFS) rates of high-MVI group were significantly poorer than those of low-MVI and non-MVI groups (P<0.001 and P=0.001; P<0.001 and P=0.003). Multivariate analysis showed high-MVI, type of resection, ICG-R15 and tumor size were risk factors for OS after hepatectomy. High-MVI, type of resection and tumor size were risk factors for RFS. In subgroup analyses, the OS and RFS rates of low-MVI and non-MVI groups were better than high-MVI group regardless of tumor size. In high-MVI group, anatomical liver resection (n=28) showed better OS and RFS rates compared with non-anatomical liver resection (n=29) (P=0.012 and P=0.002).ConclusionsThe novel risk classification of MVI based on histopathological features is valuable for predicting prognosis of HCC patients after hepatectomy.

Influence of microvascular invasion on progression-free survival in patients with a solitary small he-patocellular carcinoma

Objective To study the influence of microvascular invasion (MVI) on progression-free survival (PFS) in patients with a solitary small hepatocellular carcinoma, and to analyze the risk factors of MVI. Methods 126 patients with a solitary small hepatocellular carcinoma who underwent liver resection at Tianjin Medical University Cancer Hospital from January 2010 to December 2012 were retrospectively stu-died. Their demographic and clinicopathological characteristics including age, gender, HBV infection, HCV infection, alcohol consumption, comorbidity, liver cirrhosis, ascites, tumor size, tumor differentiation, MVI, satellite lesion, AFP, CA19-9, ALT and TBil were analyzed. Results The 1-, 2- and 3-year PFS rates of patients with a solitary small hepatocellular carcinoma were 81.0%, 60.3% and 47.3% after surgical resection, respectively. Univariate analysis revealed that MVI, comorbidity, non-well-differentiated tumor, tumor size >4 cm were risk factors of PFS. Multivariate analysis demonstrated that only MVI and comorbidity were independent factors of PFS. MVI occurred in 43.7% of the patients. The median PFS of patients without MVI was 45 months, and the 1-, 2- and 3-year PFS rates of these patients were 91.5%, 67.6% and 56.0%, respectively. The median PFS of patients with MVI was 30 months, and the 1-, 2- and 3-year PFS rates were 67.3%, 50.9% and 35.4%, respectively. On univariate analysis, AFP >100 μg/L, non-well-differentiated tumor and satellite lesions were significantly associated with MVI. On multivariate analysis only non-well-differentiated tumor was independently associated with MVI. Conclusions MVI was an important factor affecting PFS in patients with a solitary small hepatocellular carcinoma. AFP>100 μg/L, non-well-differentiated tumor and satellite lesions were risk factors of MVI. Key words: Solitary small hepatocellular carcinoma; Progression-free survival; Microvascular invasion; Risk factors