BACKGROUND Microvascular invasion(MVI)is a significant indicator of the aggressive behavior of hepatocellular carcinoma(HCC).Expanding the surgical resection margin and performing anatomical liver resection may improv...BACKGROUND Microvascular invasion(MVI)is a significant indicator of the aggressive behavior of hepatocellular carcinoma(HCC).Expanding the surgical resection margin and performing anatomical liver resection may improve outcomes in patients with MVI.However,no reliable preoperative method currently exists to predict MVI status or to identify patients at high-risk group(M2).AIM To develop and validate models based on contrast-enhanced computed tomo-graphy(CECT)radiomics and clinicoradiological factors to predict MVI and identify M2 among patients with hepatitis B virus-related HCC(HBV-HCC).The ultimate goal of the study was to guide surgical decision-making.METHODS A total of 270 patients who underwent surgical resection were retrospectively analyzed.The cohort was divided into a training dataset(189 patients)and a validation dataset(81)with a 7:3 ratio.Radiomics features were selected using intra-class correlation coefficient analysis,Pearson or Spearman’s correlation analysis,and the least absolute shrinkage and selection operator algorithm,leading to the construction of radscores from CECT images.Univariate and multivariate analyses identified significant clinicoradiological factors and radscores associated with MVI and M2,which were subsequently incorporated into predictive models.The models’performance was evaluated using calibration,discrimination,and clinical utility analysis.RESULTS Independent risk factors for MVI included non-smooth tumor margins,absence of a peritumoral hypointensity ring,and a high radscore based on delayed-phase CECT images.The MVI prediction model incorporating these factors achieved an area under the curve(AUC)of 0.841 in the training dataset and 0.768 in the validation dataset.The M2 prediction model,which integrated the radscore from the 5 mm peritumoral area in the CECT arterial phase,α-fetoprotein level,enhancing capsule,and aspartate aminotransferase level achieved an AUC of 0.865 in the training dataset and 0.798 in the validation dataset.Calibration and decision curve analyses confirmed the models’good fit and clinical utility.CONCLUSION Multivariable models were constructed by combining clinicoradiological risk factors and radscores to preoper-atively predict MVI and identify M2 among patients with HBV-HCC.Further studies are needed to evaluate the practical application of these models in clinical settings.展开更多
BACKGROUND Despite continuous changes in treatment methods,the survival rate for advanced hepatocellular carcinoma(HCC)patients remains low,highlighting the importance of diagnostic methods for HCC.AIM To explore the ...BACKGROUND Despite continuous changes in treatment methods,the survival rate for advanced hepatocellular carcinoma(HCC)patients remains low,highlighting the importance of diagnostic methods for HCC.AIM To explore the efficacy of texture analysis based on multi-parametric magnetic resonance(MR)imaging(MRI)in predicting microvascular invasion(MVI)in preoperative HCC.METHODS This study included 105 patients with pathologically confirmed HCC,categorized into MVI-positive and MVI-negative groups.We employed Original Data Analysis,Principal Component Analysis,Linear Discriminant Analysis(LDA),and Non-LDA(NDA)for texture analysis using multi-parametric MR images to predict preoperative MVI.The effectiveness of texture analysis was determined using the B11 program of the MaZda4.6 software,with results expressed as the misjudgment rate(MCR).RESULTS Texture analysis using multi-parametric MRI,particularly the MI+PA+F dimensionality reduction method combined with NDA discrimination,demonstrated the most effective prediction of MVI in HCC.Prediction accuracy in the pulse and equilibrium phases was 83.81%.MCRs for the combination of T2-weighted imaging(T2WI),arterial phase,portal venous phase,and equilibrium phase were 22.86%,16.19%,20.95%,and 20.95%,respectively.The area under the curve for predicting MVI positivity was 0.844,with a sensitivity of 77.19%and specificity of 91.67%.CONCLUSION Texture analysis of arterial phase images demonstrated superior predictive efficacy for MVI in HCC compared to T2WI,portal venous,and equilibrium phases.This study provides an objective,non-invasive method for preoperative prediction of MVI,offering a theoretical foundation for the selection of clinical therapy.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)recurrence is highly correlated with increased mortality.Microvascular invasion(MVI)is indicative of aggressive tumor biology in HCC.AIM To construct an artificial neural networ...BACKGROUND Hepatocellular carcinoma(HCC)recurrence is highly correlated with increased mortality.Microvascular invasion(MVI)is indicative of aggressive tumor biology in HCC.AIM To construct an artificial neural network(ANN)capable of accurately predicting MVI presence in HCC using magnetic resonance imaging.METHODS This study included 255 patients with HCC with tumors<3 cm.Radiologists annotated the tumors on the T1-weighted plain MR images.Subsequently,a three-layer ANN was constructed using image features as inputs to predict MVI status in patients with HCC.Postoperative pathological examination is considered the gold standard for determining MVI.Receiver operating characteristic analysis was used to evaluate the effectiveness of the algorithm.RESULTS Using the bagging strategy to vote for 50 classifier classification results,a prediction model yielded an area under the curve(AUC)of 0.79.Moreover,correlation analysis revealed that alpha-fetoprotein values and tumor volume were not significantly correlated with the occurrence of MVI,whereas tumor sphericity was significantly correlated with MVI(P<0.01).CONCLUSION Analysis of variable correlations regarding MVI in tumors with diameters<3 cm should prioritize tumor sphericity.The ANN model demonstrated strong predictive MVI for patients with HCC(AUC=0.79).展开更多
Hepatocellular carcinoma(HCC)is one of the most lethal tumors in the world.Liver resection(LR)and liver transplantation(LT)are widely considered as radical treatments for early HCC.However,the recurrence rates after c...Hepatocellular carcinoma(HCC)is one of the most lethal tumors in the world.Liver resection(LR)and liver transplantation(LT)are widely considered as radical treatments for early HCC.However,the recurrence rates after curative treatment are still high and overall survival is unsatisfactory.Microvascular invasion(MVI)is considered to be one of the important prognostic factors affecting postoperative recurrence and long-term survival.Unfortunately,whether HCC patients with MVI should receive postoperative adjuvant therapy remains unknown.In this review,we summarize the therapeutic effects of transcatheter arterial chemoembolization,hepatic arterial infusion chemotherapy,tyrosine protein kinase inhibitor-based targeted therapy,and immune checkpoint inhibitors in patients with MVI after LR or LT,aiming to provide a reference for the best adjuvant treatment strategy for HCC patients with MVI after LT or LR.展开更多
BACKGROUND Microvascular invasion(MVI)is an important predictor of poor prognosis in patients with hepatocellular carcinoma(HCC).Accurate preoperative prediction of MVI in HCC would provide useful information to guide...BACKGROUND Microvascular invasion(MVI)is an important predictor of poor prognosis in patients with hepatocellular carcinoma(HCC).Accurate preoperative prediction of MVI in HCC would provide useful information to guide the choice of therapeutic strategy.Shear wave elastography(SWE)plays an important role in hepatic imaging,but its value in the preoperative prediction of MVI in HCC has not yet been proven.AIM To explore the value of conventional ultrasound features and SWE in the preoperative prediction of MVI in HCC.METHODS Patients with a postoperative pathological diagnosis of HCC and a definite diagnosis of MVI were enrolled in this study.Conventional ultrasound features and SWE features such as maximal elasticity(Emax)of HCCs and Emax of the periphery of HCCs were acquired before surgery.These features were compared between MVI-positive HCCs and MVI-negative HCCs and between mild MVI HCCs and severe MVI HCCs.RESULTS This study included 86 MVI-negative HCCs and 102 MVI-positive HCCs,including 54 with mild MVI and 48 with severe MVI.Maximal tumor diameters,surrounding liver tissue,color Doppler flow,Emax of HCCs,and Emax of the periphery of HCCs were significantly different between MVI-positive HCCs and MVI-negative HCCs.In addition,Emax of the periphery of HCCs was significantly different between mild MVI HCCs and severe MVI HCCs.Higher Emax of the periphery of HCCs and larger maximal diameters were independent risk factors for MVI,with odds ratios of 2.820 and 1.021,respectively.CONCLUSION HCC size and stiffness of the periphery of HCC are useful ultrasound criteria for predicting positive MVI.Preoperative ultrasound and SWE can provide useful information for the prediction of MVI in HCCs.展开更多
BACKGROUND Significant correlation between lymphatic,microvascular,and perineural invasion(LMPI)and the prognosis of pancreatic neuroendocrine tumors(PENTs)was confirmed by previous studies.There was no previous study...BACKGROUND Significant correlation between lymphatic,microvascular,and perineural invasion(LMPI)and the prognosis of pancreatic neuroendocrine tumors(PENTs)was confirmed by previous studies.There was no previous study reported the relationship between magnetic resonance imaging(MRI)parameters and LMPI.AIM To determine the feasibility of using preoperative MRI of the pancreas to predict LMPI in patients with non-functioning PENTs(NFPNETs).METHODS A total of 61 patients with NFPNETs who underwent MRI scans and lymphadenectomy from May 2011 to June 2018 were included in this retrospective study.The patients were divided into group 1(n=34,LMPI negative)and group 2(n=27,LMPI positive).The clinical characteristics and qualitative MRI features were collected.In order to predict LMPI status in NF-PNETs,a multivariate logistic regression model was constructed.Diagnostic performance was evaluated by calculating the receiver operator characteristic(ROC)curve with area under ROC,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV)and accuracy.RESULTS There were significant differences in the lymph node metastasis stage,tumor grade,neuron-specific enolase levels,tumor margin,main pancreatic ductal dilatation,common bile duct dilatation,enhancement pattern,vascular and adjacent tissue involvement,synchronous liver metastases,the long axis of the largest lymph node,the short axis of the largest lymph node,number of the lymph nodes with short axis>5 or 10 mm,and tumor volume between two groups(P<0.05).Multivariate analysis showed that tumor margin(odds ratio=11.523,P<0.001)was a predictive factor for LMPI of NF-PNETs.The area under the receiver value for the predictive performance of combined predictive factors was 0.855.The sensitivity,specificity,PPV,NPV and accuracy of the model were 48.1%(14/27),97.1%(33/34),97.1%(13/14),70.2%(33/47)and 0.754,respectively.CONCLUSION Using preoperative MRI,ill-defined tumor margins can effectively predict LMPI in patients with NF-PNETs.展开更多
AIM To investigate the efficacy and safety of postoperative adjuvant transcatheter arterial chemoembolization(PA-TACE) in preventing tumor recurrence and improving survival in Barcelona Clinic Liver Cancer(BCLC) early...AIM To investigate the efficacy and safety of postoperative adjuvant transcatheter arterial chemoembolization(PA-TACE) in preventing tumor recurrence and improving survival in Barcelona Clinic Liver Cancer(BCLC) early(A) and intermediate(B) stage hepatocellular carcinoma(HCC) patients with microvascular invasion(MVI).METHODS A total of 519 BCLC A or B HCC patients treated by liver resection alone or followed by PA-TACE between January 2012 and December 2015 were studied retrospectively. Univariate and multivariate analyses were performed to investigate the risk factors for recurrence-free survival(RFS) and overall survival(OS). Multiple logistic regression was used to identify the clinicopathological characteristics associated with MVI. The rates of RFS and OS were compared among patients with or without MVI treated with liver resection alone or followed by PA-TACE. RESULTS Univariate and multivariate analyses demonstrated that serum AFP level > 400 ng/m L, tumor size > 5 cm, tumor capsule invasion, MVI, and major hepatectomy were risk factors for poor OS. Tumor capsule invasion, MVI, tumor size > 5 cm, HBV-DNA copies > 1 x 104 IU/m L, and multinodularity were risk factors for poor RFS. Multiple logistic regression identified serum AFP level > 400 ng/m L, tumor size > 5 cm, and tumor capsule invasion as independent predictors of MVI. Both OS and DFS were significantly improved in patients with MVI who received PA-TACE as compared to those who underwent liver resection alone. Patients without MVI did not show a significant difference in OS and RFS between those treated by liver resection alone or followed by PA-TACE.CONCLUSION PA-TACE is a safe adjuvant intervention and can efficiently prevent tumor recurrence and improve the survival of BCLC early-and intermediate-stage HCC patients with MVI.展开更多
Hepatocellular carcinoma(HCC)is the most common primary liver cancer,accounting for about 90%of liver cancer cases.It is currently the fifth most common cancer in the world and the third leading cause of cancer-relate...Hepatocellular carcinoma(HCC)is the most common primary liver cancer,accounting for about 90%of liver cancer cases.It is currently the fifth most common cancer in the world and the third leading cause of cancer-related mortality.Moreover,recurrence of HCC is common.Microvascular invasion(MVI)is a major factor associated with recurrence in postoperative HCC.It is difficult to evaluate MVI using traditional imaging modalities.Currently,MVI is assessed primarily through pathological and immunohistochemical analyses of postoperative tissue samples.Needle biopsy is the primary method used to confirm MVI diagnosis before surgery.As the puncture specimens represent just a small part of the tumor,and given the heterogeneity of HCC,biopsy samples may yield false-negative results.Radiomics,an emerging,powerful,and non-invasive tool based on various imaging modalities,such as computed tomography,magnetic resonance imaging,ultrasound,and positron emission tomography,can predict the HCC-MVI status preoperatively by delineating the tumor and/or the regions at a certain distance from the surface of the tumor to extract the image features.Although positive results have been reported for radiomics,its drawbacks have limited its clinical translation.This article reviews the application of radiomics,based on various imaging modalities,in preoperative evaluation of HCC-MVI and explores future research directions that facilitate its clinical translation.展开更多
BACKGROUND Microvascular invasion(MVI)is an important prognostic factor affecting early recurrence and overall survival in hepatocellular carcinoma(HCC)patients after hepatectomy and liver transplantation,but it can b...BACKGROUND Microvascular invasion(MVI)is an important prognostic factor affecting early recurrence and overall survival in hepatocellular carcinoma(HCC)patients after hepatectomy and liver transplantation,but it can be determined only in surgical specimens.Accurate preoperative prediction of MVI is conducive to clinical decisions.AIM To develop and validate a preoperative prediction model for MVI in patients with HCC.METHODS Data from 454 patients with HCC who underwent hepatectomy at the First Affiliated Hospital of Nanjing Medical University between May 2016 and October 2019 were retrospectively collected.Then,the patients were nonrandomly split into a training cohort and a validation cohort.Logistic regression analysis was used to identify variables significantly associated with MVI that were then included in the nomogram.We evaluated the discrimination and calibration ability of the nomogram by using R software.RESULTS MVI was confirmed in 209(46.0%)patients by a pathological examination.Multivariate logistic regression analysis identified four risk factors independently associated with MVI:Tumor size[odds ratio(OR)=1.195;95%confidence interval(CI):1.107–1.290;P<0.001],number of tumors(OR=4.441;95%CI:2.112–9.341;P<0.001),neutrophils(OR=1.714;95%CI:1.036–2.836;P=0.036),and serumα-fetoprotein(20–400 ng/mL,OR=1.955;95%CI:1.055–3.624;P=0.033;>400 ng/mL,OR=3.476;95%CI:1.950–6.195;P<0.001).The concordance index was 0.79(95%CI:0.74–0.84)and 0.81(95%CI:0.74–0.89)in the training and validation cohorts,respectively.The calibration curves showed good agreement between the predicted risk by the nomogram and real outcomes.CONCLUSION We have developed and validated a preoperative prediction model for MVI in patients with HCC.The model could aid physicians in clinical treatment decision making.展开更多
BACKGROUND Liver cancer is one of the most common malignant tumors,and ranks as the fourth leading cause of cancer death worldwide.Microvascular invasion(MVI)is considered one of the most important factors for recurre...BACKGROUND Liver cancer is one of the most common malignant tumors,and ranks as the fourth leading cause of cancer death worldwide.Microvascular invasion(MVI)is considered one of the most important factors for recurrence and poor prognosis of liver cancer.Thus,accurately identifying MVI before surgery is of great importance in making treatment strategies and predicting the prognosis of patients with hepatocellular carcinoma(HCC).Radiomics as an emerging field,aims to utilize artificial intelligence software to develop methods that may contribute to cancer diagnosis,treatment improvement and evaluation,and better prediction.AIM To investigate the predictive value of computed tomography radiomics for MVI in solitary HCC≤5 cm.METHODS A total of 185 HCC patients,including 122 MVI negative and 63 MVI positive patients,were retrospectively analyzed.All patients were randomly assigned to the training group(n=124)and validation group(n=61).A total of 1351 radiomic features were extracted based on three-dimensional images.The diagnostic performance of the radiomics model was verified in the validation group,and the Delong test was applied to compare the radiomics and MVIrelated imaging features(two-trait predictor of venous invasion and radiogenomic invasion).RESULTS A total of ten radiomics features were finally obtained after screening 1531 features.According to the weighting coefficient that corresponded to the features,the radiomics score(RS)calculation formula was obtained,and the RS score of each patient was calculated.The radiomics model exhibited a better correction and identification ability in the training and validation groups[area under the curve:0.72(95%confidence interval:0.58-0.86)and 0.74(95%confidence interval:0.66-0.83),respectively].Its prediction performance was significantly higher than that of the image features(P<0.05).CONCLUSION Computed tomography radiomics has certain predictive value for MVI in solitary HCC≤5 cm,and the predictive ability is higher than that of image features.展开更多
BACKGROUND The long-term effect of anatomic resection(AR)is better than that of nonanatomic resection(NAR).At present,there is no study on microvascular invasion(MVI)and liver resection types.AIM To explore whether AR...BACKGROUND The long-term effect of anatomic resection(AR)is better than that of nonanatomic resection(NAR).At present,there is no study on microvascular invasion(MVI)and liver resection types.AIM To explore whether AR improves long-term survival in patients with hepatocellular carcinoma(HCC)by removing the peritumoral MVI.METHODS A total of 217 patients diagnosed with HCC were enrolled in the study.The surgical margin was routinely measured.According to the stratification of different tumor diameters,patients were divided into the following groups:≤2 cm group,2-5 cm group,and>5 cm group.RESULTS In the 2-5 cm diameter group,the overall survival(OS)of MVI positive patients was significantly better than that of MVI negative patients(P=0.031).For the MVI positive patients,there was a statistically significant difference between AR and NAR(P=0.027).AR leads to a wider surgical margin than NAR(2.0±2.3 cm vs 0.7±0.5 cm,P<0.001).In the groups with tumor diameters<2 cm,both AR and NAR can obtain a wide surgical margin,and the surgical margins of AR are wider than that of NAR(3.5±5.8 cm vs 1.6±0.5 cm,P=0.048).In the groups with tumor diameters>5 cm,both AR and NAR fail to obtain wide surgical margin(0.6±1.0 cm vs 0.7±0.4 cm,P=0.491).CONCLUSION For patients with a tumor diameter of 2-5 cm,AR can achieve the removal of peritumoral MVI by obtaining a wide incision margin,reduce postoperative recurrence,and improve prognosis.展开更多
BACKGROUND The prognosis of hepatocellular carcinoma(HCC)remains poor and relapse occurs in more than half of patients within 2 years after hepatectomy.In terms of recent studies,microvascular invasion(MVI)is one of t...BACKGROUND The prognosis of hepatocellular carcinoma(HCC)remains poor and relapse occurs in more than half of patients within 2 years after hepatectomy.In terms of recent studies,microvascular invasion(MVI)is one of the potential predictors of recurrence.Accurate preoperative prediction of MVI is potentially beneficial to the optimization of treatment planning.AIM To develop a radiomic analysis model based on pre-operative magnetic resonance imaging(MRI)data to predict MVI in HCC.METHODS A total of 113 patients recruited to this study have been diagnosed as having HCC with histological confirmation,among whom 73 were found to have MVI and 40 were not.All the patients received preoperative examination by Gd-enhanced MRI and then curative hepatectomy.We manually delineated the tumor lesion on the largest cross-sectional area of the tumor and the adjacent two images on MRI,namely,the regions of interest.Quantitative analyses included most discriminant factors(MDFs)developed using linear discriminant analysis algorithm and histogram analysis with MaZda software.Independent significant variables of clinical and radiological features and MDFs for the prediction of MVI were estimated and a discriminant model was established by univariate and multivariate logistic regression analysis.Prediction ability of the above-mentioned parameters or model was then evaluated by receiver operating characteristic(ROC)curve analysis.Five-fold cross-validation was also applied via R software.RESULTS The area under the ROC curve(AUC)of the MDF(0.77-0.85)outperformed that of histogram parameters(0.51-0.74).After multivariate analysis,MDF values of the arterial and portal venous phase,and peritumoral hypointensity in the hepatobiliary phase were identified to be independent predictors of MVI(P<0.05).The AUC value of the model was 0.939[95%confidence interval(CI):0.893-0.984,standard error:0.023].The result of internal five-fold cross-validation(AUC:0.912,95%CI:0.841-0.959,standard error:0.0298)also showed favorable predictive efficacy.CONCLUSION Noninvasive MRI radiomic model based on MDF values and imaging biomarkers may be useful to make preoperative prediction of MVI in patients with primary HCC.展开更多
Objective:Treatment strategies for recurrent hepatocellular carcinoma(rHCC)are controversial.We used the status of microvascular invasion(MVI)at primary resection as a marker to choose moderate treatment options for r...Objective:Treatment strategies for recurrent hepatocellular carcinoma(rHCC)are controversial.We used the status of microvascular invasion(MVI)at primary resection as a marker to choose moderate treatment options for rHCC patients with Barcelona Clinic Liver Cancer(BCLC)stage B-C disease.Methods:From June 2009 to June 2017.展开更多
基金Supported by Anhui Provincial Key Research and Development Plan,No.202104j07020048.
文摘BACKGROUND Microvascular invasion(MVI)is a significant indicator of the aggressive behavior of hepatocellular carcinoma(HCC).Expanding the surgical resection margin and performing anatomical liver resection may improve outcomes in patients with MVI.However,no reliable preoperative method currently exists to predict MVI status or to identify patients at high-risk group(M2).AIM To develop and validate models based on contrast-enhanced computed tomo-graphy(CECT)radiomics and clinicoradiological factors to predict MVI and identify M2 among patients with hepatitis B virus-related HCC(HBV-HCC).The ultimate goal of the study was to guide surgical decision-making.METHODS A total of 270 patients who underwent surgical resection were retrospectively analyzed.The cohort was divided into a training dataset(189 patients)and a validation dataset(81)with a 7:3 ratio.Radiomics features were selected using intra-class correlation coefficient analysis,Pearson or Spearman’s correlation analysis,and the least absolute shrinkage and selection operator algorithm,leading to the construction of radscores from CECT images.Univariate and multivariate analyses identified significant clinicoradiological factors and radscores associated with MVI and M2,which were subsequently incorporated into predictive models.The models’performance was evaluated using calibration,discrimination,and clinical utility analysis.RESULTS Independent risk factors for MVI included non-smooth tumor margins,absence of a peritumoral hypointensity ring,and a high radscore based on delayed-phase CECT images.The MVI prediction model incorporating these factors achieved an area under the curve(AUC)of 0.841 in the training dataset and 0.768 in the validation dataset.The M2 prediction model,which integrated the radscore from the 5 mm peritumoral area in the CECT arterial phase,α-fetoprotein level,enhancing capsule,and aspartate aminotransferase level achieved an AUC of 0.865 in the training dataset and 0.798 in the validation dataset.Calibration and decision curve analyses confirmed the models’good fit and clinical utility.CONCLUSION Multivariable models were constructed by combining clinicoradiological risk factors and radscores to preoper-atively predict MVI and identify M2 among patients with HBV-HCC.Further studies are needed to evaluate the practical application of these models in clinical settings.
基金Supported by National Natural Science Foundation of China,No.81560278the Health Commission of Guangxi Zhuang Autonomous Region,No.Z-A20221157,No.Z20200953,and No.G201903023.
文摘BACKGROUND Despite continuous changes in treatment methods,the survival rate for advanced hepatocellular carcinoma(HCC)patients remains low,highlighting the importance of diagnostic methods for HCC.AIM To explore the efficacy of texture analysis based on multi-parametric magnetic resonance(MR)imaging(MRI)in predicting microvascular invasion(MVI)in preoperative HCC.METHODS This study included 105 patients with pathologically confirmed HCC,categorized into MVI-positive and MVI-negative groups.We employed Original Data Analysis,Principal Component Analysis,Linear Discriminant Analysis(LDA),and Non-LDA(NDA)for texture analysis using multi-parametric MR images to predict preoperative MVI.The effectiveness of texture analysis was determined using the B11 program of the MaZda4.6 software,with results expressed as the misjudgment rate(MCR).RESULTS Texture analysis using multi-parametric MRI,particularly the MI+PA+F dimensionality reduction method combined with NDA discrimination,demonstrated the most effective prediction of MVI in HCC.Prediction accuracy in the pulse and equilibrium phases was 83.81%.MCRs for the combination of T2-weighted imaging(T2WI),arterial phase,portal venous phase,and equilibrium phase were 22.86%,16.19%,20.95%,and 20.95%,respectively.The area under the curve for predicting MVI positivity was 0.844,with a sensitivity of 77.19%and specificity of 91.67%.CONCLUSION Texture analysis of arterial phase images demonstrated superior predictive efficacy for MVI in HCC compared to T2WI,portal venous,and equilibrium phases.This study provides an objective,non-invasive method for preoperative prediction of MVI,offering a theoretical foundation for the selection of clinical therapy.
基金the Tsinghua University Institute of Precision Medicine,No.2022ZLA006.
文摘BACKGROUND Hepatocellular carcinoma(HCC)recurrence is highly correlated with increased mortality.Microvascular invasion(MVI)is indicative of aggressive tumor biology in HCC.AIM To construct an artificial neural network(ANN)capable of accurately predicting MVI presence in HCC using magnetic resonance imaging.METHODS This study included 255 patients with HCC with tumors<3 cm.Radiologists annotated the tumors on the T1-weighted plain MR images.Subsequently,a three-layer ANN was constructed using image features as inputs to predict MVI status in patients with HCC.Postoperative pathological examination is considered the gold standard for determining MVI.Receiver operating characteristic analysis was used to evaluate the effectiveness of the algorithm.RESULTS Using the bagging strategy to vote for 50 classifier classification results,a prediction model yielded an area under the curve(AUC)of 0.79.Moreover,correlation analysis revealed that alpha-fetoprotein values and tumor volume were not significantly correlated with the occurrence of MVI,whereas tumor sphericity was significantly correlated with MVI(P<0.01).CONCLUSION Analysis of variable correlations regarding MVI in tumors with diameters<3 cm should prioritize tumor sphericity.The ANN model demonstrated strong predictive MVI for patients with HCC(AUC=0.79).
基金Supported by the National Natural Science Foundation of China,No.81902839.
文摘Hepatocellular carcinoma(HCC)is one of the most lethal tumors in the world.Liver resection(LR)and liver transplantation(LT)are widely considered as radical treatments for early HCC.However,the recurrence rates after curative treatment are still high and overall survival is unsatisfactory.Microvascular invasion(MVI)is considered to be one of the important prognostic factors affecting postoperative recurrence and long-term survival.Unfortunately,whether HCC patients with MVI should receive postoperative adjuvant therapy remains unknown.In this review,we summarize the therapeutic effects of transcatheter arterial chemoembolization,hepatic arterial infusion chemotherapy,tyrosine protein kinase inhibitor-based targeted therapy,and immune checkpoint inhibitors in patients with MVI after LR or LT,aiming to provide a reference for the best adjuvant treatment strategy for HCC patients with MVI after LT or LR.
基金Supported by the Key Program of Science and Technology Commission Foundation of Changning,No.CNKW2022Y61.
文摘BACKGROUND Microvascular invasion(MVI)is an important predictor of poor prognosis in patients with hepatocellular carcinoma(HCC).Accurate preoperative prediction of MVI in HCC would provide useful information to guide the choice of therapeutic strategy.Shear wave elastography(SWE)plays an important role in hepatic imaging,but its value in the preoperative prediction of MVI in HCC has not yet been proven.AIM To explore the value of conventional ultrasound features and SWE in the preoperative prediction of MVI in HCC.METHODS Patients with a postoperative pathological diagnosis of HCC and a definite diagnosis of MVI were enrolled in this study.Conventional ultrasound features and SWE features such as maximal elasticity(Emax)of HCCs and Emax of the periphery of HCCs were acquired before surgery.These features were compared between MVI-positive HCCs and MVI-negative HCCs and between mild MVI HCCs and severe MVI HCCs.RESULTS This study included 86 MVI-negative HCCs and 102 MVI-positive HCCs,including 54 with mild MVI and 48 with severe MVI.Maximal tumor diameters,surrounding liver tissue,color Doppler flow,Emax of HCCs,and Emax of the periphery of HCCs were significantly different between MVI-positive HCCs and MVI-negative HCCs.In addition,Emax of the periphery of HCCs was significantly different between mild MVI HCCs and severe MVI HCCs.Higher Emax of the periphery of HCCs and larger maximal diameters were independent risk factors for MVI,with odds ratios of 2.820 and 1.021,respectively.CONCLUSION HCC size and stiffness of the periphery of HCC are useful ultrasound criteria for predicting positive MVI.Preoperative ultrasound and SWE can provide useful information for the prediction of MVI in HCCs.
基金Supported by Beijing Hospitals Authority Youth Program,No.QML20231103.
文摘BACKGROUND Significant correlation between lymphatic,microvascular,and perineural invasion(LMPI)and the prognosis of pancreatic neuroendocrine tumors(PENTs)was confirmed by previous studies.There was no previous study reported the relationship between magnetic resonance imaging(MRI)parameters and LMPI.AIM To determine the feasibility of using preoperative MRI of the pancreas to predict LMPI in patients with non-functioning PENTs(NFPNETs).METHODS A total of 61 patients with NFPNETs who underwent MRI scans and lymphadenectomy from May 2011 to June 2018 were included in this retrospective study.The patients were divided into group 1(n=34,LMPI negative)and group 2(n=27,LMPI positive).The clinical characteristics and qualitative MRI features were collected.In order to predict LMPI status in NF-PNETs,a multivariate logistic regression model was constructed.Diagnostic performance was evaluated by calculating the receiver operator characteristic(ROC)curve with area under ROC,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV)and accuracy.RESULTS There were significant differences in the lymph node metastasis stage,tumor grade,neuron-specific enolase levels,tumor margin,main pancreatic ductal dilatation,common bile duct dilatation,enhancement pattern,vascular and adjacent tissue involvement,synchronous liver metastases,the long axis of the largest lymph node,the short axis of the largest lymph node,number of the lymph nodes with short axis>5 or 10 mm,and tumor volume between two groups(P<0.05).Multivariate analysis showed that tumor margin(odds ratio=11.523,P<0.001)was a predictive factor for LMPI of NF-PNETs.The area under the receiver value for the predictive performance of combined predictive factors was 0.855.The sensitivity,specificity,PPV,NPV and accuracy of the model were 48.1%(14/27),97.1%(33/34),97.1%(13/14),70.2%(33/47)and 0.754,respectively.CONCLUSION Using preoperative MRI,ill-defined tumor margins can effectively predict LMPI in patients with NF-PNETs.
基金Supported by Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor,Ministry of Education,No.GKZ201604Key Project of Guangxi Health and Family Planning Commission,China,No.S201513Key Project of Guangxi Science and Technology Department,China,No.Gui Ke AB16380242
文摘AIM To investigate the efficacy and safety of postoperative adjuvant transcatheter arterial chemoembolization(PA-TACE) in preventing tumor recurrence and improving survival in Barcelona Clinic Liver Cancer(BCLC) early(A) and intermediate(B) stage hepatocellular carcinoma(HCC) patients with microvascular invasion(MVI).METHODS A total of 519 BCLC A or B HCC patients treated by liver resection alone or followed by PA-TACE between January 2012 and December 2015 were studied retrospectively. Univariate and multivariate analyses were performed to investigate the risk factors for recurrence-free survival(RFS) and overall survival(OS). Multiple logistic regression was used to identify the clinicopathological characteristics associated with MVI. The rates of RFS and OS were compared among patients with or without MVI treated with liver resection alone or followed by PA-TACE. RESULTS Univariate and multivariate analyses demonstrated that serum AFP level > 400 ng/m L, tumor size > 5 cm, tumor capsule invasion, MVI, and major hepatectomy were risk factors for poor OS. Tumor capsule invasion, MVI, tumor size > 5 cm, HBV-DNA copies > 1 x 104 IU/m L, and multinodularity were risk factors for poor RFS. Multiple logistic regression identified serum AFP level > 400 ng/m L, tumor size > 5 cm, and tumor capsule invasion as independent predictors of MVI. Both OS and DFS were significantly improved in patients with MVI who received PA-TACE as compared to those who underwent liver resection alone. Patients without MVI did not show a significant difference in OS and RFS between those treated by liver resection alone or followed by PA-TACE.CONCLUSION PA-TACE is a safe adjuvant intervention and can efficiently prevent tumor recurrence and improve the survival of BCLC early-and intermediate-stage HCC patients with MVI.
基金Supported by the Shanghai Municipal Commission of Science and Technology, No. 19411951200Clinical Research Plan of SHDC, No. SHDC2020CR3020Athe Research Startup Fund of Huashan Hospital Fudan University, No.2021QD035
文摘Hepatocellular carcinoma(HCC)is the most common primary liver cancer,accounting for about 90%of liver cancer cases.It is currently the fifth most common cancer in the world and the third leading cause of cancer-related mortality.Moreover,recurrence of HCC is common.Microvascular invasion(MVI)is a major factor associated with recurrence in postoperative HCC.It is difficult to evaluate MVI using traditional imaging modalities.Currently,MVI is assessed primarily through pathological and immunohistochemical analyses of postoperative tissue samples.Needle biopsy is the primary method used to confirm MVI diagnosis before surgery.As the puncture specimens represent just a small part of the tumor,and given the heterogeneity of HCC,biopsy samples may yield false-negative results.Radiomics,an emerging,powerful,and non-invasive tool based on various imaging modalities,such as computed tomography,magnetic resonance imaging,ultrasound,and positron emission tomography,can predict the HCC-MVI status preoperatively by delineating the tumor and/or the regions at a certain distance from the surface of the tumor to extract the image features.Although positive results have been reported for radiomics,its drawbacks have limited its clinical translation.This article reviews the application of radiomics,based on various imaging modalities,in preoperative evaluation of HCC-MVI and explores future research directions that facilitate its clinical translation.
基金the National Natural Science Foundation of China,No.81672100the Key Laboratory for Laboratory Medicine of Jiangsu Province of China,No.ZDXKB2016005.
文摘BACKGROUND Microvascular invasion(MVI)is an important prognostic factor affecting early recurrence and overall survival in hepatocellular carcinoma(HCC)patients after hepatectomy and liver transplantation,but it can be determined only in surgical specimens.Accurate preoperative prediction of MVI is conducive to clinical decisions.AIM To develop and validate a preoperative prediction model for MVI in patients with HCC.METHODS Data from 454 patients with HCC who underwent hepatectomy at the First Affiliated Hospital of Nanjing Medical University between May 2016 and October 2019 were retrospectively collected.Then,the patients were nonrandomly split into a training cohort and a validation cohort.Logistic regression analysis was used to identify variables significantly associated with MVI that were then included in the nomogram.We evaluated the discrimination and calibration ability of the nomogram by using R software.RESULTS MVI was confirmed in 209(46.0%)patients by a pathological examination.Multivariate logistic regression analysis identified four risk factors independently associated with MVI:Tumor size[odds ratio(OR)=1.195;95%confidence interval(CI):1.107–1.290;P<0.001],number of tumors(OR=4.441;95%CI:2.112–9.341;P<0.001),neutrophils(OR=1.714;95%CI:1.036–2.836;P=0.036),and serumα-fetoprotein(20–400 ng/mL,OR=1.955;95%CI:1.055–3.624;P=0.033;>400 ng/mL,OR=3.476;95%CI:1.950–6.195;P<0.001).The concordance index was 0.79(95%CI:0.74–0.84)and 0.81(95%CI:0.74–0.89)in the training and validation cohorts,respectively.The calibration curves showed good agreement between the predicted risk by the nomogram and real outcomes.CONCLUSION We have developed and validated a preoperative prediction model for MVI in patients with HCC.The model could aid physicians in clinical treatment decision making.
基金Scientific Research Program of Hunan Provincial Health Commission,China,No.B2019072Changsha Science and Technology Project,China,No.kq1907062.
文摘BACKGROUND Liver cancer is one of the most common malignant tumors,and ranks as the fourth leading cause of cancer death worldwide.Microvascular invasion(MVI)is considered one of the most important factors for recurrence and poor prognosis of liver cancer.Thus,accurately identifying MVI before surgery is of great importance in making treatment strategies and predicting the prognosis of patients with hepatocellular carcinoma(HCC).Radiomics as an emerging field,aims to utilize artificial intelligence software to develop methods that may contribute to cancer diagnosis,treatment improvement and evaluation,and better prediction.AIM To investigate the predictive value of computed tomography radiomics for MVI in solitary HCC≤5 cm.METHODS A total of 185 HCC patients,including 122 MVI negative and 63 MVI positive patients,were retrospectively analyzed.All patients were randomly assigned to the training group(n=124)and validation group(n=61).A total of 1351 radiomic features were extracted based on three-dimensional images.The diagnostic performance of the radiomics model was verified in the validation group,and the Delong test was applied to compare the radiomics and MVIrelated imaging features(two-trait predictor of venous invasion and radiogenomic invasion).RESULTS A total of ten radiomics features were finally obtained after screening 1531 features.According to the weighting coefficient that corresponded to the features,the radiomics score(RS)calculation formula was obtained,and the RS score of each patient was calculated.The radiomics model exhibited a better correction and identification ability in the training and validation groups[area under the curve:0.72(95%confidence interval:0.58-0.86)and 0.74(95%confidence interval:0.66-0.83),respectively].Its prediction performance was significantly higher than that of the image features(P<0.05).CONCLUSION Computed tomography radiomics has certain predictive value for MVI in solitary HCC≤5 cm,and the predictive ability is higher than that of image features.
基金The National Key Research and Development Program of China,No.2016YFC0106004.
文摘BACKGROUND The long-term effect of anatomic resection(AR)is better than that of nonanatomic resection(NAR).At present,there is no study on microvascular invasion(MVI)and liver resection types.AIM To explore whether AR improves long-term survival in patients with hepatocellular carcinoma(HCC)by removing the peritumoral MVI.METHODS A total of 217 patients diagnosed with HCC were enrolled in the study.The surgical margin was routinely measured.According to the stratification of different tumor diameters,patients were divided into the following groups:≤2 cm group,2-5 cm group,and>5 cm group.RESULTS In the 2-5 cm diameter group,the overall survival(OS)of MVI positive patients was significantly better than that of MVI negative patients(P=0.031).For the MVI positive patients,there was a statistically significant difference between AR and NAR(P=0.027).AR leads to a wider surgical margin than NAR(2.0±2.3 cm vs 0.7±0.5 cm,P<0.001).In the groups with tumor diameters<2 cm,both AR and NAR can obtain a wide surgical margin,and the surgical margins of AR are wider than that of NAR(3.5±5.8 cm vs 1.6±0.5 cm,P=0.048).In the groups with tumor diameters>5 cm,both AR and NAR fail to obtain wide surgical margin(0.6±1.0 cm vs 0.7±0.4 cm,P=0.491).CONCLUSION For patients with a tumor diameter of 2-5 cm,AR can achieve the removal of peritumoral MVI by obtaining a wide incision margin,reduce postoperative recurrence,and improve prognosis.
基金Supported by Joint Funds for the Innovation of Science and Technology,Fujian Province (CN),No. 2019Y9125
文摘BACKGROUND The prognosis of hepatocellular carcinoma(HCC)remains poor and relapse occurs in more than half of patients within 2 years after hepatectomy.In terms of recent studies,microvascular invasion(MVI)is one of the potential predictors of recurrence.Accurate preoperative prediction of MVI is potentially beneficial to the optimization of treatment planning.AIM To develop a radiomic analysis model based on pre-operative magnetic resonance imaging(MRI)data to predict MVI in HCC.METHODS A total of 113 patients recruited to this study have been diagnosed as having HCC with histological confirmation,among whom 73 were found to have MVI and 40 were not.All the patients received preoperative examination by Gd-enhanced MRI and then curative hepatectomy.We manually delineated the tumor lesion on the largest cross-sectional area of the tumor and the adjacent two images on MRI,namely,the regions of interest.Quantitative analyses included most discriminant factors(MDFs)developed using linear discriminant analysis algorithm and histogram analysis with MaZda software.Independent significant variables of clinical and radiological features and MDFs for the prediction of MVI were estimated and a discriminant model was established by univariate and multivariate logistic regression analysis.Prediction ability of the above-mentioned parameters or model was then evaluated by receiver operating characteristic(ROC)curve analysis.Five-fold cross-validation was also applied via R software.RESULTS The area under the ROC curve(AUC)of the MDF(0.77-0.85)outperformed that of histogram parameters(0.51-0.74).After multivariate analysis,MDF values of the arterial and portal venous phase,and peritumoral hypointensity in the hepatobiliary phase were identified to be independent predictors of MVI(P<0.05).The AUC value of the model was 0.939[95%confidence interval(CI):0.893-0.984,standard error:0.023].The result of internal five-fold cross-validation(AUC:0.912,95%CI:0.841-0.959,standard error:0.0298)also showed favorable predictive efficacy.CONCLUSION Noninvasive MRI radiomic model based on MDF values and imaging biomarkers may be useful to make preoperative prediction of MVI in patients with primary HCC.
文摘Objective:Treatment strategies for recurrent hepatocellular carcinoma(rHCC)are controversial.We used the status of microvascular invasion(MVI)at primary resection as a marker to choose moderate treatment options for rHCC patients with Barcelona Clinic Liver Cancer(BCLC)stage B-C disease.Methods:From June 2009 to June 2017.