Objective:Histology grade,subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival.The aim of the study was to investigate the relationship between chromosomal instability,morphol...Objective:Histology grade,subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival.The aim of the study was to investigate the relationship between chromosomal instability,morphological subtypes and the grading system used in lung non-mucinous adenocarcinoma(LNMA).Methods:We developed a whole genome copy number variation(WGCNV)scoring system and applied next generation sequencing to evaluate CNVs present in 91 LNMA tumor samples.Results:Higher histological grades,aggressive subtypes and more advanced TNM staging were associated with an increased WGCNV score,particularly in CNV regions enriched for tumor suppressor genes and oncogenes.In addition,we demonstrate that 24-chromosome CNV profiling can be performed reliably from specific cell types(<100 cells)isolated by sample laser capture microdissection.Conclusions:Our findings suggest that the WGCNV scoring system we developed may have potential value as an adjunct test for predicting the prognosis of patients diagnosed with LNMA.展开更多
AIM: To establish a model for prognosis assessment of extranodal follicular dendritic cell (FDC) sarcoma.METHODS: Nine lesions were examined by routine and molecular approaches.Clinicopathological factors from the new...AIM: To establish a model for prognosis assessment of extranodal follicular dendritic cell (FDC) sarcoma.METHODS: Nine lesions were examined by routine and molecular approaches.Clinicopathological factors from the new cases and 97 reported cases were analyzed for their prognostic values.RESULTS: The current lesions were found in f ive male and four female patients,located mainly in the head and neck area and averaging 7.2 cm in size.Six patients had recurrence or metastasis and three remained free of disease.The 106 patients (male/female ratio,1.1:1) were aged from 9 to 82 years (median,44 years).The tumor sizes ranged from 1.5 to 21 cm (mean,7.4 cm).Abdominal/pelvic region was affected most frequently (43%).Surgical resection was performed in 100 patients,followed by radiation and/or chemotherapy in 35 of them.Follow-up data were available in 91 cases,covering a period of 3-324 mo (mean,27 mo;median,19 mo).Of the informative cases,38 (42%) had recurrence or metastasis,and 12 (13%) died of the disease.These tumors were classif ied histologically into lowand high-grade lesions.A size ≥ 5 cm (P = 0.003),highgrade histology (P = 0.046) and a mitotic count ≥ 5/10 HPF (P = 0.013) were associated with tumor recurrence.The lesions were def ined as low-,intermediateand high-risk tumors,and their recurrence rates were 16%,46% and 73%,and their mortality rates 0%,4% and 45%,respectively.CONCLUSION: Extranodal FDC tumors behave like soft tissue sarcomas.Their clinical outcomes are variable and can be evaluated according to their sizes and grades.展开更多
Objectives:To develop and validate a radiomics nomogram for preoperative prediction of tumor histologic grade in gastric adenocarcinoma(GA).Methods:This retrospective study enrolled 592 patients with clinicopathologic...Objectives:To develop and validate a radiomics nomogram for preoperative prediction of tumor histologic grade in gastric adenocarcinoma(GA).Methods:This retrospective study enrolled 592 patients with clinicopathologically confirmed GA(low-grade:n=154;high-grade:n=438)from January 2008 to March 2018 who were divided into training(n=450)and validation(n=142)sets according to the time of computed tomography(CT)examination.Radiomic features were extracted from the portal venous phase CT images.The Mann-Whitney U test and the least absolute shrinkage and selection operator(LASSO)regression model were used for feature selection,data dimension reduction and radiomics signature construction.Multivariable logistic regression analysis was applied to develop the prediction model.The radiomics signature and independent clinicopathologic risk factors were incorporated and presented as a radiomics nomogram.The performance of the nomogram was assessed with respect to its calibration and discrimination.Results:A radiomics signature containing 12 selected features was significantly associated with the histologic grade of GA(P<0.001 for both training and validation sets).A nomogram including the radiomics signature and tumor location as predictors was developed.The model showed both good calibration and good discrimination,in which C-index in the training set,0.752[95%confidence interval(95%CI):0.701-0.803];C-index in the validation set,0.793(95%CI:0.711-0.874).Conclusions:This study developed a radiomics nomogram that incorporates tumor location and radiomics signatures,which can be useful in facilitating preoperative individualized prediction of histologic grade of GA.展开更多
Background:Pre-operative non-invasive histological evaluation of hepatocellular carcinoma(HCC)remains a challenge.Tumor perfusion is significantly associated with the development and aggressiveness of HCC.The purpose ...Background:Pre-operative non-invasive histological evaluation of hepatocellular carcinoma(HCC)remains a challenge.Tumor perfusion is significantly associated with the development and aggressiveness of HCC.The purpose of the study was to evaluate the clinical value of quantitative liver perfusion parameters and corresponding histogram parameters derived from traditional triphasic enhanced computed tomography(CT)scans in predicting histological grade of HCC.Methods:Totally,52 patients with HCC were enrolled in this retrospective study and underwent triple-phase enhanced CT imaging.The blood perfusion parameters were derived from triple-phase CT scans.The relationship of liver perfusion parameters and corresponding histogram parameters with the histological grade of HCC was analyzed.Receiver operating characteristic(ROC)curve analysis was used to determine the optimal ability of the parameters to predict the tumor histological grade.Results:The variance of arterial enhancement fraction(AEF)was significantly higher in HCCs without poorly differentiated components(NP-HCCs)than in HCCs with poorly differentiated components(P-HCCs).The difference in hepatic blood flow(HF)between total tumor and total liver flow(ΔHF=HFtumor-HFliver)and relative flow(rHF=ΔHF/HF_(liver))were significantly higher in NP-HCCs than in P-HCCs.The difference in portal vein blood supply perfusion(PVP)between tumor and liver tissue(ΔPVP)and theΔPVP/liver PVP ratio(rPVP)were significantly higher in patients with NP-HCCs than in patients with P-HCCs.The area under ROC(AUC)ofΔPVP and rPVP were both 0.697 with a high sensitivity of 84.2%and specificity of only 56.2%.TheΔHF and rHF had a higher specificity of 87.5%with an AUC of 0.681 and 0.673,respectively.The combination of rHF and rPVP showed the highest AUC of 0.732 with a sensitivity of 57.9%and specificity of 93.8%.The combined parameter ofΔHF and rPVP,rHF and rPVP had the highest positive predictive value of 0.903,and that of rPVP andΔPVP had the highest negative predictive value of 0.781.Conclusion:Liver perfusion parameters and corresponding histogram parameters(includingΔHF,rHF,ΔPVP,rPVP,and AEFvariance)in patients with HCC derived from traditional triphasic CT scans may be helpful to non-invasively and pre-operatively predict the degree of the differentiation of HCC.展开更多
Background:Prediction models for the histological grade of hepatocellular carcinoma(HCC)remain unsatisfactory.The purpose of this study is to develop preoperative models to predict histological grade of HCC based on g...Background:Prediction models for the histological grade of hepatocellular carcinoma(HCC)remain unsatisfactory.The purpose of this study is to develop preoperative models to predict histological grade of HCC based on gadolinium-ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)-enhanced magnetic resonance imaging(MRI)radiomics.And to compare the performance between artificial neural network(ANN)and logistic regression model.Methods:A total of 122 HCCs were randomly assigned to the training set(n=85)and the test set(n=37).There were 242 radiomic features extracted from volumetric of interest(VOI)of arterial and hepatobiliary phases images.The radiomic features and clinical parameters[gender,age,alpha-fetoprotein(AFP),carcinoembryonic antigen(CEA),carbohydrate antigen 19-9(CA19-9),alanine aminotransferase(ALT),aspartate transaminase(AST)]were selected by permutation test and decision tree.ANN of arterial phase(ANN-AP),logistic regression model of arterial phase(LR-AP),ANN of hepatobiliary phase(ANN-HBP),logistic regression mode of hepatobiliary phase(LR-HBP),ANN of combined arterial and hepatobiliary phases(ANN-AP+HBP),and logistic regression model of combined arterial and hepatobiliary phases(LR-AP+HBP)were built to predict HCC histological grade.Those prediction models were assessed and compared.Results:ANN-AP and LR-AP were composed by AST and radiomic features based on arterial phase.ANN-HBP and LR-HBP were composed by AFP and radiomic features based on hepatobiliary phase.ANN-AP+HBP and LR-AP+HBP were composed by AST and radiomic features based on arterial and hepatobiliary phases.The prediction models could distinguish between high-grade tumors[Edmondson-Steiner(E-S)grade III and IV]and low-grade tumors(E-S grade I and II)in both training set and test set.In the test set,the AUCs of ANN-AP,LR-AP,ANN-HBP,LR-HBP,ANN-AP+HBP and LR-AP+HBP were 0.889,0.777,0.941,0.819,0.944 and 0.792 respectively.The ANN-HBP was significantly superior to LR-HBP(P=0.001).And the ANN-AP+HBP was significantly superior to LR-AP+HBP(P=0.007).Conclusions:Prediction models consisting of clinical parameters and Gd-EOB-DTPA-enhanced MRI radiomic features(based on arterial phase,hepatobiliary phase,and combined arterial and hepatobiliary phases)could distinguish between high-grade HCCs and low-grade HCCs.And the ANN was superior to logistic regression model in predicting histological grade of HCC.展开更多
Background:The 21-gene recurrence score(RS)assay has been recommended by major guidelines for treatment decision in hormone receptor(HR)-positive early breast cancer(EBC).However,the genomic assay is not accessible an...Background:The 21-gene recurrence score(RS)assay has been recommended by major guidelines for treatment decision in hormone receptor(HR)-positive early breast cancer(EBC).However,the genomic assay is not accessible and affordable worldwide.Alternatively,an increasing number of studies have shown that traditional immunohistochemistry(IHC)can partially or even completely replace the role of the 21-gene genomic assay.Here,we developed and validated a predictive model(IHC3 model)combining the Ki-67 index,progesterone receptor(PR)expression,histologic grade,and tumor size to predict the recurrence risk of HR-positive EBC.Methods:The data from 389 patients(development set)with HR-positive,human epidermal growth factor receptor 2-negative,lymph node non-metastasized invasive breast cancer were used to construct the IHC3 model based on the Surexam®21-gene RS and the TAILORx clinical trial criteria.An additional 146 patients with the same characteristics constituted the validation set.The predictive accuracy of the IHC3 model was compared with that of Orucevic et al.’s nomogram.Invasive diseasefree survival(IDFS)was analyzed in the IHC3 predictive low-recurrence risk(pLR)group and the predictive high-recurrence risk(pHR)group.The Pearson chi-square test,Fisher exact test,and log-rank test were used for analysis.Results:The pLR and pHR group could be easily stratified using the decision tree model without network dependence.The accuracies of the IHC3 model were 86.1%in the development set and 87.7%in the validation set.The predictive accuracy of the IHC3 model and Orucevic et al.’s nomogram for the whole cohort was 86.5%and 86.9%,respectively.After a 52-month of median follow-up,a significant difference was found in IDFS between of the IHC3 pLR and the pHR groups(P=0.001)but not in the IDFS between the low-and high-recurrence risk groups according to the Surexam®21-gene RS and the TAILORx clinical trial criteria(P=0.556)or 21-gene binary RS group(P=0.511).Conclusions:The proposed IHC3 model could reliably predict low and high recurrence risks in most HR-positive EBC patients.This easy-to-use predictive model may be a reliable replacement for the 21-gene genomic assay in patients with EBC who have no access to or cannot afford the 21-gene genomic assay.展开更多
基金grants from Beijing Hospital Key Research Program(121 Research Program,No.BJ2019-195)。
文摘Objective:Histology grade,subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival.The aim of the study was to investigate the relationship between chromosomal instability,morphological subtypes and the grading system used in lung non-mucinous adenocarcinoma(LNMA).Methods:We developed a whole genome copy number variation(WGCNV)scoring system and applied next generation sequencing to evaluate CNVs present in 91 LNMA tumor samples.Results:Higher histological grades,aggressive subtypes and more advanced TNM staging were associated with an increased WGCNV score,particularly in CNV regions enriched for tumor suppressor genes and oncogenes.In addition,we demonstrate that 24-chromosome CNV profiling can be performed reliably from specific cell types(<100 cells)isolated by sample laser capture microdissection.Conclusions:Our findings suggest that the WGCNV scoring system we developed may have potential value as an adjunct test for predicting the prognosis of patients diagnosed with LNMA.
基金Supported by Grants from National Natural Science Foundation of China,No.30171052,30572125 and 30772508
文摘AIM: To establish a model for prognosis assessment of extranodal follicular dendritic cell (FDC) sarcoma.METHODS: Nine lesions were examined by routine and molecular approaches.Clinicopathological factors from the new cases and 97 reported cases were analyzed for their prognostic values.RESULTS: The current lesions were found in f ive male and four female patients,located mainly in the head and neck area and averaging 7.2 cm in size.Six patients had recurrence or metastasis and three remained free of disease.The 106 patients (male/female ratio,1.1:1) were aged from 9 to 82 years (median,44 years).The tumor sizes ranged from 1.5 to 21 cm (mean,7.4 cm).Abdominal/pelvic region was affected most frequently (43%).Surgical resection was performed in 100 patients,followed by radiation and/or chemotherapy in 35 of them.Follow-up data were available in 91 cases,covering a period of 3-324 mo (mean,27 mo;median,19 mo).Of the informative cases,38 (42%) had recurrence or metastasis,and 12 (13%) died of the disease.These tumors were classif ied histologically into lowand high-grade lesions.A size ≥ 5 cm (P = 0.003),highgrade histology (P = 0.046) and a mitotic count ≥ 5/10 HPF (P = 0.013) were associated with tumor recurrence.The lesions were def ined as low-,intermediateand high-risk tumors,and their recurrence rates were 16%,46% and 73%,and their mortality rates 0%,4% and 45%,respectively.CONCLUSION: Extranodal FDC tumors behave like soft tissue sarcomas.Their clinical outcomes are variable and can be evaluated according to their sizes and grades.
基金supported by the National Key Research and Development Program of China(No.2017YFC 1309100)the National Science Fund for Distinguished Young Scholars(No.81925023)the National Natural Science Foundation of China(No.82071892,81771912,81901910)。
文摘Objectives:To develop and validate a radiomics nomogram for preoperative prediction of tumor histologic grade in gastric adenocarcinoma(GA).Methods:This retrospective study enrolled 592 patients with clinicopathologically confirmed GA(low-grade:n=154;high-grade:n=438)from January 2008 to March 2018 who were divided into training(n=450)and validation(n=142)sets according to the time of computed tomography(CT)examination.Radiomic features were extracted from the portal venous phase CT images.The Mann-Whitney U test and the least absolute shrinkage and selection operator(LASSO)regression model were used for feature selection,data dimension reduction and radiomics signature construction.Multivariable logistic regression analysis was applied to develop the prediction model.The radiomics signature and independent clinicopathologic risk factors were incorporated and presented as a radiomics nomogram.The performance of the nomogram was assessed with respect to its calibration and discrimination.Results:A radiomics signature containing 12 selected features was significantly associated with the histologic grade of GA(P<0.001 for both training and validation sets).A nomogram including the radiomics signature and tumor location as predictors was developed.The model showed both good calibration and good discrimination,in which C-index in the training set,0.752[95%confidence interval(95%CI):0.701-0.803];C-index in the validation set,0.793(95%CI:0.711-0.874).Conclusions:This study developed a radiomics nomogram that incorporates tumor location and radiomics signatures,which can be useful in facilitating preoperative individualized prediction of histologic grade of GA.
文摘Background:Pre-operative non-invasive histological evaluation of hepatocellular carcinoma(HCC)remains a challenge.Tumor perfusion is significantly associated with the development and aggressiveness of HCC.The purpose of the study was to evaluate the clinical value of quantitative liver perfusion parameters and corresponding histogram parameters derived from traditional triphasic enhanced computed tomography(CT)scans in predicting histological grade of HCC.Methods:Totally,52 patients with HCC were enrolled in this retrospective study and underwent triple-phase enhanced CT imaging.The blood perfusion parameters were derived from triple-phase CT scans.The relationship of liver perfusion parameters and corresponding histogram parameters with the histological grade of HCC was analyzed.Receiver operating characteristic(ROC)curve analysis was used to determine the optimal ability of the parameters to predict the tumor histological grade.Results:The variance of arterial enhancement fraction(AEF)was significantly higher in HCCs without poorly differentiated components(NP-HCCs)than in HCCs with poorly differentiated components(P-HCCs).The difference in hepatic blood flow(HF)between total tumor and total liver flow(ΔHF=HFtumor-HFliver)and relative flow(rHF=ΔHF/HF_(liver))were significantly higher in NP-HCCs than in P-HCCs.The difference in portal vein blood supply perfusion(PVP)between tumor and liver tissue(ΔPVP)and theΔPVP/liver PVP ratio(rPVP)were significantly higher in patients with NP-HCCs than in patients with P-HCCs.The area under ROC(AUC)ofΔPVP and rPVP were both 0.697 with a high sensitivity of 84.2%and specificity of only 56.2%.TheΔHF and rHF had a higher specificity of 87.5%with an AUC of 0.681 and 0.673,respectively.The combination of rHF and rPVP showed the highest AUC of 0.732 with a sensitivity of 57.9%and specificity of 93.8%.The combined parameter ofΔHF and rPVP,rHF and rPVP had the highest positive predictive value of 0.903,and that of rPVP andΔPVP had the highest negative predictive value of 0.781.Conclusion:Liver perfusion parameters and corresponding histogram parameters(includingΔHF,rHF,ΔPVP,rPVP,and AEFvariance)in patients with HCC derived from traditional triphasic CT scans may be helpful to non-invasively and pre-operatively predict the degree of the differentiation of HCC.
基金This study has received funding by Outstanding Youth supported by Medical Science and Technology Development Foundation Nanjing(JQX16022)Jiangsu Province Key Medical Young Talents,“13th Five-Year”Health Promotion Project of Jiangsu Province(QNRC2016041)+2 种基金The study was conducted in accordance with the Declaration of Helsinki(as revised in 2013)The study was approved by local institutional review board(No.2019AE01036)informed consent from patients was waived due to its retrospective nature。
文摘Background:Prediction models for the histological grade of hepatocellular carcinoma(HCC)remain unsatisfactory.The purpose of this study is to develop preoperative models to predict histological grade of HCC based on gadolinium-ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)-enhanced magnetic resonance imaging(MRI)radiomics.And to compare the performance between artificial neural network(ANN)and logistic regression model.Methods:A total of 122 HCCs were randomly assigned to the training set(n=85)and the test set(n=37).There were 242 radiomic features extracted from volumetric of interest(VOI)of arterial and hepatobiliary phases images.The radiomic features and clinical parameters[gender,age,alpha-fetoprotein(AFP),carcinoembryonic antigen(CEA),carbohydrate antigen 19-9(CA19-9),alanine aminotransferase(ALT),aspartate transaminase(AST)]were selected by permutation test and decision tree.ANN of arterial phase(ANN-AP),logistic regression model of arterial phase(LR-AP),ANN of hepatobiliary phase(ANN-HBP),logistic regression mode of hepatobiliary phase(LR-HBP),ANN of combined arterial and hepatobiliary phases(ANN-AP+HBP),and logistic regression model of combined arterial and hepatobiliary phases(LR-AP+HBP)were built to predict HCC histological grade.Those prediction models were assessed and compared.Results:ANN-AP and LR-AP were composed by AST and radiomic features based on arterial phase.ANN-HBP and LR-HBP were composed by AFP and radiomic features based on hepatobiliary phase.ANN-AP+HBP and LR-AP+HBP were composed by AST and radiomic features based on arterial and hepatobiliary phases.The prediction models could distinguish between high-grade tumors[Edmondson-Steiner(E-S)grade III and IV]and low-grade tumors(E-S grade I and II)in both training set and test set.In the test set,the AUCs of ANN-AP,LR-AP,ANN-HBP,LR-HBP,ANN-AP+HBP and LR-AP+HBP were 0.889,0.777,0.941,0.819,0.944 and 0.792 respectively.The ANN-HBP was significantly superior to LR-HBP(P=0.001).And the ANN-AP+HBP was significantly superior to LR-AP+HBP(P=0.007).Conclusions:Prediction models consisting of clinical parameters and Gd-EOB-DTPA-enhanced MRI radiomic features(based on arterial phase,hepatobiliary phase,and combined arterial and hepatobiliary phases)could distinguish between high-grade HCCs and low-grade HCCs.And the ANN was superior to logistic regression model in predicting histological grade of HCC.
基金This study was funded by the science and technology commission of Beijing:Optimization of breast cancer screening program for 35-75 years old women in Beijing(Grant No.D161100000816005)。
文摘Background:The 21-gene recurrence score(RS)assay has been recommended by major guidelines for treatment decision in hormone receptor(HR)-positive early breast cancer(EBC).However,the genomic assay is not accessible and affordable worldwide.Alternatively,an increasing number of studies have shown that traditional immunohistochemistry(IHC)can partially or even completely replace the role of the 21-gene genomic assay.Here,we developed and validated a predictive model(IHC3 model)combining the Ki-67 index,progesterone receptor(PR)expression,histologic grade,and tumor size to predict the recurrence risk of HR-positive EBC.Methods:The data from 389 patients(development set)with HR-positive,human epidermal growth factor receptor 2-negative,lymph node non-metastasized invasive breast cancer were used to construct the IHC3 model based on the Surexam®21-gene RS and the TAILORx clinical trial criteria.An additional 146 patients with the same characteristics constituted the validation set.The predictive accuracy of the IHC3 model was compared with that of Orucevic et al.’s nomogram.Invasive diseasefree survival(IDFS)was analyzed in the IHC3 predictive low-recurrence risk(pLR)group and the predictive high-recurrence risk(pHR)group.The Pearson chi-square test,Fisher exact test,and log-rank test were used for analysis.Results:The pLR and pHR group could be easily stratified using the decision tree model without network dependence.The accuracies of the IHC3 model were 86.1%in the development set and 87.7%in the validation set.The predictive accuracy of the IHC3 model and Orucevic et al.’s nomogram for the whole cohort was 86.5%and 86.9%,respectively.After a 52-month of median follow-up,a significant difference was found in IDFS between of the IHC3 pLR and the pHR groups(P=0.001)but not in the IDFS between the low-and high-recurrence risk groups according to the Surexam®21-gene RS and the TAILORx clinical trial criteria(P=0.556)or 21-gene binary RS group(P=0.511).Conclusions:The proposed IHC3 model could reliably predict low and high recurrence risks in most HR-positive EBC patients.This easy-to-use predictive model may be a reliable replacement for the 21-gene genomic assay in patients with EBC who have no access to or cannot afford the 21-gene genomic assay.
