Introduction: Meningiomas are the most common type of extra-axial neoplasm. Peritumoral brain edema (PTBE) can be seen around meningiomas while it may be absent in others. Despite that Ki67 proliferative index has bee...Introduction: Meningiomas are the most common type of extra-axial neoplasm. Peritumoral brain edema (PTBE) can be seen around meningiomas while it may be absent in others. Despite that Ki67 proliferative index has been previously correlated with meningioma grades, no definite relationship has been established in relation to PTBE in meningioma patients. Objective: Correlate the peritumoral brain edema with the Ki67 proliferative index of meningiomas. Patients & Methods: Aclinical prospective study was conducted on 56 patients (47 women, 9 men;mean age 50.89 ± 12.55 years) diagnosed with meningiomas. All patients were evaluated regarding the presence of brain edema surrounding the lesion in pre-operative neuroimaging using T2W and FLAIR MR images. Immunohistochemical staining of Ki67 index (representing proliferative activity) was done. Correlation between presence of PTBE and Ki67 index values was evaluated. Results: PTBE was found in nearly half of the patients (48.2%), while the remaining (51.8%) of patients did not exhibit PTBE in their pre-operative neuroimaging. The mean value of Ki67 index in meningioma patients with PTBE was 4.83% compared to a value of 1.83% in patients without PTBE, P value = 0.014. Conclusion: High Ki67 indices are evident in meningiomas with surrounding peritumoral brain edema (PTBE).展开更多
Objective: To determine whether VEGF plays a role in the development of peritumoral brain edema. Methods 50 meningioma patients and their VEGF expression were studied. We took a monoclonal antibody from mouse to VEGF ...Objective: To determine whether VEGF plays a role in the development of peritumoral brain edema. Methods 50 meningioma patients and their VEGF expression were studied. We took a monoclonal antibody from mouse to VEGF to stain the tumor cells, the vascular endothelial cells and the interstitial cells. The severity of brain edema was evaluated according to CT or MR scans by the following equation: edema index= V tumor +edema /Vtumor. The relationship between VEGF expression and edema index was analyzed statistically. Results VEGF was expressed in meningioma tumor cells, which is usually concentrated at the peripheral sites of the tumor. There was a positive linear correlation between the expression and the brain edema index. Conclusion VEGF may play a role in the development of peritumoral brain edema in meningioma patient.展开更多
BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in a...BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner,and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma(HCC).AIM To develop and validate a preoperative nomogram using contrast-enhanced computed tomography(CECT)to predict the presence of VETC+in HCC.METHODS We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers.Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase.Radiomics features,essential for identifying VETC+HCC,were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set.The model’s performance was validated on two separate test sets.Receiver operating characteristic(ROC)analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets.The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features.ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features,the radiomics features and the radiomics nomogram.RESULTS The study included 190 individuals from two independent centers,with the majority being male(81%)and a median age of 57 years(interquartile range:51-66).The area under the curve(AUC)for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825,0.788,and 0.680 in the training set and the two test sets.A total of 13 features were selected to construct the Rad-score.The nomogram,combining clinicalradiological and combined radiomics features could accurately predict VETC+in all three sets,with AUC values of 0.859,0.848 and 0.757.Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models.CONCLUSION This study demonstrates the potential utility of a CECT-based radiomics nomogram,incorporating clinicalradiological features and combined radiomics features,in the identification of VETC+HCC.展开更多
Metabolic reprogramming is a key feature driving oncogenesis in cancers. Recent studies have revealed that protein metabolism is largely altered in gliomas facilitating its malignant growth. Urea is the end product of...Metabolic reprogramming is a key feature driving oncogenesis in cancers. Recent studies have revealed that protein metabolism is largely altered in gliomas facilitating its malignant growth. Urea is the end product of nitrogen metabolism which is mainly produced by arginase. The interdependence of arginase and other biochemical mechanisms triggered scientific research interest. This research aimed to investigate the relationships between the urea as the main parameter of protein metabolism and glioma progression. It was also the most pronounced relationship between urea and the level of the nuclear protein Ki-67 as a marker of proliferative activity and O-6-methylguanine-DNA methyltransferase (MGMT), which performs DNA repair. Postoperative material from 20 patients with gliomas of different grades of anaplasia was analyzed.展开更多
目的探讨动态对比增强MRI(dynamic contrast-enhancement MRI,DCE-MRI)瘤周血管特征结合瘤内血流动力学参数在乳腺影像报告和数据系统(breast imaging reporting and data system,BI-RADS)4类肿瘤中的鉴别诊断价值。材料与方法回顾性分...目的探讨动态对比增强MRI(dynamic contrast-enhancement MRI,DCE-MRI)瘤周血管特征结合瘤内血流动力学参数在乳腺影像报告和数据系统(breast imaging reporting and data system,BI-RADS)4类肿瘤中的鉴别诊断价值。材料与方法回顾性分析2018年8月至2023年3月于大连医科大学附属第一医院行乳腺MRI检查为BI-RADS 4类且病理结果明确肿瘤的女性病例102例,其中良性组43例,恶性组59例。记录患者年龄、病灶最大径(dmax)、乳腺DCE-MRI基本影像学特征、瘤周血管特征及瘤内血流动力学参数值。通过单因素和多因素logistic回归分析比较两组间多参数的差异,利用受试者工作特征(receiver operating characteristic,ROC)曲线以及曲线下面积(area under the curve,AUC)分析瘤周血管特征指标与瘤内参数值联合应用对BI-RADS 4类乳腺良恶性两组肿瘤鉴别的诊断效能。应用DeLong检验对AUC进行比较。结果乳腺良性组和恶性组病例在年龄、dmax、背景实质强化(background parenchymal enhancement,BPE)、纤维腺体组织量(fibroglandular tissue,FGT)、瘤周相邻血管征(adjacent vascular sign,AVS)数目、瘤周血管最大径、患侧瘤周与健侧同一象限血管直径差值(△d)、瘤周血管出现期相以及瘤内容积转移常数(volume transfer constant,K^(trans))、速率常数(flux rate constant,K_(ep))、最大增强斜率(maximum slope of increase,MSI)和时间-信号强度曲线(time-signal intensity curve,TIC)类型的差异均具有统计学意义(P<0.05),而病变位置、信号增强率(signal enhancement ratio,SER)和血管外细胞外间隙容积比(volume fraction of extravascular extra vascular space,V_(e))差异无统计学意义(P>0.05)。通过多因素logistic回归分析结果显示,△d、dmax、MSI和K^(trans)为区分两组间的独立影响因素,其中优势比最大的是MSI值(AUC为0.923)。将瘤周血管特征△d分别与dmax、MSI和K^(trans)进行两者联合模型比较,以△d与MSI联合模型的诊断效能最高(AUC为0.933,敏感度和特异度分别为93.2%和83.7%),且△d联合MSI与△d联合K^(trans)比较的差异具有统计学意义(P=0.001);其他联合指标在两两比较时差异无统计学意义(P>0.05),联合模型高于单独MSI模型的诊断效能。结论瘤周血管特征指标(△d)联合瘤内半定量(MSI)血流动力学参数对评价BI-RADS 4类乳腺肿瘤具有较好的鉴别诊断价值。展开更多
文摘Introduction: Meningiomas are the most common type of extra-axial neoplasm. Peritumoral brain edema (PTBE) can be seen around meningiomas while it may be absent in others. Despite that Ki67 proliferative index has been previously correlated with meningioma grades, no definite relationship has been established in relation to PTBE in meningioma patients. Objective: Correlate the peritumoral brain edema with the Ki67 proliferative index of meningiomas. Patients & Methods: Aclinical prospective study was conducted on 56 patients (47 women, 9 men;mean age 50.89 ± 12.55 years) diagnosed with meningiomas. All patients were evaluated regarding the presence of brain edema surrounding the lesion in pre-operative neuroimaging using T2W and FLAIR MR images. Immunohistochemical staining of Ki67 index (representing proliferative activity) was done. Correlation between presence of PTBE and Ki67 index values was evaluated. Results: PTBE was found in nearly half of the patients (48.2%), while the remaining (51.8%) of patients did not exhibit PTBE in their pre-operative neuroimaging. The mean value of Ki67 index in meningioma patients with PTBE was 4.83% compared to a value of 1.83% in patients without PTBE, P value = 0.014. Conclusion: High Ki67 indices are evident in meningiomas with surrounding peritumoral brain edema (PTBE).
文摘Objective: To determine whether VEGF plays a role in the development of peritumoral brain edema. Methods 50 meningioma patients and their VEGF expression were studied. We took a monoclonal antibody from mouse to VEGF to stain the tumor cells, the vascular endothelial cells and the interstitial cells. The severity of brain edema was evaluated according to CT or MR scans by the following equation: edema index= V tumor +edema /Vtumor. The relationship between VEGF expression and edema index was analyzed statistically. Results VEGF was expressed in meningioma tumor cells, which is usually concentrated at the peripheral sites of the tumor. There was a positive linear correlation between the expression and the brain edema index. Conclusion VEGF may play a role in the development of peritumoral brain edema in meningioma patient.
基金The study was reviewed and approved by the Second Hospital of Shandong University Institutional Review Board,IRB No.KYLL-2023LW044.
文摘BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner,and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma(HCC).AIM To develop and validate a preoperative nomogram using contrast-enhanced computed tomography(CECT)to predict the presence of VETC+in HCC.METHODS We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers.Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase.Radiomics features,essential for identifying VETC+HCC,were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set.The model’s performance was validated on two separate test sets.Receiver operating characteristic(ROC)analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets.The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features.ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features,the radiomics features and the radiomics nomogram.RESULTS The study included 190 individuals from two independent centers,with the majority being male(81%)and a median age of 57 years(interquartile range:51-66).The area under the curve(AUC)for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825,0.788,and 0.680 in the training set and the two test sets.A total of 13 features were selected to construct the Rad-score.The nomogram,combining clinicalradiological and combined radiomics features could accurately predict VETC+in all three sets,with AUC values of 0.859,0.848 and 0.757.Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models.CONCLUSION This study demonstrates the potential utility of a CECT-based radiomics nomogram,incorporating clinicalradiological features and combined radiomics features,in the identification of VETC+HCC.
文摘Metabolic reprogramming is a key feature driving oncogenesis in cancers. Recent studies have revealed that protein metabolism is largely altered in gliomas facilitating its malignant growth. Urea is the end product of nitrogen metabolism which is mainly produced by arginase. The interdependence of arginase and other biochemical mechanisms triggered scientific research interest. This research aimed to investigate the relationships between the urea as the main parameter of protein metabolism and glioma progression. It was also the most pronounced relationship between urea and the level of the nuclear protein Ki-67 as a marker of proliferative activity and O-6-methylguanine-DNA methyltransferase (MGMT), which performs DNA repair. Postoperative material from 20 patients with gliomas of different grades of anaplasia was analyzed.
文摘目的探讨动态对比增强MRI(dynamic contrast-enhancement MRI,DCE-MRI)瘤周血管特征结合瘤内血流动力学参数在乳腺影像报告和数据系统(breast imaging reporting and data system,BI-RADS)4类肿瘤中的鉴别诊断价值。材料与方法回顾性分析2018年8月至2023年3月于大连医科大学附属第一医院行乳腺MRI检查为BI-RADS 4类且病理结果明确肿瘤的女性病例102例,其中良性组43例,恶性组59例。记录患者年龄、病灶最大径(dmax)、乳腺DCE-MRI基本影像学特征、瘤周血管特征及瘤内血流动力学参数值。通过单因素和多因素logistic回归分析比较两组间多参数的差异,利用受试者工作特征(receiver operating characteristic,ROC)曲线以及曲线下面积(area under the curve,AUC)分析瘤周血管特征指标与瘤内参数值联合应用对BI-RADS 4类乳腺良恶性两组肿瘤鉴别的诊断效能。应用DeLong检验对AUC进行比较。结果乳腺良性组和恶性组病例在年龄、dmax、背景实质强化(background parenchymal enhancement,BPE)、纤维腺体组织量(fibroglandular tissue,FGT)、瘤周相邻血管征(adjacent vascular sign,AVS)数目、瘤周血管最大径、患侧瘤周与健侧同一象限血管直径差值(△d)、瘤周血管出现期相以及瘤内容积转移常数(volume transfer constant,K^(trans))、速率常数(flux rate constant,K_(ep))、最大增强斜率(maximum slope of increase,MSI)和时间-信号强度曲线(time-signal intensity curve,TIC)类型的差异均具有统计学意义(P<0.05),而病变位置、信号增强率(signal enhancement ratio,SER)和血管外细胞外间隙容积比(volume fraction of extravascular extra vascular space,V_(e))差异无统计学意义(P>0.05)。通过多因素logistic回归分析结果显示,△d、dmax、MSI和K^(trans)为区分两组间的独立影响因素,其中优势比最大的是MSI值(AUC为0.923)。将瘤周血管特征△d分别与dmax、MSI和K^(trans)进行两者联合模型比较,以△d与MSI联合模型的诊断效能最高(AUC为0.933,敏感度和特异度分别为93.2%和83.7%),且△d联合MSI与△d联合K^(trans)比较的差异具有统计学意义(P=0.001);其他联合指标在两两比较时差异无统计学意义(P>0.05),联合模型高于单独MSI模型的诊断效能。结论瘤周血管特征指标(△d)联合瘤内半定量(MSI)血流动力学参数对评价BI-RADS 4类乳腺肿瘤具有较好的鉴别诊断价值。
