Objective To investigate the difference in texture features on diffusion weighted imaging(DWI) images between breast benign and malignant tumors.Methods Patients including 56 with mass-like breast cancer, 16 with brea...Objective To investigate the difference in texture features on diffusion weighted imaging(DWI) images between breast benign and malignant tumors.Methods Patients including 56 with mass-like breast cancer, 16 with breast fibroadenoma, and 4 with intraductal papilloma of breast treated in the Hainan Hospital of Chinese PLA General Hospital were retrospectively enrolled in this study, and allocated to the benign group(20 patients) and the malignant group(56 patients) according to the post-surgically pathological results. Texture analysis was performed on axial DWI images, and five characteristic parameters including Angular Second Moment(ASM), Contrast, Correlation, Inverse Difference Moment(IDM), and Entropy were calculated. Independent sample t-test and Mann-Whitney U test were performed for intergroup comparison. Regression model was established by using Binary Logistic regression analysis, and receiver operating characteristic curve(ROC) analysis was carried out to evaluate the diagnostic efficiency. Results The texture features ASM, Contrast, Correlation and Entropy showed significant differences between the benign and malignant breast tumor groups(PASM= 0.014, Pcontrast= 0.019, Pcorrelation= 0.010, Pentropy= 0.007). The area under the ROC curve was 0.685, 0.681, 0.754, and 0.683 respectively for the positive texture variables mentioned above, and that for the combined variables(ASM, Contrast, and Entropy) was 0.802 in the model of Logistic regression. Binary Logistic regression analysis demonstrated that ASM, Contrast and Entropy were considered as thespecific imaging variables for the differential diagnosis of breast benign and malignant tumors.Conclusion The texture analysis of DWI may be a simple and effective tool in the differential diagnosis between breast benign and malignant tumors.展开更多
目的探讨手术前后淋巴细胞和单核细胞计数比(lymphocyte to monocyte ratio,LMR)对结直肠癌患者预后判断价值。方法收集解放军总医院海南医院2012年12月至2019年6月经手术病理确诊的结直肠腺癌患者95例,计算患者手术前后LMR并分析其对5...目的探讨手术前后淋巴细胞和单核细胞计数比(lymphocyte to monocyte ratio,LMR)对结直肠癌患者预后判断价值。方法收集解放军总医院海南医院2012年12月至2019年6月经手术病理确诊的结直肠腺癌患者95例,计算患者手术前后LMR并分析其对5年无进展生存(progression free survival,PFS)和总生存(overall survival,OS)的预测价值。结果术前LMR对患者PFS(AUC=0.62,P=0.04,敏感性为29.80%,特异性为41.70%)和OS(AUC=0.64,P=0.02,敏感性为27.30%,特异性为41.20%)具有预测价值,而术后LMR未发现明显预测价值;以4.01为界将术前LMR分为低LMR组(<4.01)和高LMR组(≥4.01),不同术前LMR在不同性别、年龄等参数中无明显差异,术前高LMR组患者PFS时间[(52.69±26.39)月比(32.17±27.90)月,P<0.01]和OS时间[(57.38±26.39)月比(38.49±26.29)月,P<0.01]均明显优于低LMR组;多因素分析显示术前LMR是患者PFS(HR=0.82,95%CI:0.68~0.98,P=0.03)和OS(HR=0.82,95%CI:0.67~1.00,P=0.05)的独立预后因素。结论术前LMR对结直肠癌患者预后判断具有一定价值,术前LMR高的患者预后相对较好。展开更多
文摘Objective To investigate the difference in texture features on diffusion weighted imaging(DWI) images between breast benign and malignant tumors.Methods Patients including 56 with mass-like breast cancer, 16 with breast fibroadenoma, and 4 with intraductal papilloma of breast treated in the Hainan Hospital of Chinese PLA General Hospital were retrospectively enrolled in this study, and allocated to the benign group(20 patients) and the malignant group(56 patients) according to the post-surgically pathological results. Texture analysis was performed on axial DWI images, and five characteristic parameters including Angular Second Moment(ASM), Contrast, Correlation, Inverse Difference Moment(IDM), and Entropy were calculated. Independent sample t-test and Mann-Whitney U test were performed for intergroup comparison. Regression model was established by using Binary Logistic regression analysis, and receiver operating characteristic curve(ROC) analysis was carried out to evaluate the diagnostic efficiency. Results The texture features ASM, Contrast, Correlation and Entropy showed significant differences between the benign and malignant breast tumor groups(PASM= 0.014, Pcontrast= 0.019, Pcorrelation= 0.010, Pentropy= 0.007). The area under the ROC curve was 0.685, 0.681, 0.754, and 0.683 respectively for the positive texture variables mentioned above, and that for the combined variables(ASM, Contrast, and Entropy) was 0.802 in the model of Logistic regression. Binary Logistic regression analysis demonstrated that ASM, Contrast and Entropy were considered as thespecific imaging variables for the differential diagnosis of breast benign and malignant tumors.Conclusion The texture analysis of DWI may be a simple and effective tool in the differential diagnosis between breast benign and malignant tumors.
