基于多模态MRI特征构建的预测模型用于BI-RADS 4类乳腺肿瘤良恶性鉴别诊断价值分析  

Value analysis of the prediction model based on multimodal MRI characteristics for the differential diagnosis of benign and malignant BI-RADS 4 types of breast tumors

作　　者：朱彬 万涛 许华 贾浩 陈士新 Zhu Bin;Wan Tao;Xu Hua;Jia Hao;Chen Shixin(Department of Imaging,3201 Hospital,Hanzhong 723000,China)

机构地区：[1]三二〇一医院影像科,汉中723000

出　　处：《国际肿瘤学杂志》2024年第11期678-683,共6页Journal of International Oncology

摘　　要：目的探讨基于多模态MRI特征构建的预测模型用于乳腺影像报告和数据系统(BI-RADS)4类乳腺肿瘤良恶性的鉴别诊断价值。方法回顾性纳入2018年1月—2023年1月于三二〇一医院行对比增强MRI检查证实为BI-RADS 4类乳腺肿瘤的患者204例,根据手术后病理组织学检查结果分为恶性组(124例)和良性组(80例),比较两组临床及MRI影像学特征资料;对BI-RADS 4类乳腺肿瘤良恶性鉴别诊断指标进行多因素logistic回归分析;构建BI-RADS 4类乳腺肿瘤良恶性鉴别诊断预测模型;采用受试者操作特征(ROC)曲线比较各指标对BI-RADS 4类乳腺肿瘤良恶性的鉴别诊断价值。结果恶性组和良性组年龄(t=7.78,P<0.001)、内部强化类型(χ^(2)=14.50,P=0.002)、表观弥散系数(t=-6.77,P<0.001)、纵向弛豫时间(T_(1))值(t=-6.15,P<0.001)、纵向弛豫率(R_(1))值(t=7.02,P<0.001)差异均具有统计学意义。多因素分析显示,年龄(OR=1.16,95%CI为1.07~1.25,P<0.001)、内部强化类型(不均匀:OR=8.08,95%CI为2.21~29.51,P=0.002)、表观弥散系数(OR=0.01,95%CI为0.00~0.05,P<0.001)、T_(1)值(OR=0.99,95%CI为0.99~1.00,P<0.001)及R_(1)值(OR=1043.50,95%CI为46.48~23426.36,P<0.001)均是BI-RADS 4类乳腺肿瘤良恶性鉴别诊断的独立影响因素。依据多因素分析结果构建BI-RADS 4类乳腺肿瘤良恶性鉴别诊断的logistic回归模型,logit(P)=0.05+0.15×年龄+2.09×内部强化类型−5.21×表观弥散系数−0.01×T_(1)值+6.95×R_(1)值。ROC曲线分析显示,利用年龄、内部强化类型、表观弥散系数、T_(1)值、R_(1)值、logistic回归模型P值对于乳腺肿瘤良恶性进行鉴别诊断,约登指数分别为40.60%、39.68%、49.44%、38.23%、43.27%、75.70%,ROC曲线下面积分别为0.757、0.647、0.718、0.724、0.757、0.924。结论内部强化类型、表观弥散系数、T_(1)值及R_(1)值在内的多模态磁共振指标均可用于BI-RADS 4类乳腺肿瘤良恶性的鉴别诊断,基于上述指标构建的鉴别诊断模型Objective To explore the value of the prediction model based on multimodal MRI characteristics for the differential diagnosis of benign and malignant breast tumors of breast imaging reporting and date system(BI-RADS)4 types.Methods A total of 204 patients with BI-RADS 4 types of breast tumors confirmed by contrast-enhanced MRI in 3201 Hospital from January 2018 to January 2023 were retrospectively included,and were divided into the malignant group(124 cases)and the benign group(80 cases)according to surgical histopathology.Clinical and MRI imaging characteristics of the two groups were compared.Multivariate logistic regression analysis was performed for the differential diagnosis indexes of benign and malignant breast tumors of BI-RADS 4 types.A prediction model for differential diagnosis of benign and malignant BI-RADS 4 types of breast tumors was constructed.Receiver operator characteristic(ROC)curve was used to compare the differential diagnostic value of each index for benign and malignant BI-RADS 4 types of breast tumors.Results There were statistically significant differences in age(t=7.78,P<0.001),internal enhancement type(χ^(2)=14.50,P=0.002),apparent diffusion coefficient(t=-6.77,P<0.001)longitudinal relaxation time(T_(1))value(t=-6.15,P<0.001),and longitudinal relaxation rate(R_(1))value(t=7.02,P<0.001)between the malignant and benign groups.Multivariate analysis showed that age(OR=1.16,95%CI:1.07-1.25,P<0.001),internal reinforcement type(uneven:OR=8.08,95%CI:2.21-29.51,P=0.002),apparent diffusion coefficient(OR=0.01,95%CI:0.00-0.05,P<0.001),T_(1) value(OR=0.99,95%CI:0.99-1.00,P<0.001),and R_(1) value(OR=1043.50,95%CI:46.48-23426.36,P<0.001)were all independent factors influencing the differential diagnosis of benign and malignant BI-RADS 4 types of breast tumors.According to the results of multivariate analysis,a logistic regression model for differential diagnosis of benign and malignant BI-RADS 4 types of breast tumors was constructed.logit(P)=0.05+0.15×age+2.09×internal enhancement type-5.21×app

关 键 词：乳腺肿瘤 磁共振成像 乳腺影像报告和数据系统 诊断 鉴别 

分 类 号：R73[医药卫生—肿瘤]