摘要
目的 探讨合成MRI(synthetic MRI, SyMRI)定量参数直方图特征鉴别乳腺良恶性病变的价值。材料与方法 回顾性收集2019年10月至2021年11月经病理证实的186例乳腺病变患者资料,术前均行常规MRI和SyMRI扫描。利用PyRadiomic软件提取SyMRI定量参数的直方图特征。采用独立样本t检验或Mann-Whitney U检验比较良恶性病变SyMRI定量参数的直方图特征差异,将单因素分析中差异具有统计学意义的参数纳入多因素logistic回归分析,用受试者工作特征(receiver operating characteristic curve, ROC)曲线评估参数的诊断效能。结果 共纳入150例患者的166个病灶(61个良性,105个恶性)。多因素分析结果显示T1-90th(P=0.002)、T1-熵(P=0.001)与质子密度-峰度(P=0.014)是鉴别乳腺良恶性病变的独立预测因素。logistic回归模型鉴别乳腺良恶性病变的AUC值为0.89(95%CI:0.84~0.94),敏感度为85.15%,特异度为81.97%。结论 SyMRI直方图特征可为鉴别乳腺病变治疗前精准诊断提供依据。
Objective:To explore the value of whole volume histogram features from synthetic MRI(SyMRI)in the diagnosis of benign and malignant breast tumors.Materials and Methods:Clinical and imaging data of 186 patients with breast lesions were retrospective collected from October 2019 to November 2021.All patients were confirmed by puncture biopsy and/or surgical pathology,and preoperative conventional MRI and SyMRI scans were performed.The independent samples t-test or Mann-Whitney U test was chosen to compare quantitative parameters between benign and malignant breast lesions.Multivariate logistic regression model was developed based on the univariate result,and the corresponding ROC curves were obtained with AUC,sensitivity and specificity.Results:A total of 150 patients with breast lesions(166 lesions in total)were enrolled.Multivariate analysis showed that T1-90th(P=0.002),T1-entropy(P=0.001)and proton density-kurtosis(P=0.014)were independent predictors for the differentiation of benign and malignant breast lesions.The AUC of differentiating benign and malignant breast lesions by multivariate logistic regression model was 0.89(95%CI:0.84-0.94),with the sensitivity of 85.15%and the specificity of 81.97%.Conclusions:The whole volume histogram parameters from SyMRI can provide a basis for accurate diagnosis of identifying benign and malignant breast lesions.
作者
孙胜君
李芹
李方正
吴莎莎
牛庆亮
SUN Shengjun;LI Qin;LI Fangzheng;WU Shasha;NIU Qingliang(School of Medical Imaging,Weifang Medical College,Weifang 261000,China;Center of Medicine Imaging,Weifang Traditional Chinese Medical Hospital,Weifang 261041,China)
出处
《磁共振成像》
CAS
CSCD
北大核心
2023年第8期58-62,164,共6页
Chinese Journal of Magnetic Resonance Imaging
基金
山东省自然科学基金(编号:ZR202103060229)。
关键词
乳腺肿瘤
良恶性鉴别
磁共振成像
合成磁共振成像
直方图
定量参数
breast neoplasms
distinguish between benign and malignant
magnetic resonance imaging
synthetic magnetic resonance imaging
histogram
quantitative
