基于简化多模态MRI构建乳腺癌诊断影像组学模型的研究  

Abbreviated multimodal MRI based radiomics models for breast cancer diagnosis

作　　者：赵家琪 武靖[1] 刘雨璐 彭媛[2] 胡雪歌 王殊[2] 王屹[1] Zhao Jiaqi;Wu Jing;Liu Yulu;Peng Yuan;Hu Xuege;Wang Shu;Wang Yi(Department of Radiology,Peking University People's Hospital,Beijing 100044,China;Department of Breast Surgery,Peking University People's Hospital,Beijing 100044,China)

机构地区：[1]北京大学人民医院放射科,北京100044 [2]北京大学人民医院乳腺外科,北京100044

出　　处：《中华普通外科杂志》2022年第11期834-838,共5页Chinese Journal of General Surgery

摘　　要：目的基于简化多模态磁共振影像(MRI)构建影像组学模型诊断乳腺癌。方法回顾性分析2014年6月至2019年3月所有具有穿刺或手术切除病理结果的1 306例乳腺疾病患者(良性病变416例,乳腺癌890例)的乳腺MRI图像,分为训练集(n=702)、内部验证集(n=302)、外部验证集(n=302)。所有图像简化为:联合模型组[T2加权脂肪抑制序列(T2WI)、扩散加权成像序列(DWI)和增强第一期图像]、非增强组(T2WI和DWI)及单期增强组(增强第一期图像)。提取影像特征并用方差分析和拉索回归法筛选有效特征;采用3种分类器(Bagging决策树、高斯过程、支持向量机)预测乳腺癌;选择最佳者构建乳腺癌诊断模型;最后通过内部和外部验证集验证。结果应用高斯过程分类器,联合模型和非增强模型预测乳腺癌AUC值,训练集为0.903和0.893、内部验证集为0.893和0.863、外部验证集为0.878和0.864。结论应用简化多模态MRI构建的影像组学模型能够准确诊断乳腺癌,而且非增强模型无需造影剂也可准确诊断乳腺癌,为简化诊断流程提供了可行性。Objective To create radiomics models based on abbreviated multimodal magnetic resonance imaging(MRI)for the diagnosis of breast cancer.Methods All breast MR imaging data between Jun 2014 and Mar 2019 were retrospectively collected.Patients with pathological results of puncture or surgical resection were involved in this study.One thousand three hundred and six patients(416 benign and 890 breast cancer)were divided into training cohort(n=702),internal validation cohort(n=302),and external validation cohort(n=302).All images were reduced to:the joint model group[including T2 weighted imaging(T2WI),DWI(diffusion-weighted imaging)and first contrast-enhanced sequences],non-enhanced group(T2WI and DWI)and single-phase enhanced group(first contrast-enhanced sequences).Analysis of variance(ANOVA)and least absolute shrinkage and selection operator(LASSO)were used to reduce the dimension of texture features.Three supervised machine learning algorithms(Bagging decision tree,Gaussian process,support vector machine)were used to predict benign and malignant breast lesions,and the best classifier was selected to construct breast cancer diagnosis model.Models were validated by internal and external validation cohorts.Results The Gaussian process algorithm was chosen.The area under the curve(AUC)of the joint model and the non-enhanced model for predicting breast cancer were 0.903 and 0.893 for the training cohort,0.893 and 0.863 for the internal validation cohort,and 0.878 and 0.864 for the external validation cohort.Conclusions The radiomics model based on abbreviated multimodal MRI can accurately diagnose breast cancer.And the non-enhanced model can accurately diagnose breast cancer without contrast enhancement,which provides feasibility for simplifying the diagnosis process.

关 键 词：乳腺肿瘤 磁共振成像 诊断 影像组学 

分 类 号：R445.2[医药卫生—影像医学与核医学] R737.9[医药卫生—诊断学]