摘要
目的 基于动态增强磁共振(DCE-MRI)序列及扩散加权成像(DWI)序列构建影像组学模型,探讨其对直径≤2 cm的乳腺肿块良恶性的鉴别价值.方法 选取2019 年1 月至2022 年8 月就诊于本院122 例患者,均接受MRI检查,且经测量肿块直径≤2 cm.将所有患者图像以DICOM格式上传至慧影大数据平台,使用双盲法在DWI及DCE第三期图像上逐层勾画感兴趣区(ROI),后将该病灶勾画的所有ROI融合成三维容积感兴趣区(3D-VOI)进行组学分析.按照4∶ 1 将数据集随机分为训练集与测试集,采用逻辑回归(LR)分类器,构建DCE、DWI及DCE与DWI联合鉴别模型,以病理检查为金标准,评价三种影像组学模型的鉴别效能,并比较三种模型的曲线下面积(AUC)、准确率、特异度及敏感度.结果 根据病理结果将122 例患者分为良性42 例,恶性80 例,以DCE构建组学模型鉴别乳腺小肿块的AUC值为0.83(0.65～1.00)、准确率67%、特异度81%、敏感度67%;以DWI构建组学模型鉴别乳腺小肿块的AUC值0.81(0.67～0.98)、准确率64%,特异度78%、敏感度75%;以DCE与DWI联合模型鉴别乳腺小肿块AUC值0.93(0.80～1.00)、准确率80%、特异度88%、敏感度89%.结论 DCE-MRI与DWI序列联合所建立的模型无创性鉴别乳腺小肿块良恶性的价值更高.
Abstract
Objective Based on dynamic contrast enhancement-magnetic resonance imaging(DCE-MRI)sequence and diffusion weighted imaging(DWI),DWI sequence to construct a radiomics model to explore its value in the differential di-agnosis of benign and malignant breast masses less than 2 cm in diameter.Methods A total of 122 patients admitted to our hospital from January 2019 to August 2022 were selected.All patients underwent MRI examination,and the diameter of the tumor was less than 2 cm.The images of all patients were uploaded to Huiyin big data platform with digital imaging and communications in medicine(DICOM),and the region of interest(ROI)was delineated on DWI and DCE phase 3 images layer by layer using the double-blind method,and then all rois delineated by the lesion were fused into Three dimensional volume region of interest(3D-VOI)for omics analysis.The dataset was randomly divided into training set and test set ac-cording to 4∶ 1.Logistic regression(LR)classifier was used to construct DCE,DWI and DCE-DWI combined discrimination models.The area under the curve(AUC),accuracy,specificity and sensitivity of the three models were compared.Re-sults According to the pathological results,the 122 patients were divided into benign group(n =42)and malignant group(n =80).The AUC value of the radiomics model constructed by DCE was 0.83(0.65-1.00),the accuracy was 67% ,the specificity was81% ,and the sensitivity was 67% .The AUC,accuracy,specificity and sensitivity of the radiomics model constructed by DWI in identifying small breast masses were 0.81(0.67-0.98),64% ,78% and 75% ,respectively.The AUC value of the combined model of DCE and DWI was0.93(0.80-1.00),the accuracy was 80% ,the specificity was 88% ,and the sensitivity was 89% .Conclusion The combination of DCE-MRI and DWI has a higher value in noninva-sive differential diagnosis of small breast masses.
基金项目
安徽省卫健委科研项目(AHWJ2021b147)
蚌埠医学院自然科学重点项目(2020byzd126)
NETL
NSTL
万方数据