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Value of Magnetic Resonance Imaging Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors

机译:磁共振成像纹理分析在乳腺良恶性肿瘤鉴别诊断中的价值

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摘要

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,Pc =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 the specific 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.
机译:目的探讨乳腺良恶性肿瘤在扩散加权成像(DWI)图像上的纹理特征差异。方法:在海南治疗的56例肿块样乳腺癌,16例乳腺纤维腺瘤,4例乳管内乳头状瘤患者。回顾性地纳入中国人民解放军总医院医院,根据术后病理结果将其分为良性组(20例)和恶性组(56例)。计算了角秒矩(ASM),对比度,相关性,逆差矩(IDM)和熵这5个特征参数,并进行了独立样本t检验和Mann-Whitney U检验进行组间比较,使用回归模型建立回归模型进行二进制Logistic回归分析和接收器工作特性曲线(ROC)分析以评估诊断结果乳腺良恶性组的纹理特征ASM,对比度,相关性和熵表现出显着差异(PASM = 0.014,Pc = 0.019,Pcorrelation = 0.010,Pentropy = 0.007).ROC曲线下的面积为0.685在Logistic回归模型中,上述正纹理变量的系数分别为0.681、0.754和0.683,组合变量(ASM,对比度和熵)的系数分别为0.802。二元Logistic回归分析表明,ASM,对比度和熵结论DWI的质地分析可能是一种简便,有效的乳腺良恶性肿瘤鉴别诊断工具。

著录项

  • 来源
    《中国医学科学杂志(英文版)》 |2019年第1期|33-37|共5页
  • 作者单位

    Department of Radiology,Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology,Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology,Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology,Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology,Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology,Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology,Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology, Chinese PLA General Hospital, Beijing 100853, China;

    Department of Oncology, Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology,Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan 572013, China;

    Department of Radiology, Chinese PLA General Hospital, Beijing 100853, China;

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  • 正文语种 eng
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  • 入库时间 2022-08-19 04:26:30
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