ADC全容积直方图在乳腺良恶性肿瘤鉴别中的应用
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四川省成都市卫健委医学科研项目(2022573);


Application of whole-lesion histogram analysis of apparent diffusion coeffi-cient in differentiation benign and malignant breast lesions
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    摘要:

    目的:探讨表观扩散系数(ADC)直方图在乳腺良恶性肿瘤鉴别中的应用。方法:选取58例经病理证实的乳腺肿块型病变患者为研究对象,按照病变良恶性分为良性病变组(n=26)和恶性病变组(n=32)。术前进行扩散加权成像(DWI)并后处理得到ADC图,在直方图分析软件上计算病变区ADC的直方图,比较乳腺良恶性病变ADC直方图参数的差异,受试者工作特征(ROC)曲线评价ADC直方图参数对乳腺良恶性病变的鉴别诊断价值。结果:恶性病变组患者ADC的平均值、最小值及25%、50%、75%百分位数及偏度值低于良性病变组,差异有统计学意义(P<0.05);两组患者90%百分位数、最大值及峰度值比较,差异无统计学意义(P>0.05)。结论:ADC直方图参数能帮助区分乳腺良恶性肿块型病变,其中25%的百分位数的鉴别诊断价值最高。

    Abstract:

    Objective:To explore the application of histogram of apparent diffusion coefficient (ADC) in differentiation benign and malignant breast lesions.Methods:A total of 58 patients with breast mass lesions confirmed by pathology were enrolled.They were divided into a benign lesion group(n=26)and a malignant lesion group(n=32)according to the benign and malignant nature of the lesions.DWI imaging was performed before operation and ADC map were generated.The ADC histogram analysis were computed on the histogram analysis software,and the differences of ADC histogram parameters of benign and malignant breast lesions were compared,and the receiver operating characteristic(ROC)curve was used to evaluate the differential diagnostic efficacy.Results:The mean,mini-mum,25%,50%,75% percentile of ADC value and skewness values of malignant tumors were lower than benign tumors(P<0.05),while there was no statistical difference between the 90% percentile,maximum and kurtosis values of ADC values between benign and malignant tumors(P>0.05).Conclusion:Histogram analysis of ADC can help distinguish between benign and malignant breast le-sions,with 25% percentiles having the highest differential diagnosis value.

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周立绥;赵吕志;贾莉;吴玲;. ADC全容积直方图在乳腺良恶性肿瘤鉴别中的应用[J].川北医学院学报,2025,40(7):914-917.

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  • 在线发布日期: 2025-08-10
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