Zhang Wei, Jin Guan-Qiao, Liu Jun-Jie, Su Dan-Ke, Luo Ning-Bin, Xie Dong, Lai Shao-Lv, Huang Xiang-Yang, Huang Wei-Li
Department of Radiology, Affiliated Tumor Hospital of Guangxi Medical University 71 Hedi Road, Nanning 530021, Guangxi Zhuang Autonomous Region, China.
Department of Ultrasound Diagnosis, Affiliated Tumor Hospital of Guangxi Medical University 71 Hedi Road, Nanning 530021, Guangxi Zhuang Autonomous Region, China.
Int J Clin Exp Med. 2015 Aug 15;8(8):12096-104. eCollection 2015.
The purpose of this study was to explore the diagnostic performance of apparent diffusion coefficient (ADC) values for breast lesions by different measuring methods and find out the optimum measuring method.
ADCW-mean and ADCW-min were obtained by whole-measurement method, while ADCmean and ADCmin were extracted by spot-measurement method. Four ADCs were analyzed by One-way ANOVA and Independent T-test. The diagnostic performances of these four ADCs were calculated by receiver operating characteristics (ROC) curves and the area under the curves (AUC) were compared through Z-test.
For the whole-measurement method, there were significant differences between malignant and benign lesions (ADCW-mean=1.014±0.197 for malignant, ADCW-mean=1.650±0.348 for benign, F=37.511, P<0.001; ADCW-min=0.627±0.144 for malignant, ADCW-min=1.245±0.290 for benign, F=41.446, P<0.001), as well as the spot-measurement method (ADCmean=1.010±0.234 for malignant, ADCmean=1.648±0.392 for benign, F=34.580, P<0.001; ADCmin=0.817±0.203 for malignant, ADCmin=1.411±0.357 for benign, F=40.039, P<0.001). The optimal diagnostic threshold of ADCW-mean, ADCW-min, ADCmean, and ADCmin values were 1.223×10(-3) mm(2)/s, 0.897×10(-3) mm(2)/s, 1.315×10(-3) mm(2)/s, and 1.111×10(-3) mm(2)/s, respectively. ROC curves indicated that the AUC for ADCW-min (0.969) was statistically significant higher than the AUC for ADCW-mean (0.940; Z=2.473, p=0.013), ADCmean (0.919; Z=3.691, P=0.000), and ADCmin (0.928; Z=3.634, P=0.000). The AUC for ADCW-mean was also significantly higher than the AUC for ADCmean (Z=2.863, P=0.004).
The results provided evidence that the most reliable and accurate value in demonstrating the limitation of diffusion may be ADCW-min, and it has the highest diagnostic value in distinguishing breast lesions from malignant to benign.
本研究旨在探讨不同测量方法下表观扩散系数(ADC)值对乳腺病变的诊断性能,并找出最佳测量方法。
通过全测量法获得ADCW-均值和ADCW-最小值,而通过点测量法提取ADC均值和ADC最小值。采用单因素方差分析和独立样本t检验对四个ADC值进行分析。通过绘制受试者工作特征(ROC)曲线计算这四个ADC值的诊断性能,并通过Z检验比较曲线下面积(AUC)。
对于全测量法,恶性和良性病变之间存在显著差异(恶性病变的ADCW-均值=1.014±0.197,良性病变的ADCW-均值=1.650±0.348,F=37.511,P<0.001;恶性病变的ADCW-最小值=0.627±0.144,良性病变的ADCW-最小值=1.245±0.290,F=41.446,P<0.001),点测量法亦是如此(恶性病变的ADC均值=1.010±0.234,良性病变的ADC均值=1.648±0.392,F=34.580,P<0.001;恶性病变的ADC最小值=0.817±0.203,良性病变的ADC最小值=1.411±0.357,F=40.039,P<0.001)。ADCW-均值、ADCW-最小值、ADC均值和ADC最小值的最佳诊断阈值分别为1.223×10(-3) mm(2)/s、0.897×10(-3) mm(2)/s、1.315×10(-3) mm(2)/s和1.111×10(-3) mm(2)/s。ROC曲线表明,ADCW-最小值的AUC(0.969)在统计学上显著高于ADCW-均值的AUC(0.940;Z=2.473,p=0.013)、ADC均值的AUC(0.919;Z=3.691,P=0.000)以及ADC最小值的AUC(0.928;Z=3.634,P=0.000)。ADCW-均值的AUC也显著高于ADC均值的AUC(Z=2.863,P=0.004)。
结果表明,在显示扩散受限方面最可靠、准确的值可能是ADCW-最小值,它在区分乳腺恶性与良性病变方面具有最高的诊断价值。