图像后处理对全数字化乳腺影像病变检出率的影响

Effect of image post-processing in full-field digital mammography on detection accuracy of breast lesions

目的比较全数字化乳腺影像(FFDM)的两种图像后处理方式———动态对比度全智能优化(PV)与组织均衡技术(TE)对乳腺病变检出率的影响。方法选取符合纳入标准的患者的乳腺X线图像,按经PV和TE两种后处理方式的图像和原始图像(RAW)分为3组,由2名放射科医师阅片并记录评分结果。使用受试者工作特征(ROC)曲线进行统计学分析。结果 49例患者共62个病灶,均经病理证实。PV组、TE组及RAW组ROC曲线下面积(Az)分别为0.770±0.031、0.684±0.033、0.709±0.032。3组中PV组Az值及敏感度最高,RAW组假阴性率最高,TE组假阳性率最高。对于恶性病灶,PV组优于TE组及RAW组,TE组与RAW组间差异无统计学意义,3组间总体差异有统计学意义(P<0.05);对于良性病灶3组间差异无统计学意义。结论恰当的后处理能够增加FFDM对特定类型病变的显示能力;对检出恶性病灶,PV优于TE。

Objective To compare the effect of premium view （PV） and tissue equalization （TE） in full field digital mammography （FFDM） on brcast lesions detection accuracy. Methods Two radiologists read images in the post processing modes of PV, TE image and RAW which accorded inclusion criteria and then recorded the results. Sixty two lesions detected from 49 patients undergoing FFDM and confirmed by pathology were selected. All observations were evaluated by the receiver operating characteristic （ROC） curve analysis. Results The mean area under the ROC curve （Az） values of PV, TE and RAW groups was 0. 770±0. 031, 0. 684±0. 033 and 0. 709±0. 032, respectively. Among 3 groups, Az value and sensitivity of PV group was the highest. RAW group had the highest false negative rate, and the false positive rate of the TE group was highest. PV group made better diagnostic ability than TE and RAW group for malignant lesions. There was no significant difference between TE and RAW group. However, significant difference among all 3 groups was found （P〈2. 0.05）. Overall groups had no significant difference in benign lesions. Conclusion It can be improved that FFI）M display capability for particular type lesions after using appropriate image post-processing method. Compared with TE, PV pro vides better diagnostic ability on breast lesions in FFDM. PV is better for detection of malignant lesions than TE.