Yang Kai-yan, Liu Xiao-juan, Zhai Ren-you
Department of Radiology, Capital University of Medical Sciences, Beijing, China.
Zhonghua Zhong Liu Za Zhi. 2012 May;34(5):360-3. doi: 10. 3760/cma.j.issn.0253-3766.2012.05.009.
To evaluate the impact of breast density on computer-aided detection (CAD) for breast cancer and the CAD false-positive rate of normal controls.
Two hundred and seventy-one histologically proven breast malignant lesions (from Feb. 2008 to Dec. 2009) and 238 randomly selected normal cases were classified by mammographic density according to the American College of Radiology breast imaging reporting and data system (BI-RADS). Mammograms of BI-RADS 1 or BI-RADS 2 density were categorized as non-dense breasts, and those of BI-RADS 3 or BI-RADS 4 density were categorized as dense breasts. Full-field digital mammography (GEMS Senographe) were performed in all patients and controls with craniocaudal (CC) and mediolateral oblique (MLO) views. Then the image data were transferred to review workstation (SenoAdvantage), and the lesions were marked by Second Look Digital CAD system (version 7.2, iCAD). The differences of sensitivity and false-positive rate between dense and non-dense breasts were compared.
Overall, the sensitivity of CAD in detection of cancers was 84.1% (228/271), there was a statistically significant difference in CAD of cancers in dense versus non-dense breasts (P = 0.015). The sensitivity of CAD in detection of mass cancers was 76.5% (186/243), in detection of calcification cancers was 79.1% (125/158), there was no statistically significant difference in CAD performance for the detection of mass cancers versus calcification cancers (P = 0.547). There was a significant difference in the CAD performance for the detection of mass cancer cases in non-dense versus dense breasts (P = 0.001), but no significant difference in the CAD for the detection of calcification cancers in non-dense versus dense breasts (P = 0.216). In the controls, the distribution of mass false-positive marks did not differ significantly between non-dense and dense breast tissue cases (P = 0.207), but the distribution of calcification false-positive marks differed significantly between non-dense and dense breast tissue cases (P = 0.001). There was a statistically significant difference of false-positive marks in non-dense versus dense breasts (P = 0.043).
The sensitivity of CAD in the detection of breast cancers is impacted by breast density. There is a statistically significant difference in the CAD performance for the detection of cancer cases in non-dense versus dense breasts. The false-positive rate of CAD is lower in dense versus non-dense breasts. It appears difficult for CAD in the early detection of breast cancer in the absence of microcalcifications, particularly in dense breasts.
评估乳腺密度对乳腺癌计算机辅助检测（CAD）的影响以及正常对照的CAD假阳性率。
根据美国放射学会乳腺影像报告和数据系统（BI-RADS），对271例经组织学证实的乳腺恶性病变（2008年2月至2009年12月）和238例随机选择的正常病例进行乳腺钼靶密度分类。BI-RADS 1或BI-RADS 2密度的乳腺钼靶片被归类为非致密型乳腺，而BI-RADS 3或BI-RADS 4密度的则被归类为致密型乳腺。所有患者和对照均进行全视野数字化乳腺钼靶摄影（GEMS Senographe），包括头尾位（CC）和内外斜位（MLO）视图。然后将图像数据传输至回顾工作站（SenoAdvantage），并使用Second Look Digital CAD系统（版本7.2，iCAD）标记病变。比较致密型和非致密型乳腺之间的敏感性和假阳性率差异。
总体而言，CAD检测癌症的敏感性为84.1%（228/271），致密型和非致密型乳腺中癌症的CAD存在统计学显著差异（P = 0.015）。CAD检测肿块型癌症的敏感性为76.5%（186/243），检测钙化型癌症的敏感性为79.1%（125/158），检测肿块型癌症和钙化型癌症的CAD性能无统计学显著差异（P = 0.547）。非致密型和致密型乳腺中检测肿块型癌症病例的CAD性能存在显著差异（P = 0.001），但非致密型和致密型乳腺中检测钙化型癌症的CAD无显著差异（P = 0.216）。在对照组中，非致密型和致密型乳腺组织病例之间的肿块假阳性标记分布无显著差异（P = 0.207），但钙化假阳性标记分布在非致密型和致密型乳腺组织病例之间存在显著差异（P = 0.001）。非致密型和致密型乳腺之间的假阳性标记存在统计学显著差异（P = 0.043）。
CAD检测乳腺癌的敏感性受乳腺密度影响。非致密型和致密型乳腺中检测癌症病例的CAD性能存在统计学显著差异。致密型乳腺与非致密型乳腺相比，CAD的假阳性率较低。在没有微钙化的情况下，CAD似乎难以早期检测乳腺癌，尤其是在致密型乳腺中。
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