Suryanarayanan Sankararaman, Karellas Andrew, Vedantham Srinivasan, Waldrop Sandra M, D'Orsi Carl J
1 Department of Radiology, Emory University School of Medicine, Winship Cancer Institute, 1701 Uppergate Dr, Bldg C, Suite 5018, Atlanta, GA 30322, USA.
Radiology. 2005 Jul;236(1):31-6. doi: 10.1148/radiol.2361040741. Epub 2005 Jun 27.
To evaluate retrospectively the effect of a wavelet-based compression method on the detection of simulated masses of various sizes and clustered microcalcifications on data-compressed digital mammograms.
The images used in this study were acquired with institutional review board approval and patient informed consent, both of which allowed subsequent image data analysis. Patient identification was removed from images, and the study complied with requirements of the Health Insurance Portability and Accountability Act. Masses 3, 6, and 8 mm in diameter were analytically simulated and added to clinical mammographic backgrounds. In addition, microcalcifications were extracted from a clinical mammogram and hybridized with simulated microcalcifications for use in this study. Image compression conditions of 1:1, 15:1, and 30:1 were investigated. Observer responses were recorded with a six-point rating scale, and receiver operating characteristic (ROC) analysis was performed. In addition, two well-established numeric observer models were used to study the effect of image compression under the same compression conditions as were used with human observers. Analysis of variance was performed after observer adjustment to compare the mean values for area under the ROC curve (A(z)) across the three compression levels for the masses and microcalcification clusters.
The results of the study indicated no significant differences in the A(z) values for masses with the compression conditions investigated. For images of microcalcifications, there were significant differences in A(z) values between compression ratios of 1:1 and 30:1 (P = .0005) and of 15:1 and 30:1 (P = .004); the difference between compression ratios of 1:1 and 15:1 was nonsignificant (P = .053). The observer models and human observers exhibited similar trends in detection of the masses investigated in this study.
Detection of simulated masses was not affected by the compression method with the conditions used in this study, while the detection of microcalcifications was significantly reduced with a compression ratio of more than 15:1.
回顾性评估基于小波的压缩方法对检测数据压缩后的数字乳腺钼靶片中不同大小的模拟肿块及簇状微钙化的影响。
本研究中使用的图像在获得机构审查委员会批准和患者知情同意后采集，二者均允许后续的图像数据分析。图像中去除了患者标识，且该研究符合《健康保险流通与责任法案》的要求。对直径为3毫米、6毫米和8毫米的肿块进行分析模拟，并添加到临床乳腺钼靶背景中。此外，从一张临床乳腺钼靶片中提取微钙化，并与模拟微钙化混合用于本研究。研究了1:1、15:1和30:1的图像压缩条件。观察者的反应采用六点评分量表记录，并进行了受试者操作特征（ROC）分析。此外，使用两个成熟的数字观察者模型，在与人类观察者相同的压缩条件下研究图像压缩的影响。在观察者调整后进行方差分析，以比较肿块和微钙化簇在三个压缩水平下的ROC曲线下面积（A(z)）的平均值。
研究结果表明，在所研究的压缩条件下，肿块的A(z)值没有显著差异。对于微钙化图像，1:1与30:1的压缩比之间（P = .0005）以及15:1与30:1的压缩比之间（P = .004）的A(z)值存在显著差异；1:1与15:1的压缩比之间的差异不显著（P = .053）。观察者模型和人类观察者在本研究中所研究的肿块检测方面表现出相似的趋势。
在本研究使用的条件下，模拟肿块的检测不受压缩方法的影响，而压缩比超过15:1时，微钙化的检测显著降低。
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