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使用双能乳腺摄影术对乳腺微钙化进行分类。

Classification of breast microcalcifications using dual-energy mammography.

作者信息

Ghammraoui Bahaa, Makeev Andrey, Zidan Ahmed, Alayoubi Alaadin, Glick Stephen J

机构信息

U.S. Food and Drug Administration, CDRH, Division of Imaging Diagnostics and Software Reliability, Silver Spring, Maryland, United States.

CDER, Division of Product Quality Research, Office of testing and Research, Silver Spring, Maryland, United States.

出版信息

J Med Imaging (Bellingham). 2019 Jan;6(1):013502. doi: 10.1117/1.JMI.6.1.013502. Epub 2019 Mar 12.

Abstract

The potential of dual-energy mammography for microcalcification classification was investigated with simulation and phantom studies. Classification of type I/II calcifications was performed using the tissue attenuation ratio as a performance metric. The simulation and phantom studies were carried out using breast phantoms of 50% fibroglandular and 50% adipose tissue composition and thicknessess ranging from 3 to 6 cm. The phantoms included models of microcalcifications ranging in size between 200 and . The simulation study was carried out with fixed MGD of 1.5 mGy using various low- and high-kVp spectra, aluminum filtration thicknesses, and exposure distribution ratios to predict an optimized imaging protocol for the phantom study. Attenuation ratio values were calculated for microcalcification signals of different types at two different voltage settings. ROC analysis showed that classification performance as indicated by the area under the ROC curve was always greater than 0.95 for 1.5 mGy deposited mean glandular dose. This study provides encouraging first results in classifying malignant and benign microcalcifications based solely on dual-energy mammography images.

摘要

通过模拟和体模研究,对双能乳腺摄影术在微钙化分类方面的潜力进行了研究。使用组织衰减率作为性能指标对I/II型钙化进行分类。模拟和体模研究使用的乳腺体模由50%的纤维腺体组织和50%的脂肪组织组成,厚度在3至6厘米之间。体模中包含尺寸在200至[此处原文缺失具体数值]之间的微钙化模型。模拟研究在固定平均腺体剂量(MGD)为1.5毫戈瑞的情况下进行,采用各种低千伏和高千伏光谱、铝过滤厚度以及曝光分布比,以预测体模研究的优化成像方案。在两种不同电压设置下,计算了不同类型微钙化信号的衰减率值。ROC分析表明,对于沉积平均腺体剂量为1.5毫戈瑞的情况,ROC曲线下面积所表明的分类性能始终大于0.95。这项研究为仅基于双能乳腺摄影图像对恶性和良性微钙化进行分类提供了令人鼓舞的初步结果。

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本文引用的文献

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Screening for breast cancer in 2018-what should we be doing today?
Curr Oncol. 2018 Jun;25(Suppl 1):S115-S124. doi: 10.3747/co.25.3770. Epub 2018 Jun 13.
2
Characterization of breast calcification types using dual energy x-ray method.
Phys Med Biol. 2017 Sep 15;62(19):7741-7764. doi: 10.1088/1361-6560/aa8445.
5
Non-invasive classification of breast microcalcifications using x-ray coherent scatter computed tomography.
Phys Med Biol. 2017 Feb 7;62(3):1192-1207. doi: 10.1088/1361-6560/aa5187.
7
Breast microcalcifications: the lesions in anatomical pathology.
Diagn Interv Imaging. 2014 Feb;95(2):141-52. doi: 10.1016/j.diii.2013.12.011. Epub 2014 Feb 10.
8
Comparison of the x-ray attenuation properties of breast calcifications, aluminium, hydroxyapatite and calcium oxalate.
Phys Med Biol. 2013 Apr 7;58(7):N103-13. doi: 10.1088/0031-9155/58/7/N103. Epub 2013 Mar 8.
9
Size-adapted microcalcification segmentation in mammography utilizing scale-space signatures.
Comput Med Imaging Graph. 2010 Sep;34(6):487-93. doi: 10.1016/j.compmedimag.2009.12.009. Epub 2010 Jan 18.
10
Dual-energy digital mammography for calcification imaging: noise reduction techniques.
Phys Med Biol. 2008 Oct 7;53(19):5421-43. doi: 10.1088/0031-9155/53/19/010. Epub 2008 Sep 2.

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