- 期刊
利用標準乳房假體評估乳腺密度與影像灰階之關聯性
Evaluating Glandularity of Breast Phantom Using Gray-scale
摘要
乳癌是女性惡性腫瘤發生率的第一名，乳癌風險會隨著乳腺密度的上升而增加，並造成影像判讀難度增加，臨床上使用乳房影像報告分類系統（Breast imaging-reporting and data system, BI-RADS）作為乳腺密度的分級工具，然而，準確的量化乳腺密度是一重要的課題。本研究利用4、5、6公分厚度的標準乳房假體進行照射，射束參數分別為28、30與31 kVp，30、55與80 mAs，圈選影像中不同乳腺密度的灰階值，以線性迴歸建立乳腺密度與影像灰階之關聯性，並在自動曝露（automatic exposure control, AEC）照射條件下，以假體與臨床影像進行驗證。所求得的線性迴歸方程式為y = 19629.7 + 1278.2 × Thickness (cm) + 1746.8 × Density - 61.821 × mAs - 495.497 × kVp，以迴歸方程式與乳房假體進行驗證，21.7%乳腺密度在厚度為4.5、5.0公分，百分誤差為7.4%與12.1%，50.0%乳腺密度在厚度為6.5、7.0公分時的百分誤差為4.1%與4.7%，平均百分誤差為7.9%，本研究所提出的方法能有效的量化乳腺密度，並提升乳癌篩檢之價值。
並列摘要
Breast cancer is predominant of malignant tumors in females. Increase in the glandular density increases the risk of breast cancer. BI-RADS is a frequently used density indicator in mammography; however, it significantly overestimates the glandularity. Therefore, it is very important to accurately and quantitatively assess the glandularity by mammography. In this study, the phantoms with different thicknesses were exposed using a mammography machine at 28, 30, and 31 kVp, and 30, 55, and 80 mAs, respectively. The regions of interest (ROIs) were drawn to assess the gray level. The relationships between the glandularity and gray level under various compression thicknesses, kVp, and mAs were established by the multivariable linear regression. A phantom verification was performed with automatic exposure control (AEC). The regression equation was obtained as y = 19629.7 + 1278.2 × Thickness (cm) + 1746.8 × Density - 61.821 × mAs - 495.497 × kVp. The percent differences of glandularity to the regression equation were 7.4% (4.5 cm) and 12.1% (5.0 cm) for 21.7% glandularity and 4.1% (6.5 cm) and 4.7% (7.0 cm) for 50.0% glandularity. The average percent differences were 7.9%. We concluded that the proposed method could be clinically applied in mammography to improve the glandularity estimation and further increase the importance of breast cancer screening.
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