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Quantifying breast density with a cone-beam breast CT

机译:使用锥形束胸部CT量化胸部密度

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Volumetric breast density was evaluated using a simulated cone beam breast CT with 80 kVp. The breast was modeled as a cylinder with background tissue composition of 20% glandular and 80% adipose. Various objects with different sizes and tissue compositions were embedded. Ray-tracing algorithm was utilized to obtain projection images in a full rotation without considering scatter, beam hardening and imaging noise. Filtered backprojection was adopted for image reconstruction with high quality. Reconstructed images had flat profiles except at large cone angle of 8.6° to 10°. They were calibrated using known linear attenuation coefficients of two image contrast objects. A 3D mapping of tissue densities could be directly computed within 5% error. Tissue volumes were obtained by counting voxels in appropriate attenuation coefficient ranges. Results of contrast objects were consistent with true volumes within 10% error. However, cone angle artifact decreased pixel values, and a reduction algorithm was required for accurate tissue assessment at large cone angles. This study indicates the possibility of excellent quantitative breast density measurements and volume assessments with cone-beam breast CT.
机译:使用80 kVp的模拟锥束乳腺CT评估乳房的体积密度。将乳房建模为圆柱体,其背景组织成分为20%的腺体和80%的脂肪。嵌入了具有不同大小和组织组成的各种对象。光线跟踪算法用于获得完整旋转的投影图像,而无需考虑散射,光束硬化和成像噪声。采用滤波反投影进行高质量图像重建。重建的图像具有平坦的轮廓,除了在8.6°到10°的大锥角处。使用两个图像对比对象的已知线性衰减系数对它们进行了校准。组织密度的3D映射可以直接在5%的误差范围内进行计算。通过在适当的衰减系数范围内对体素进行计数来获得组织体积。对比对象的结果与误差在10%以内的真实体积一致。但是,锥角伪像会减少像素值,因此需要使用缩小算法来对大锥角进行准确的组织评估。这项研究表明使用锥形束乳腺CT进行出色的定量乳腺密度测量和体积评估的可能性。

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