The performance of three digital detectors was measured at two exposure index (EI) levels in terms of the effect on features at the borderline of detectability. The null hypothesis was that there would be no statistically significant difference in the CNR of marginally visible features of a baseline‐ (2.2 µGy) and reduced dose (1.4 µGy) images. The experiment used three digital detectors and a phantom composed of an aluminum contrast‐recovery plate, with features of varying diameters and hole depths, which was placed between the detector/grid and 5–20 cm Lucite. Exposures were made using a kVp between 55 and 110 corresponding to the Lucite thickness and a mAs producing an EI of approximately 220 or 140. Images were acquired for all detectors, EI values, and all Lucite thicknesses, then scored by a team of physicists and technologists in terms of feature visibility for each feature size. Contrast‐to‐noise ratio (CNR) was calculated for each feature using an ROI over the feature and a local background annulus. The uncertainty in the CNR was determined by sampling the background at each feature size, finding residuals from an overall background fit, and then calculating a standard deviation in the noise for each size. The marginal feature pair for each feature size bracketed the reader score. The difference between the CNR values of corresponding marginal features in EI‐paired images was significant (P < 0.05) for one detector and not significant (P > 0.05) for marginal features of the other two. Based on both reader scoring and CNR measurements of phantoms, patient doses can be lowered by 30% for those two detectors without a statistically significant difference in lesion perceptibility of the marginally visible feature, while for the other detector there was a statistically significant change in marginal feature detectability and dose reduction was not recommended.

中文翻译：

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基于边缘对比度可检测性重要性的数字放射线照相剂量减少

根据对可检测性边界特征的影响，在两个曝光指数 (EI) 水平下测量了三个数字探测器的性能。零假设是基线（2.2 µGy）和减少剂量（1.4 µGy）图像的边缘可见特征的 CNR 不存在统计学上的显着差异。该实验使用了三个数字探测器和一个由铝制对比恢复板组成的模型，具有不同的直径和孔深度，放置在探测器/网格和 5-20 厘米有机玻璃之间。使用对应于有机玻璃厚度的 55 至 110 kVp 和产生约 220 或 140 EI 的 mAs 进行曝光。采集所有探测器、EI 值和所有有机玻璃厚度的图像，然后由物理学家团队进行评分，技术人员在每个特征尺寸的特征可见性方面。使用特征上的 ROI 和局部背景环来计算每个特征的对比度与噪声比 (CNR)。CNR 的不确定性是通过对每个特征尺寸的背景进行采样、从整体背景拟合中找到残差，然后计算每个尺寸的噪声的标准偏差来确定的。每个特征大小的边缘特征对将读者得分括起来。对于一个检测器，EI 配对图像中相应边缘特征的 CNR 值之间的差异显着（P  < 0.05），而 对于其他两个检测器的边缘特征，差异不显着（ P > 0.05）。根据读者评分和体模的 CNR 测量，这两个探测器的患者剂量可以降低 30%，而边缘可见特征的病变感知度没有统计学上的显着差异，而对于另一个探测器，边缘可见特征的病变感知度存在统计学上的显着变化。不推荐特征可检测性和剂量减少。