Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905, USA.
Med Phys. 2013 Apr;40(4):041908. doi: 10.1118/1.4794498.
Efficient optimization of CT protocols demands a quantitative approach to predicting human observer performance on specific tasks at various scan and reconstruction settings. The goal of this work was to investigate how well a channelized Hotelling observer (CHO) can predict human observer performance on 2-alternative forced choice (2AFC) lesion-detection tasks at various dose levels and two different reconstruction algorithms: a filtered-backprojection (FBP) and an iterative reconstruction (IR) method.
A 35 × 26 cm(2) torso-shaped phantom filled with water was used to simulate an average-sized patient. Three rods with different diameters (small: 3 mm; medium: 5 mm; large: 9 mm) were placed in the center region of the phantom to simulate small, medium, and large lesions. The contrast relative to background was -15 HU at 120 kV. The phantom was scanned 100 times using automatic exposure control each at 60, 120, 240, 360, and 480 quality reference mAs on a 128-slice scanner. After removing the three rods, the water phantom was again scanned 100 times to provide signal-absent background images at the exact same locations. By extracting regions of interest around the three rods and on the signal-absent images, the authors generated 21 2AFC studies. Each 2AFC study had 100 trials, with each trial consisting of a signal-present image and a signal-absent image side-by-side in randomized order. In total, 2100 trials were presented to both the model and human observers. Four medical physicists acted as human observers. For the model observer, the authors used a CHO with Gabor channels, which involves six channel passbands, five orientations, and two phases, leading to a total of 60 channels. The performance predicted by the CHO was compared with that obtained by four medical physicists at each 2AFC study.
The human and model observers were highly correlated at each dose level for each lesion size for both FBP and IR. The Pearson's product-moment correlation coefficients were 0.986 [95% confidence interval (CI): 0.958-0.996] for FBP and 0.985 (95% CI: 0.863-0.998) for IR. Bland-Altman plots showed excellent agreement for all dose levels and lesions sizes with a mean absolute difference of 1.0% ± 1.1% for FBP and 2.1% ± 3.3% for IR.
Human observer performance on a 2AFC lesion detection task in CT with a uniform background can be accurately predicted by a CHO model observer at different radiation dose levels and for both FBP and IR methods.
高效优化 CT 协议需要一种定量方法来预测在特定扫描和重建设置下,特定任务中人类观察者的表现。本研究的目的是探讨通道化 Hotelling 观察者(CHO)在不同剂量水平和两种不同重建算法(滤波反投影(FBP)和迭代重建(IR)方法)下,对 2AFC 病变检测任务中人类观察者表现的预测能力。
使用一个填充有水的 35×26cm2 体模来模拟一个平均大小的患者。在体模的中心区域放置三个不同直径的棒(小:3mm;中:5mm;大:9mm)以模拟小、中、大病变。在 120kV 时,对比相对于背景的对比度为-15HU。使用自动曝光控制,在一台 128 层扫描仪上,每个体模扫描 100 次,每次扫描的质量参考 mAs 分别为 60、120、240、360 和 480。在移除三个棒后,将水模再次扫描 100 次,以在相同位置获得无信号的背景图像。通过提取三个棒周围和无信号图像上的感兴趣区域,作者生成了 21 个 2AFC 研究。每个 2AFC 研究有 100 次试验,每次试验由一个信号存在的图像和一个信号不存在的图像并排随机排列组成。总共向模型和人类观察者呈现了 2100 次试验。四名医学物理学家作为人类观察者进行观察。对于模型观察者,作者使用了带有 Gabor 通道的 CHO,其中涉及六个通道通带、五个方向和两个相位,总共 60 个通道。比较了 CHO 预测的性能与四名医学物理学家在每个 2AFC 研究中的表现。
对于 FBP 和 IR,在每个 2AFC 研究中,对于每个病变大小,人类和模型观察者在每个剂量水平下均高度相关。FBP 的 Pearson 乘积矩相关系数为 0.986(95%置信区间(CI):0.958-0.996),IR 为 0.985(95%CI:0.863-0.998)。Bland-Altman 图显示,在所有剂量水平和病变大小下,FBP 的平均绝对差异为 1.0%±1.1%,IR 为 2.1%±3.3%,均具有极好的一致性。
在具有均匀背景的 CT 中,使用通道化 Hotelling 观察者(CHO)模型可以准确预测人类观察者在不同辐射剂量水平和 FBP 与 IR 两种方法下进行的 2AFC 病变检测任务的表现。