Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain
Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain
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DOI：
10.1118/1.4812430
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发表时间：
2013-08-01
期刊：
影响因子：
3.8
通讯作者：
McCollough, Cynthia H.
中科院分区：
文献类型：
--
作者：
Leng, Shuai;Yu, Lifeng;McCollough, Cynthia H.
目的：本研究的目的是探讨模型观察者和人类观察者的CT成像的病变检测和定位的任务时，病变locationisUncertaint.Methods：两个圆柱形杆（3毫米和5毫米直径）之间的相关性放置在一个35 × 26厘米躯干形水幻影模拟病变，-15 HU对比度在120 kV。在四个剂量水平（CTDIvol = 5.7、11.4、17.1和22.8 mGy）下，在128层CT扫描仪上对体模扫描100次。提取每个病变周围的感兴趣区域（ROI）以生成存在信号的图像，每个ROI包含128 x 128像素。无信号图像的相应ROI由无病变模拟杆的图像生成。通过在每个病变周围移动ROI，随机分布每个ROI中病变（杆）的位置。通过让三名经过训练的观察者识别病变的存在或不存在，指示每个图像中的病变位置并在6点量表上对检测任务的置信度进行评分来进行人类观察者研究。使用具有Gabor通道的通道化Hotelling模型观测器（CHO）分析相同的图像数据。将内部噪声添加到模型观测器研究的决策变量中。使用非参数方法计算ROC曲线下面积（AUC）和定位ROC（LROC）曲线。的斯皮尔曼的等级顺序之间的相关性的平均性能的人类观察员和模型观察员的性能计算的AUC的ROC曲线和LROC曲线为3-和5-mm直径insulines.Results：在两个ROC和LROC分析，AUC值的模型观察员同意以及在三个人类观察员的平均值。对于3 mm和5 mm直径病变的ROC和LROC分析，斯皮尔曼秩序相关值均为1.0，表明人类观察者的平均性能和模型观察者性能之间的优值（AUC）的秩序完全一致。在不同大小的低对比度病变（~ 15 HU）的CT成像中，对于CT中病变位置不确定的检测和定位任务，具有Gabor通道的CHO的性能与人类观察者的性能高度相关在四个临床相关剂量水平下进行成像。这表明Gabor CHO模型观察者能够有意义地评估CT图像质量，以优化低对比度病变检测和定位任务中的扫描方案和辐射剂量水平。(C)2013年美国医学物理学家协会。
Purpose: The purpose of this study was to investigate the correlation between model observer and human observer performance in CT imaging for the task of lesion detection and localization when the lesion location is uncertain.Methods: Two cylindrical rods (3-mm and 5-mm diameters) were placed in a 35 x 26 cm torso-shaped water phantom to simulate lesions with -15 HU contrast at 120 kV. The phantom was scanned 100 times on a 128-slice CT scanner at each of four dose levels (CTDIvol = 5.7, 11.4, 17.1, and 22.8 mGy). Regions of interest (ROIs) around each lesion were extracted to generate images with signal-present, with each ROI containing 128 x 128 pixels. Corresponding ROIs of signal-absent images were generated from images without lesion mimicking rods. The location of the lesion (rod) in each ROI was randomly distributed by moving the ROIs around each lesion. Human observer studies were performed by having three trained observers identify the presence or absence of lesions, indicating the lesion location in each image and scoring confidence for the detection task on a 6-point scale. The same image data were analyzed using a channelized Hotelling model observer (CHO) with Gabor channels. Internal noise was added to the decision variables for the model observer study. Area under the curve (AUC) of ROC and localization ROC (LROC) curves were calculated using a nonparametric approach. The Spearman's rank order correlation between the average performance of the human observers and the model observer performance was calculated for the AUC of both ROC and LROC curves for both the 3- and 5-mm diameter lesions.Results: In both ROC and LROC analyses, AUC values for the model observer agreed well with the average values across the three human observers. The Spearman's rank order correlation values for both ROC and LROC analyses for both the 3- and 5-mm diameter lesions were all 1.0, indicating perfect rank ordering agreement of the figures of merit (AUC) between the average performance of the human observers and the model observer performance.Conclusions: In CT imaging of different sizes of low-contrast lesions (-15 HU), the performance of CHO with Gabor channels was highly correlated with human observer performance for the detection and localization tasks with uncertain lesion location in CT imaging at four clinically relevant dose levels. This suggests the ability of Gabor CHO model observers to meaningfully assess CT image quality for the purpose of optimizing scan protocols and radiation dose levels in detection and localization tasks for low-contrast lesions. (C) 2013 American Association of Physicists in Medicine.