Department of Radiology, Mayo Clinic, Rochester, MN, United States of America.
Phys Med Biol. 2019 May 10;64(10):105011. doi: 10.1088/1361-6560/ab1a45.
The purpose of this study was to determine the correlation between human observer performance for localization of small low contrast lesions within uniform water background versus an anatomical liver background, under the conditions of varying dose, lesion size, and reconstruction algorithm. Liver lesions (5 mm, 7 mm, and 9 mm, contrast: -21 HU) were digitally inserted into CT projection data of ten normal patients in vessel-free liver regions. Noise was inserted into the projection data to create three image sets: full dose and simulated half and quarter doses. Images were reconstructed with a standard filtered back projection (FBP) and an iterative reconstruction (IR) algorithm. Lesion and noise insertion procedures were repeated with water phantom data. Two-dimensional regions of interest (66 lesion-present, 34 lesion-absent) were selected, randomized, and independently reviewed by three medical physicists to identify the most likely location of the lesion and provide a confidence score. Locations and confidence scores were assessed using the area under the localization receiver operating characteristic curve (Az). We examined the correlation between human performance for the liver and uniform water backgrounds as dose, lesion size, and reconstruction algorithm varied. As lesion size or dose increased, reader localization performance improved. For full dose IR images, the Az for 5, 7, and 9 mm lesions were 0.53, 0.91, and 0.97 (liver) and 0.51, 0.96, and 0.99 (uniform water), respectively. Similar trends were seen with other parameters. Performance values for liver and uniform backgrounds were highly correlated for both reconstruction algorithms, with a Spearman correlation of ρ = 0.97, and an average difference in Az of 0.05 ± 0.04. For the task of localizing low contrast liver lesions, human observer performance was highly correlated between anatomical and uniform backgrounds, suggesting that lesion localization studies emulating a clinical test of liver lesion detection can be performed using a uniform background.
本研究旨在确定在不同剂量、病灶大小和重建算法条件下,人体观察者在均匀水背景和解剖肝背景下定位小低对比度病灶的能力之间的相关性。将(5mm、7mm 和 9mm,对比度:-21HU)的肝脏病变数字插入到无血管肝脏区域的 10 名正常患者的 CT 投影数据中。将噪声插入到投影数据中,以创建三个图像集:全剂量和模拟半剂量和四分之一剂量。使用标准滤波后投影(FBP)和迭代重建(IR)算法对图像进行重建。使用水模数据重复进行病变和噪声插入过程。选择、随机化二维感兴趣区域(66 个病变存在,34 个病变不存在),由三名医学物理学家独立进行审阅,以确定病变最有可能的位置,并提供置信度评分。使用定位接收者操作特征曲线(Az)的下面积评估位置和置信度评分。我们研究了在剂量、病灶大小和重建算法变化时,人体在肝脏和均匀水背景下的性能相关性。随着病灶大小或剂量的增加,读者的定位性能得到改善。对于全剂量 IR 图像,5mm、7mm 和 9mm 病灶的 Az 在肝脏为 0.53、0.91 和 0.97(肝脏)和 0.51、0.96 和 0.99(均匀水),分别。其他参数也出现了类似的趋势。对于两种重建算法,肝脏和均匀背景的性能值高度相关,Spearman 相关系数 ρ为 0.97,Az 的平均差异为 0.05±0.04。对于定位低对比度肝脏病变的任务,人体观察者在解剖和均匀背景之间的性能高度相关,这表明可以使用均匀背景来进行模拟肝脏病变检测的临床测试的病变定位研究。