Ma Chi, Yu Lifeng, Chen Baiyu, Koo Chi Wan, Takahashi Edwin A, Fletcher Joel G, Levin David L, Kuzo Ronald S, Viers Lyndsay D, Vincent-Sheldon Stephanie A, Leng Shuai, McCollough Cynthia H
Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
J Med Imaging (Bellingham). 2017 Jan;4(1):013510. doi: 10.1117/1.JMI.4.1.013510. Epub 2017 Mar 31.
Task-based assessment of computed tomography (CT) image quality requires a large number of cases with ground truth. Prospective case acquisition can be time-consuming. Inserting lesions into existing cases to simulate positive cases is a promising alternative. The aim was to evaluate a recently developed projection-based lesion insertion technique in thoracic CT. In total, 32 lung nodules of various attenuations were segmented from 21 patient cases, forward projected, inserted into projections, and reconstructed. Two experienced radiologists and two residents independently evaluated these nodules in two substudies. First, the 32 inserted and the 32 original nodules were presented in a randomized order and each received a score from 1 to 10 (1 = absolutely artificial to 10 = absolutely realistic). Second, the inserted and the corresponding original lesions were presented side-by-side to each reader. For the randomized evaluation, discrimination of real versus inserted nodules was poor with areas under the receiver operative characteristic curves being 0.57 [95% confidence interval (CI): 0.46 to 0.68], 0.69 (95% CI: 0.58 to 0.78), and 0.62 (95% CI: 0.54 to 0.69) for the two residents, two radiologists, and all four readers, respectively. Our projection-based lung nodule insertion technique provides a robust method to artificially generate positive cases that prove to be difficult to differentiate from real cases.
基于任务的计算机断层扫描（CT）图像质量评估需要大量具有真实情况的病例。前瞻性病例采集可能很耗时。将病变插入现有病例以模拟阳性病例是一种很有前景的替代方法。目的是评估一种最近开发的基于投影的病变插入技术在胸部CT中的应用。总共从21例患者病例中分割出32个不同衰减的肺结节，进行正向投影，插入到投影中并重建。两名经验丰富的放射科医生和两名住院医生在两项子研究中独立评估这些结节。首先，32个插入的结节和32个原始结节以随机顺序呈现，每个结节都获得1到10分的评分（1分 = 绝对不自然至10分 = 绝对逼真）。其次，将插入的病变和相应的原始病变并排呈现给每位读者。对于随机评估，两名住院医生、两名放射科医生以及所有四名读者区分真实结节与插入结节的能力较差，受试者操作特征曲线下面积分别为0.57 [95%置信区间（CI）：0.46至0.68]、0.69（95%CI：0.58至0.78）和0.62（95%CI：0.54至0.69）。我们基于投影的肺结节插入技术提供了一种可靠的方法来人工生成阳性病例，事实证明这些病例很难与真实病例区分开来。
