Medical Image Optimisation and Perception Group (MIOPeG), Medical Imaging & Radiation Sciences Faculty Research Group, Faculty of Health Sciences, The University of Sydney, Cumberland Campus, Lidcombe, NSW, 2141, Australia,
J Digit Imaging. 2013 Dec;26(6):1001-7. doi: 10.1007/s10278-013-9595-6.
This study aimed to determine if phantom-based methodologies for optimization of hepatic lesion detection with computed tomography (CT) require randomization of lesion placement and inclusion of normal images. A phantom containing fixed opacities of varying size (diameters, 2.4, 4.8, and 9.5 mm) was scanned at various exposure and slice thickness settings. Two image sets were compared: All images in the first image set contained opacities with known location; the second image set contained images with opacities in random locations. Following Institutional Review Board approval, nine experienced observers scored opacity visualization using a 4-point confidence scale. Comparisons between image sets were performed using Spearman, Kappa, and Wilcoxon techniques. Observer scores demonstrated strong correlation between both approaches when all opacity sizes were combined (r = 0.92, p < 0.0001), for the 9.5 mm opacity (r = 0.96, p < 0.0001) and for the 2.4 mm opacity (r = 0.64, p < 0.05). There was no significant correlation for the 4.8 mm opacity. A significantly higher sensitivity score for the known compared with the unknown location was found for the 9.5 mm opacity and 4.8 mm opacity for a single slice thickness and exposure condition (p < 0.05). Phantom-based optimization of CT hepatic examinations requires randomized lesion location when investigating challenging conditions; however, a standard phantom with fixed lesion location is suitable for the optimization of routine liver protocols. The development of more sophisticated phantoms or methods than those currently available is indicated for the optimization of CT protocols for diagnostic tasks involving the detection of subtle change.
本研究旨在确定基于体模的方法是否需要对 CT 肝脏病变检测进行随机化和包含正常图像来进行优化。一个包含不同大小固定不透明度(直径为 2.4、4.8 和 9.5 毫米)的体模在不同的曝光和切片厚度设置下进行扫描。比较了两组图像:第一组图像集中的所有图像均包含已知位置的不透明度;第二组图像集中的图像包含不透明度随机位置。经机构审查委员会批准,9 名经验丰富的观察者使用 4 分置信度量表对不透明度可视化进行评分。使用 Spearman、Kappa 和 Wilcoxon 技术比较两组图像。当结合所有不透明度大小进行比较时,观察者评分在两种方法之间表现出很强的相关性(r=0.92,p<0.0001),对于 9.5 毫米的不透明度(r=0.96,p<0.0001)和 2.4 毫米的不透明度(r=0.64,p<0.05)。4.8 毫米的不透明度没有显著相关性。对于单一切片厚度和曝光条件,与未知位置相比,已知位置的敏感度评分显著更高,适用于 9.5 毫米和 4.8 毫米的不透明度(p<0.05)。在研究挑战性条件时,CT 肝脏检查的基于体模优化需要随机化病变位置;然而,对于常规肝脏协议的优化,具有固定病变位置的标准体模是合适的。对于涉及检测细微变化的诊断任务的 CT 协议优化,需要开发比当前更复杂的体模或方法。