Chen L, Boone J M, Abbey C K, Hargreaves J, Bateni C, Lindfors K K, Yang K, Nosratieh A, Hernandez A, Gazi P
Department of Radiology, University of California, Davis, CA, USA.
Phys Med Biol. 2015 Apr 21;60(8):3347-58. doi: 10.1088/0031-9155/60/8/3347. Epub 2015 Mar 31.
The objective of this study was to compare the lesion detection performance of human observers between thin-section computed tomography images of the breast, with thick-section (>40 mm) simulated projection images of the breast. Three radiologists and six physicists each executed a two alterative force choice (2AFC) study involving simulated spherical lesions placed mathematically into breast images produced on a prototype dedicated breast CT scanner. The breast image data sets from 88 patients were used to create 352 pairs of image data. Spherical lesions with diameters of 1, 2, 3, 5, and 11 mm were simulated and adaptively positioned into 3D breast CT image data sets; the native thin section (0.33 mm) images were averaged to produce images with different slice thicknesses; average section thicknesses of 0.33, 0.71, 1.5 and 2.9 mm were representative of breast CT; the average 43 mm slice thickness served to simulate simulated projection images of the breast.The percent correct of the human observer's responses were evaluated in the 2AFC experiments. Radiologists lesion detection performance was significantly (p < 0.05) better in the case of thin-section images, compared to thick section images similar to mammography, for all but the 1 mm lesion diameter lesions. For example, the average of three radiologist's performance for 3 mm diameter lesions was 92% correct for thin section breast CT images while it was 67% for the simulated projection images. A gradual reduction in observer performance was observed as the section thickness increased beyond about 1 mm. While a performance difference based on breast density was seen in both breast CT and the projection image results, the average radiologist performance using breast CT images in dense breasts outperformed the performance using simulated projection images in fatty breasts for all lesion diameters except 11 mm. The average radiologist performance outperformed that of the average physicist observer, however trends in performance were similar. Human observers demonstrate significantly better mass-lesion detection performance on thin-section CT images of the breast, compared to thick-section simulated projection images of the breast.
本研究的目的是比较人类观察者在乳腺薄层计算机断层扫描图像与乳腺厚层(>40mm)模拟投影图像之间的病灶检测性能。三名放射科医生和六名物理学家各自进行了一项二选一强制选择(2AFC)研究,该研究涉及将模拟的球形病灶数学放置到在一台原型专用乳腺CT扫描仪上生成的乳腺图像中。使用来自88名患者的乳腺图像数据集创建了352对图像数据。模拟了直径为1、2、3、5和11mm的球形病灶,并将其自适应定位到三维乳腺CT图像数据集中;对原始薄层(0.33mm)图像进行平均以生成具有不同层厚的图像;0.33、0.71、1.5和2.9mm的平均层厚代表乳腺CT;平均43mm的层厚用于模拟乳腺的模拟投影图像。在2AFC实验中评估了人类观察者反应的正确百分比。除了1mm直径的病灶外,对于所有其他病灶,与类似于乳腺X线摄影的厚层图像相比,放射科医生在薄层图像情况下的病灶检测性能显著更好(p<0.05)。例如,对于直径为3mm的病灶,三名放射科医生在乳腺薄层CT图像上的平均性能正确率为92%,而在模拟投影图像上为67%。当层厚增加到超过约1mm时,观察到观察者性能逐渐下降。虽然在乳腺CT和投影图像结果中都观察到了基于乳腺密度的性能差异,但对于除11mm外的所有病灶直径,放射科医生使用致密乳腺中的乳腺CT图像的平均性能优于使用脂肪乳腺中的模拟投影图像的性能。放射科医生的平均性能优于平均物理学家观察者,然而性能趋势相似。与乳腺厚层模拟投影图像相比,人类观察者在乳腺薄层CT图像上表现出显著更好的肿块病灶检测性能。