Faculty of Health Sciences, Universiti Sultan Zainal Abidin, Terengganu, Malaysia.
Discipline of Medical Radiation Sciences, Faculty of Health Sciences, The University of Sydney, Lidcombe, New South Wales, Australia.
J Med Radiat Sci. 2020 Sep;67(3):170-176. doi: 10.1002/jmrs.387. Epub 2020 Mar 27.
3D-printed imaging phantoms are now increasingly available and used for computed tomography (CT) dose optimisation study and image quality analysis. The aim of this study was to evaluate the integrated 3D-printed cardiac insert phantom when evaluating iterative reconstruction (IR) algorithm in coronary CT angiography (CCTA) protocols.
The 3D-printed cardiac insert phantom was positioned into a chest phantom and scanned with a 16-slice CT scanner. Acquisitions were performed with CCTA protocols using 120 kVp at four different tube currents, 300, 200, 100 and 50 mA (protocols A, B, C and D, respectively). The image data sets were reconstructed with a filtered back projection (FBP) and three different IR algorithm strengths. The image quality metrics of image noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were calculated for each protocol.
Decrease in dose levels has significantly increased the image noise, compared to FBP of protocol A (P < 0.001). As a result, the SNR and CNR were significantly decreased (P < 0.001). For FBP, the highest noise with poor SNR and CNR was protocol D with 19.0 ± 1.6 HU, 18.9 ± 2.5 and 25.1 ± 3.6, respectively. For IR algorithm, the highest strength (AIDR3D ) yielded the lowest noise with excellent SNR and CNR.
The use of IR algorithm and increasing its strengths have reduced noise significantly and thus increased the SNR and CNR when compared to FBP. Therefore, this integrated 3D-printed phantom approach could be used for dose optimisation study and image quality analysis in CCTA protocols.
3D 打印成像体模现在越来越多地被用于计算机断层扫描(CT)剂量优化研究和图像质量分析。本研究旨在评估在冠状动脉 CT 血管造影(CCTA)方案中评估迭代重建(IR)算法时,集成的 3D 打印心脏插入体模的性能。
将 3D 打印的心脏插入体模放置在胸部体模中,并使用 16 层 CT 扫描仪进行扫描。使用 120kVp 在四个不同的管电流(分别为 300、200、100 和 50mA)下进行 CCTA 协议采集。使用滤波反投影(FBP)和三种不同的 IR 算法强度对图像数据集进行重建。计算每个协议的图像噪声、信噪比(SNR)和对比噪声比(CNR)等图像质量指标。
与协议 A 的 FBP 相比,剂量水平降低显著增加了图像噪声(P<0.001)。结果,SNR 和 CNR 显著降低(P<0.001)。对于 FBP,噪声最高、SNR 和 CNR 最差的是协议 D,分别为 19.0±1.6HU、18.9±2.5 和 25.1±3.6。对于 IR 算法,强度最高(AIDR3D)的算法产生的噪声最低,SNR 和 CNR 最佳。
与 FBP 相比,使用 IR 算法并增加其强度可显著降低噪声,从而提高 SNR 和 CNR。因此,这种集成的 3D 打印体模方法可用于 CCTA 方案中的剂量优化研究和图像质量分析。