Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Clin Radiol. 2013 Sep;68(9):902-8. doi: 10.1016/j.crad.2013.03.024. Epub 2013 May 21.
To evaluate the relationship between different noise indices (NIs) and radiation dose and to compare the effect of different reconstruction algorithm applications for ultra-low-dose chest computed tomography (CT) on image quality improvement and the accuracy of volumetric measurement of ground-glass opacity (GGO) nodules using a phantom study.
A 11 cm thick transverse phantom section with a chest wall, mediastinum, and 14 artificial GGO nodules with known volumes (919.93 ± 64.05 mm(3)) was constructed. The phantom was scanned on a Discovery CT 750HD scanner with five different NIs (NIs = 20, 30, 40, 50, and 60). All data were reconstructed with a 0.625 mm section thickness using the filtered back-projection (FBP), 50% adaptive statistical iterative reconstruction (ASiR), and Veo model-base iterative reconstruction algorithms. Image noise was measured in six regions of interest (ROIs). Nodule volumes were measured using a commercial volumetric software package. The image quality and the volume measurement errors were analysed.
Image noise increased dramatically from 30.7 HU at NI 20 to 122.4 HU at NI 60, with FBP reconstruction. Conversely, Veo reconstruction effectively controlled the noise increase, with an increase from 9.97 HU at NI 20 to only 15.1 HU at NI 60. Image noise at NI 60 with Veo was even lower (50.8%) than that at NI 20 with FBP. The contrast-to-noise ratio (CNR) of Veo at NI 40 was similar to that of FBP at NI 20. All artificial GGO nodules were successfully identified and measured with an average relative volume measurement error with Veo at NI 60 of 4.24%, comparable to a value of 10.41% with FBP at NI 20. At NI 60, the radiation dose was only one-tenth that at NI 20.
The Veo reconstruction algorithms very effectively reduced image noise compared with the conventional FBP reconstructions. Using ultra-low-dose CT scanning and Veo reconstruction, GGOs can be detected and quantified with an acceptable accuracy.
评估不同噪声指数(NI)与辐射剂量之间的关系,并通过体模研究比较不同重建算法应用于超低剂量胸部 CT 对图像质量改善和磨玻璃密度(GGO)结节容积测量准确性的影响。
构建了一个 11cm 厚的横断面体模,包括胸壁、纵隔和 14 个具有已知容积(919.93±64.05mm³)的人工 GGO 结节。体模在 Discovery CT 750HD 扫描仪上以 5 个不同的 NI(NI=20、30、40、50 和 60)进行扫描。所有数据均使用 0.625mm 层厚进行滤波反投影(FBP)、50%自适应统计迭代重建(ASiR)和 Veo 模型基础迭代重建算法重建。在六个感兴趣区域(ROI)测量图像噪声。使用商业容积软件包测量结节容积。分析图像质量和体积测量误差。
FBP 重建时,NI 从 20 增加到 60 时,图像噪声从 30.7HU 急剧增加到 122.4HU,而 Veo 重建则有效控制了噪声的增加,NI 从 20 增加到 60 时,噪声仅从 9.97HU 增加到 15.1HU。NI 60 时的 Veo 噪声甚至比 NI 20 时的 FBP 噪声低 50.8%。NI 40 时的对比噪声比(CNR)与 NI 20 时的 FBP 相似。所有人工 GGO 结节均能成功识别和测量,NI 60 时 Veo 的平均相对体积测量误差为 4.24%,与 NI 20 时 FBP 的 10.41%相当。在 NI 60 时,辐射剂量仅为 NI 20 时的十分之一。
与传统 FBP 重建相比,Veo 重建算法可有效降低图像噪声。使用超低剂量 CT 扫描和 Veo 重建,可以以可接受的准确性检测和量化 GGO。