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首页> 外文期刊>Clinical Radiology: Journal of the Royal College of Radiologists >Impact of the adaptive statistical iterative reconstruction technique on image quality in ultra-low-dose CT
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Impact of the adaptive statistical iterative reconstruction technique on image quality in ultra-low-dose CT

机译:自适应统计迭代重建技术对超低剂量CT图像质量的影响

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Aim 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. Materials and methods A 11 cm thick transverse phantom section with a chest wall, mediastinum, and 14 artificial GGO nodules with known volumes (919.93 ± 64.05 mm3) 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. Results 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. Conclusion 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.
机译:目的评估不同噪声指数(NIs)与辐射剂量之间的关系,并比较不同重建算法应用在超低剂量胸部计算机断层扫描(CT)上对图像质量改善和地面容积测量准确性的影响。玻璃体不透明性(GGO)结节使用体模研究。材料和方法构建了一个11厘米厚的横向幻影截面,带有一个胸壁,纵隔和14个已知体积(919.93±64.05 mm3)的人造GGO结节。在具有五个不同NI(NI = 20、30、40、50和60)的Discovery CT 750HD扫描仪上扫描了幻像。使用滤波后的反投影(FBP),50%自适应统计迭代重建(ASiR)和基于Veo模型的迭代重建算法,以0.625 mm的截面厚度重建所有数据。在六个感兴趣区域(ROI)中测量了图像噪声。结节体积使用商业体积软件包测量。分析了图像质量和体积测量误差。结果通过FBP重建,图像噪声从NI 20的30.7 HU急剧增加到NI 60的122.4 HU。相反,Veo重建有效地控制了噪声的增加,从NI 20的9.97 HU增加到NI 60的15.1 HU。使用Veo的NI 60的图像噪声甚至比带有FBP的NI 20的噪声低(50.8%)。在NI 40时,Veo的对比度噪声比(CNR)与在NI 20时的FBP相似。所有人工GGO结节均已成功识别并测量,在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%值相当。在NI 60时,辐射剂量仅为NI 20时的辐射剂量的十分之一。结论与传统的FBP重建相比,Veo重建算法非常有效地降低了图像噪声。使用超低剂量CT扫描和Veo重建,可以以可接受的精度检测和定量GGO。

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