Filtered Back Projection, Adaptive Statistical Iterative Reconstruction, and a Model-based Iterative Reconstruction in Abdominal CT: An Experimental Clinical Study-猫眼课题宝

DOI：

10.1148/radiol.12112707

发表时间：

2013-01-01

期刊：

RADIOLOGY

影响因子：

19.7

通讯作者：

中科院分区：

医学1区

文献类型：

作者：

Deak, Zsuzsanna;Grimm, Jochen M.;Wirth, Stefan

目的：比较不同世代的三种图像重建算法在腹部常规多层螺旋CT检查中的主客观图像质量参数。材料和方法：这项机构审查委员会批准的研究包括22例连续接受腹部常规CT检查的患者(平均年龄56.1岁+/-15.8岁；平均体重79.1 kg+/-14.8 kg)。采用低对比度体模进行客观质量控制。原始数据集通过滤波反投影(FPB)、自适应统计迭代重建(ASIR)和基于模型的迭代重建(MBIR)进行重建。放射科医生使用半定量评分(-3到+3)来评估主观图像质量和伪影，将FBP和MBIR图像与ASIR图像进行比较。用Wilcoxon检验和组内相关系数对数据进行评价。对软组织结构的目标噪声和CT数的测量结果进行方差分析。结果：模型研究显示，与ASIR或FBP相比，MBIR的低对比度目标的可探测性更好。主观评分显示，MBIR的图像质量更高，与ASIR(均为P均为.001)相比，分辨率更高(中值为2；范围为1-3)，噪声更低(2；范围为1-3)，轮廓更精细(2；范围为1-2)。FBP表现较差(0，范围22至0)；-1[范围，-3至0]；0[范围，21至0]；ALL，P，.001)。观察者间的平均相关性图像感知为0.9，伪影为0.7。与ASIR算法相比，FBIR算法的客观噪声提高了14%~68%，MBIR算法降低了18%~47%(P&lt；.001)。结论：MBIR算法明显改善了常规腹部多层CT图像的主客观图像质量参数。(C)RSNA，2012年

Purpose: To compare objective and subjective image quality parameters of three image reconstruction algorithms of different generations at routine multidetector computed tomographic (CT) examinations of the abdomen.Materials and Methods: This institutional review board-approved study included 22 consecutive patients (mean age, 56.1 years +/- 15.8 [standard deviation]; mean weight, 79.1 kg +/- 14.8) who underwent routine CT examinations of the abdomen. A low-contrast phantom was used for objective quality control. Raw data sets were reconstructed by using filtered back projection (FPB), adaptive statistical iterative reconstruction (ASIR), and a model-based iterative reconstruction (MBIR). Radiologists used a semiquantitative scale (-3 to +3) to rate subjective image quality and artifacts, comparing both FBP and MBIR images with ASIR images. The Wilcoxon test and the intraclass correlation coefficient were used to evaluate the data. Measurements of objective noise and CT numbers of soft tissue structures were compared with analysis of variance.Results: The phantom study revealed an improved detectability of low-contrast targets for MBIR compared with ASIR or FBP. Subjective ratings showed higher image quality for MBIR, with better resolution (median value, 2; range, 1 to 3), lower noise (2; range, 1 to 3), and finer contours (2; range, 1 to 2) compared with ASIR (all P,.001). FBP performed inferiorly (0, range, 22 to 0]; -1 [range, -3 to 0]; 0 [range, 21 to 0], respectively; all, P,.001). Mean interobserver correlation was 0.9 for image perception and 0.7 for artifacts. Objective noise for FBP was 14%-68% higher and for MBIR was 18%-47% lower than that for ASIR (P < .001).Conclusion: The MBIR algorithm considerably improved objective and subjective image quality parameters of routine abdominal multidetector CT images compared with those of ASIR and FBP. (C) RSNA, 2012

Filtered Back Projection, Adaptive Statistical Iterative Reconstruction, and a Model-based Iterative Reconstruction in Abdominal CT: An Experimental Clinical Study

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