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能谱CT在减轻肝脏高密度植入物硬化伪影的研究

发布时间:2019-03-28 13:19
【摘要】:目的:研究在非增强扫描中宝石能谱CT减轻肝脏高密度植入物引起的射线束硬化伪影最佳单能量,通过对基物质对图的分析辨别肝内植入物的物质。 资料与方法:选取肝癌术后的62个病例,进行能谱扫描(Gestone spectralimaging,GSI),其中获得碘油硬化伪影图像99层,125I粒子金属伪影图像19层,钛止血夹金属伪影28层,所选层面以lOkeV为间距,在40keV~140keV间进行图像重建,共获得11组不同能量水平的单能量图像,分别为单能量图像mono图像和mono+MARs(Metalartifacts reducing system)图像,同时获得平均能量图(QC图)并重建6种基物质对图像。量化分析:以每一层为一个单元,在高密度植入物区边缘硬化伪影明显处测量并计算获得伪影指数(artifact index, AI)AI=。测量同层腹壁皮下脂肪作为层面的背景噪声。主观分析:对各种基物质对图像进行比较分析,并对物质密度及物质所在片区边缘密度这两个重要特征进行评分,以区分碘油、金属粒子与钛止血夹金属三种物质在不同基物质对图中的差异。采用SPSS18.0对所获得的全部数据进行分析处理,,所有数据均进行方差齐性检验和正态性检验,以P0.05为差异有统计学意义。 结果分析:80keV是降低碘油和钛夹的硬化伪影的最佳单能量,而粒子的最佳单能量出现在70keV。各组物质mono+MARs图像和mono图像的图像噪声在70keV下能到达最低。mono+MARs图像和mono图对比,除对125I粒子组AI值在40~90keV时有统计学差异外,其他均没表现出统计学差异。与QC图的比较分析中,单能量图像与QC图AI比较有明显的统计学差异(P0.05);而SDn值与QC图比较没有有明显的统计学差异。 结合mono+MARs70keV图像,对六组基物质图的比较分析及其物质密度和物质片区边缘密度这两个重要特征进行评分,根据碘油、125I粒子及钛夹在基物质图像中的不同表现,可在CT图像中对不同基物质进行区分,并可在混合物质图像中将碘油和钛夹,碘油和125I粒子进行有效区分。 结论:单能量图像与QC图像相比较,它能有效减轻高密度物质的硬化伪影;根据基物质对图像对比可以初步判断物质的类型,可以通过分析不同基物质对图像的的密度和物质片区边缘密度有效区分三种植入物。
[Abstract]:Aim: to study the optimal single energy of gemstone energy spectrum (CT) to reduce the X-ray beam hardening artifact induced by liver high density implants in non-contrast scanning, and to identify the implantable substance in liver by analyzing the image of the base substance. Materials and methods: 62 cases of liver cancer after operation were selected for energy spectrum scanning (Gestone spectralimaging,GSI). 99 images of iodized oil hardening artifacts, 19 images of 125i seed metal artifacts and 28 layers of metal artifacts of titanium hemostatic clips were obtained. The selected layers are spaced by lOkeV and reconstructed between 40keV~140keV. Eleven groups of single energy images with different energy levels are obtained, which are single energy image mono image and mono MARs (Metalartifacts reducing system) image, respectively. At the same time, the average energy map (QC) was obtained and the images of 6 base matter pairs were reconstructed. Quantitative analysis: using each layer as a unit, the artifact index (artifact index, AI) AI=. was obtained by measuring and calculating the hardening artifacts at the edge of the high density implant region. The subcutaneous fat of the same abdominal wall was measured as the background noise on the plane. Subjective analysis: to compare and analyze the images of various base substances, and to grade the two important characteristics of the density of the material and the density of the edge of the area in which the substance is located, in order to distinguish the iodized oil. Differences between metal particles and titanium hemostatic clamp metal in different base material pairs. All the data were analyzed by SPSS18.0, and all the data were tested by variance homogeneity test and normality test. The difference was statistically significant (P0.05). The results showed that 80keV was the best single energy to reduce the hardening artifact of iodized oil and titanium clip, and the optimal single energy of particles appeared at 70 Kev. The image noise of mono MARs images and mono images was the lowest in 70keV. The comparison between mono MARs images and mono images showed that there was no statistical difference in the AI value of 125i seed group except for the 40~90keV of 125i seed group. Compared with QC, the AI of single-energy image was significantly different from that of QC (P0.05), but there was no significant difference between SDN and QC (P0.05). Combined with mono MARs70keV images, the comparative analysis of six groups of basic material maps and their two important characteristics, material density and edge density of material slice, were evaluated. According to the different manifestations of iodized oil, 125i seeds and titanium clamped in the base material image, Different base substances can be distinguished in CT images, and iodized oil and titanium clamps, iodized oil and 125i seeds can be effectively distinguished in mixed material images. Conclusion: compared with QC images, single energy images can effectively reduce the hardening artifacts of high density substances. According to the comparison of the base material to the image, the type of the substance can be preliminarily judged. By analyzing the density of the image and the density of the edge of the material region, the three planting inputs can be effectively distinguished by the analysis of the density of the base material to the image.
【学位授予单位】:华南理工大学
【学位级别】:硕士
【学位授予年份】:2013
【分类号】:R816.5

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