Suppr超能文献

177Lu SPECT 体模图像中的纹理分析:使用纹理特征评估均匀性要求的统计学评估。

Texture analysis in 177Lu SPECT phantom images: Statistical assessment of uniformity requirements using texture features.

机构信息

Medical Physics Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Forli-Cesena, Italy.

Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Forli-Cesena, Italy.

出版信息

PLoS One. 2019 Jul 31;14(7):e0218814. doi: 10.1371/journal.pone.0218814. eCollection 2019.

Abstract

The purpose of this study was to apply texture analysis (TA) to evaluate the uniformity of SPECT images reconstructed with the 3D Ordered Subsets Expectation Maximization (3D-OSEM) algorithm. For this purpose, a cylindrical homogeneous phantom filled with 177Lu was used and a total of 24 spherical volumes of interest (VOIs) were considered inside the phantom. The location of the VOIs was chosen in order to define two different configurations, i.e. gravity and radial configuration. The former configuration was used to investigate the uniformity of distribution of 177Lu inside the phantom, while the latter configuration was used to investigate the lack of uniformity from center towards edge of the images. For each VOI, the trend of different texture features considered as a function of 3D-OSEM updates was investigated in order to evaluate the influence of reconstruction parameters. TA was performed using CGITA software. The equality of the average texture feature trends in both spatial configurations was assumed as the null hypothesis and was tested by functional analysis of variance (fANOVA). With regard to the gravity configuration, no texture feature rejected the null hypothesis when the number of subsets increased. For the radial configuration, the statistical analysis revealed that, depending on the 3D-OSEM parameters used, a few texture features were capable of detecting the non-uniformity of 177Lu distribution inside the phantom moving from the center of the image towards its edge. Finally, cross-correlation coefficients were calculated to better identify the features that could play an important role in assessing quality assurance procedures performed on SPECT systems.

摘要

本研究旨在应用纹理分析(TA)来评估使用 3D 有序子集期望最大化(3D-OSEM)算法重建的 SPECT 图像的均匀性。为此,使用充满 177Lu 的圆柱形均匀体模,并在体模内部考虑总共 24 个球形感兴趣区域(VOI)。VOI 的位置选择是为了定义两种不同的配置,即重力和径向配置。前者配置用于研究 177Lu 在体模内的分布均匀性,后者配置用于研究图像中心到边缘的不均匀性。对于每个 VOI,研究了不同纹理特征作为 3D-OSEM 更新函数的趋势,以评估重建参数的影响。TA 使用 CGITA 软件进行。假设平均纹理特征趋势在两种空间配置中的相等性是零假设,并通过方差分析(fANOVA)进行检验。对于重力配置,当子集数量增加时,没有纹理特征拒绝零假设。对于径向配置,统计分析表明,根据使用的 3D-OSEM 参数,一些纹理特征能够检测到从图像中心向边缘移动时 177Lu 分布的不均匀性。最后,计算了互相关系数,以更好地识别在评估 SPECT 系统质量保证程序中可能起重要作用的特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f8f/6668785/6e0fa8dcec38/pone.0218814.g002.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验