Renal statistical map for positron emission tomography with [O-15] water.
Renal statistical map for positron emission tomography with [O-15] water.
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DOI：
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发表时间：
2019
影响因子：
2.5
通讯作者：
Mahabubur Rahman-;H. Watabe;M. Shidahara;S. Watanuki;M. Tashiro;Takefumi Mori;S. Ito;Yusuke Ohsaki
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文献类型：
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作者：
Mahabubur Rahman-;H. Watabe;M. Shidahara;S. Watanuki;M. Tashiro;Takefumi Mori;S. Ito;Yusuke Ohsaki
图像统计常用于功能和分子成像研究，在这类研究中，将具有特定诊断的患者组的图像与在人口统计学变量上匹配的健康对照组的图像进行比较。脑成像中图像统计的成功促使我们开发一种获取体积归一化肾脏的方法来进行图像统计，以便我们能够局部可视化某些组之间在肾脏血流动力学参数方面逐个体素比较的统计学显著差异。对于这一演变过程的发展，我们首先使用仿射变换将所有受试者（包括健康对照（HC）和慢性肾衰竭（CRF）患者）的¹⁵O - 水正电子发射断层扫描（PET）图像相对于一名HC受试者的磁共振成像（MRI）图像进行体积归一化。然后通过基函数法获得归一化肾脏的¹⁵O动力学参数图像。最后，使用基于无阈值聚类增强的置换法生成这些参数图像的统计图。发现肾脏的动力学参数，即摄取速率常数（K₁）、清除速率常数（k₂）和血容量（Vₐ）在CRF中明显低于HC中的相应参数，并且发现k₂参数与K₁和Vₐ相比更稳定。这些参数图像的统计图使我们能够可视化HC和CRF组之间统计学上的局部显著差异（P < 0.05）。尽管PET和MRI技术在肾脏的功能和分子成像方面具有巨大潜力，但它们最多处于实验水平。据推测，肾脏的统计图在成功实施功能性和分子性肾脏成像中可能发挥重要作用。然而，为了该过程的稳健性，将需要涉及更大样本量和改进归一化技术的更多研究。
Image statistics are frequently used for functional and molecular imaging research in which images from a patient group with a specific diagnosis are compared with images from a healthy control group who have been matched for demographic variables. The success of image statistics for brain imaging has encouraged us to develop a method for obtaining volumetrically normalized kidney to perform image statistics so that we can locally visualize the statistical significant difference comparing voxel by voxel between certain groups in terms kidney blood flow kinetic parameters. For the development of this evolutionary process, we first volumetrically normalized all subjects, which include healthy control (HC) and chronic renal failure (CRF) patients, 15O water PET image with respect to one HC subject's MRI image using affine transformation. Then 15O kinetic parametric images of normalized kidneys were obtained through the basis function method. Finally, the statistical map of these parametric images was produced using the threshold-free cluster enhancement based permutation method. Kinetic parameters of kidney namely, uptake rate constant (K1), clearance rate constant (k2) and blood volume (Va), were found to be notably lower in CRF than those of in HC and k2 parameter was found to be more stable compared to K1 and Va. The statistical map of these parametric images allowed us to visualize local significant differences statistically (P<0.05) between HC and CRF groups. Though PET and MRI techniques have enormous potentiality for functional and molecular imaging of kidney, these are, at best, in experimental level. It is speculated that statistical mapping of kidney could play a significant role in the successful implementation of functional and molecular kidney imaging. However, more research involving a larger sample size and improved normalization technique will be needed for the robustness of the process.