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基于CT衰减系数图的非均匀Chang衰减校正方法在(99m)Tc-GSA SPECT/CT肝脏成像中的可靠性及优势

Reliability and advantages of using non-uniform Chang's attenuation correction method using a CT-based attenuation coefficient map in (99m)Tc-GSA SPECT/CT hepatic imaging.

作者信息

Nakamura Yuya, Tomiguchi Seiji, Tanaka Masayuki

机构信息

Division of Medical Technology, Kumamoto University Hospital, 1-1-1 Honjyo, Chuo-ku, Kumamoto City, 860-8556, Japan.

Graduate School of Health Sciences, Kumamoto University, 4-24-1, Kuhonji, Chuo-ku, Kumamoto City, 862-0976, Japan.

出版信息

EJNMMI Phys. 2015 Dec;2(1):17. doi: 10.1186/s40658-015-0120-5. Epub 2015 Aug 14.

DOI:10.1186/s40658-015-0120-5
PMID:26501818
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4538714/
Abstract

BACKGROUND

Generally, attenuation correction is made by incorporating a linear attenuation coefficient, which is based on the attenuation coefficient map (mu-map) created from a computed tomography scan, into the ordered subsets-expectation maximization reconstruction method in non-uniform domains. A non-uniform Chang's attenuation correction method that uses the mu-map created from a computed tomography image that was made after reconstruction has been performed is currently available. The purpose of this study was to determine the usefulness of the non-uniform Chang's attenuation correction method in (99m)Tc-galactosyl human serum albumin diethylenetriamine pentaacetic acid single photon emission computed tomography/computed tomography imaging.

METHODS

Single photon emission computed tomography/computed tomography imaging was performed in phantoms with (99m)Tc water solutions and in a clinical study of 20 donors in living liver tissue transplantation. Attenuation correction was then performed in the reconstructed single photon emission computed tomography images with the non-uniform Chang's method and ordered subsets-expectation maximization attenuation correction methods with triple energy window scatter correction. Root mean square error values were used for assessment of the image uniformity, and we evaluated the absolute radioactivity in liver parts in the phantoms and those in the donors who had a normal liver function.

RESULTS

The values of root mean square error on the non-uniform Chang's attenuation correction images were lower than those on ordered subsets-expectation maximization attenuation correction images for both the phantoms and the 20 donors. The difference between the true and estimated radioactivity in the non-uniform Chang's attenuation correction method was smaller than that in the ordered subsets-expectation maximization attenuation correction methods in the phantom study.

CONCLUSIONS

The non-uniform Chang's attenuation correction is considered to be superior to the ordered subsets-expectation maximization attenuation correction in the assessment of absolute liver radioactivity and liver image uniformity on (99m)Tc-galactosyl human serum albumin diethylenetriamine pentaacetic acid single photon emission computed tomography/computed tomography imaging.

摘要

背景

一般来说,衰减校正通过将基于计算机断层扫描生成的衰减系数图(μ图)的线性衰减系数纳入非均匀域中的有序子集期望最大化重建方法来实现。目前有一种非均匀的张式衰减校正方法,它使用在重建后生成的计算机断层扫描图像创建的μ图。本研究的目的是确定非均匀张式衰减校正方法在99m锝-半乳糖基人血清白蛋白二乙三胺五乙酸单光子发射计算机断层扫描/计算机断层扫描成像中的实用性。

方法

对含有99m锝水溶液的体模以及20名活体肝组织移植供体进行了临床研究,进行单光子发射计算机断层扫描/计算机断层扫描成像。然后使用非均匀张式方法和具有三能量窗散射校正的有序子集期望最大化衰减校正方法对重建后的单光子发射计算机断层扫描图像进行衰减校正。均方根误差值用于评估图像均匀性,并且我们评估了体模中肝脏部分以及肝功能正常的供体中肝脏部分的绝对放射性。

结果

对于体模和20名供体,非均匀张式衰减校正图像上的均方根误差值均低于有序子集期望最大化衰减校正图像上的均方根误差值。在体模研究中,非均匀张式衰减校正方法中真实放射性与估计放射性之间的差异小于有序子集期望最大化衰减校正方法中的差异。

结论

在99m锝-半乳糖基人血清白蛋白二乙三胺五乙酸单光子发射计算机断层扫描/计算机断层扫描成像中评估肝脏绝对放射性和肝脏图像均匀性时,非均匀张式衰减校正被认为优于有序子集期望最大化衰减校正。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/05a34306e80c/40658_2015_120_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/d4a9f664ffef/40658_2015_120_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/564f122aa0a2/40658_2015_120_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/3aa8834ef04d/40658_2015_120_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/05a34306e80c/40658_2015_120_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/d4a9f664ffef/40658_2015_120_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/564f122aa0a2/40658_2015_120_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/3aa8834ef04d/40658_2015_120_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3e1/4538714/05a34306e80c/40658_2015_120_Fig4_HTML.jpg

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