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哪些因素会影响数据驱动型呼吸门控技术中的 R 值?一项体模研究。

What factors influence the R value in data-driven respiratory gating technique? A phantom study.

机构信息

Division of Radiology, Department of Medical Technology, Kochi Medical School Hospital, Nankoku, Kochi, Japan.

出版信息

Nucl Med Commun. 2022 Oct 1;43(10):1067-1076. doi: 10.1097/MNM.0000000000001609. Epub 2022 Sep 6.

Abstract

OBJECTIVE

The R value is adopted as a metric for the effectiveness of the respiratory waveform in the Advanced Motion Free implemented in the PET scanner as the data-driven respiratory gating (DDG) algorithm. The effects of changes in various factors on R values were evaluated by phantom analysis.

METHODS

We used a programmable respiratory motion phantom QUASAR with a sphere filled with an 18F solution. Respiratory motion simulation was performed by changing the sphere diameter, radioactivity concentration, amplitude, respiratory cycle, and respiratory waveform shape. Three evaluations were performed. (1) The power spectra calculated from the input waveforms were evaluated. (2) The effects of changes in the factors on the R value were evaluated. (3) DDG waveforms and inspiratory peak intervals were compared with the input waveform data set.

RESULTS

The R values were increased and converged to a certain value as sphere diameter, radioactivity concentration, and amplitude gradually increased. The respiratory cycle showed the highest R value at 7.5 s, and the graph showed an upward convex pattern. The R value of the sinusoid waveform was higher than that of the typical waveform. There was a relationship between the power spectrum of the input waveform and R value. The visual score was also lower in the condition with a lower R value. In cases of no sphere, radioactivity, or motion, and a fast respiratory cycle, peak intervals were not accurately acquired.

CONCLUSIONS

Factors affecting the R value were sphere diameter, radioactivity concentration, amplitude, respiratory cycle, and respiratory waveform shape.

摘要

目的

在 PET 扫描仪中,采用 R 值作为 Advanced Motion Free 中呼吸波形有效性的度量标准,该系统采用数据驱动的呼吸门控(DDG)算法。通过体模分析评估了各种因素变化对 R 值的影响。

方法

我们使用可编程呼吸运动体模 QUASAR,该体模内部充满了填充有 18F 溶液的球体。通过改变球体直径、放射性浓度、幅度、呼吸周期和呼吸波形形状来进行呼吸运动模拟。进行了三次评估。(1)从输入波形计算的功率谱进行评估。(2)评估因素变化对 R 值的影响。(3)比较 DDG 波形和吸气峰间隔与输入波形数据集。

结果

随着球体直径、放射性浓度和幅度逐渐增加,R 值增加并收敛到一定值。呼吸周期在 7.5 s 时显示出最高的 R 值,图形呈向上凸的模式。正弦波的 R 值高于典型波形。输入波形的功率谱与 R 值之间存在关系。R 值较低时,视觉评分也较低。在没有球体、放射性或运动以及快速呼吸周期的情况下,无法准确获取峰值间隔。

结论

影响 R 值的因素有球体直径、放射性浓度、幅度、呼吸周期和呼吸波形形状。

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