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首页> 外文会议>IEEE Nuclear Science Symposium;Medical Imaging Conference >Advancements in data-driven respiratory motion extraction methods for clinical list-mode 18F-FDG PET datasets acquired from a commercial PET scanner
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Advancements in data-driven respiratory motion extraction methods for clinical list-mode 18F-FDG PET datasets acquired from a commercial PET scanner

机译：从商业PET扫描仪获取的临床列表模式18F-FDG PET数据集的数据驱动呼吸运动提取方法的进展

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F-FDG PET datasets. They are activity distributions: (1) with high myocardial uptake, (2) same as (1) but with portion of the heart outside the image, and with high image intensity (3) in the liver and (4) in the lung area without attenuation compensation. In Method #1, a 3D volume-of-interest (VOI) was placed over the heart region of the PET image obtained from the total acquisition time period. The surrogate RM signals were obtained from the centroids of the image intensity of the myocardial activity uptake within the same VOI of PET images obtained from rebinned list-mode data in short time intervals. The Fourier Transform (FT) of the time sequence of surrogate RM signals and smoothing reveal the RM peak and its average period, Pav. In Methods #2, #3, and #4, specially-shaped 3D VOIs were placed over the heart, the top of the liver, and the bottom of the lungs, respectively. Then, the same procedures used in Method #1 were employed except using the total counts within the corresponding VOI. The location, sizes and shapes of the VOIs were optimized for the highest signal-to-noise (S/N) in the RM peak extraction. The improved RM extraction methods were evaluated using 14 patient datasets. Method #1 was shown to work well for 79% of the datasets, and Pav showing high S/N and excellent agreement (Pearson correlation coefficient 0.997) with those obtained from an external RM monitoring belt system. Method #2 was applied successfully to 14%, and Methods #3 and #4 to the rest of datasets. Excellent agreements were also found in cross comparison between the methods. We conclude that the improved data-driven RM extraction methods which showed successful results in various PET image datasets will provide an important first step for the motion compensation application in commercial PET scanners.
机译：F-FDG PET数据集。它们是活动分布：（1）心肌摄取高，（2）与（1）相同，但心脏的一部分位于图像外，并且图像强度高（3）在肝脏中（4）在肺部没有衰减补偿。在方法1中，将3D感兴趣体积（VOI）放置在从总采集时间段获得的PET图像的心脏区域上。替代RM信号是在短时间间隔内从重新组合的列表模式数据获得的PET图像的相同VOI范围内，从心肌活动摄取图像强度的质心获得的。替代RM信号和平滑的时间序列的傅立叶变换（FT）显示了RM峰及其平均周期Pav。在方法2，方法3和方法4中，将特殊形状的3D VOI分别放置在心脏，肝脏顶部和肺部底部。然后，采用方法1中相同的步骤，只是使用相应VOI中的总数。对VOI的位置，大小和形状进行了优化，以实现RM峰提取中的最高信噪比（S / N）。使用14个患者数据集评估了改进的RM提取方法。方法＃1在79％的数据集中显示良好，并且Pav与从外部RM监测带系统获得的数据相比具有较高的信噪比和极好的一致性（皮尔逊相关系数0.997）。方法2已成功应用于14％，方法3和4已应用于其余数据集。在方法之间的交叉比较中也发现了极好的协议。我们得出的结论是，改进的数据驱动RM提取方法在各种PET图像数据集中显示了成功的结果，将为运动补偿在商业PET扫描仪中的应用提供重要的第一步。

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