Hu Tianjiao, Li Bingxuan, Yang Jigang, Zhang Bo, Fang Lei, Liu Yuqing, Xiao Peng, Xie Qingguo
Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China.
Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
Med Phys. 2024 Feb;51(2):1034-1046. doi: 10.1002/mp.16888. Epub 2023 Dec 16.
Computed tomography (CT)-based positron emission tomography (PET) attenuation correction (AC) is a commonly used method in PET AC. However, the CT truncation caused by the subject's limbs outside the CT field-of-view (FOV) leads to errors in PET AC.
In order to enhance the quantitative accuracy of PET imaging in the all-digital DigitMI 930 PET/CT system, we assessed the impact of FOV truncation on its image quality and investigated the effectiveness of geometric shape-based FOV extension algorithms in this system.
We implemented two geometric shape-based FOV extension algorithms. By setting the data from different numbers of detector channels on either side of the sinogram to zero, we simulated various levels of truncation. Specific regions of interest (ROI) were selected, and the mean values of these ROIs were calculated to visually compare the differences between truncated CT, CT extended using the FOV extension algorithms, and the original CT. Furthermore, we conducted statistical analyses on the mean and standard deviation of residual maps between truncated/extended CT and the original CT at different levels of truncation. Subsequently, similar data processing was applied to PET images corrected using original CT and those corrected using simulated truncated and extended CT images. This allowed us to evaluate the influence of FOV truncation on the images produced by the DigitMI 930 PET/CT system and assess the effectiveness of the FOV extension algorithms.
Truncation caused bright artifacts at the CT FOV edge and a slight increase in pixel values within the FOV. When using truncated CT data for PET AC, the PET activity outside the CT FOV decreased, while the extension algorithm effectively reduced these effects. Patient data showed that the activity within the CT FOV decreased by 60% in the truncated image compared to the base image, but this number could be reduced to at least 17.3% after extension.
The two geometric shape-based algorithms effectively eliminate CT truncation artifacts and restore the true distribution of CT shape and PET emission data outside the FOV in the all-digital DigitMI 930 PET/CT system. These two algorithms can be used as basic solutions for CT FOV extension in all-digital PET/CT systems.
基于计算机断层扫描（CT）的正电子发射断层扫描（PET）衰减校正（AC）是PET AC中常用的方法。然而，受检者肢体位于CT视野（FOV）之外导致的CT截断会导致PET AC出现误差。
为提高全数字DigitMI 930 PET/CT系统中PET成像的定量准确性，我们评估了FOV截断对其图像质量的影响，并研究了基于几何形状的FOV扩展算法在该系统中的有效性。
我们实施了两种基于几何形状的FOV扩展算法。通过将正弦图两侧不同数量探测器通道的数据设置为零，我们模拟了不同程度的截断。选择特定的感兴趣区域（ROI），计算这些ROI的平均值，以直观比较截断CT、使用FOV扩展算法扩展后的CT与原始CT之间的差异。此外，我们对不同截断水平下截断/扩展CT与原始CT之间残差图的均值和标准差进行了统计分析。随后，对使用原始CT校正的PET图像以及使用模拟截断和扩展CT图像校正的PET图像进行类似的数据处理。这使我们能够评估FOV截断对DigitMI 930 PET/CT系统产生的图像的影响，并评估FOV扩展算法的有效性。
截断在CT FOV边缘产生明亮伪影，并使FOV内像素值略有增加。当使用截断的CT数据进行PET AC时，CT FOV外的PET活性降低，而扩展算法有效降低了这些影响。患者数据显示，截断图像中CT FOV内的活性与基础图像相比降低了60%，但扩展后该数值可降至至少17.3%。
在全数字DigitMI 930 PET/CT系统中，这两种基于几何形状的算法有效地消除了CT截断伪影，并恢复了FOV外CT形状和PET发射数据的真实分布。这两种算法可作为全数字PET/CT系统中CT FOV扩展的基本解决方案。
