Evaluation of data-driven respiratory gating for subcentimeter lesions using digital PET/CT system and three-axis motion phantom
Evaluation of data-driven respiratory gating for subcentimeter lesions using digital PET/CT system and three-axis motion phantom
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DOI：
10.1088/2057-1976/aca90d
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发表时间：
2023-01-01
影响因子：
1.4
通讯作者：
Terauchi, Takashi
中科院分区：
文献类型：
--
作者：
Fukai, Shohei;Daisaki, Hiromitsu;Terauchi, Takashi
导论.数据驱动呼吸门控（DDG）在具有呼吸运动的亚厘米病变中的应用仍然知之甚少。因此，本研究旨在阐明DDG在亚厘米级病变中的应用以及数字正电子发射断层扫描/计算机断层扫描（PET/CT）系统结合DDG在三轴呼吸下检测这些病变的能力。方法.使用Discovery MI PET/CT系统和美国国家电气制造商协会（NEMA）体模（带微型空心球（4、5、6、8、10和13 mm））。对于每个热球和背景区域，用42.4和5.3 kBq/ml的F-18-FDG溶液填充NEMA体模。使用运动平台UniTraQ再现三轴呼吸运动的3.6 s周期。PET数据采集是在静止和旋转运动状态下进行的。在三个PET组中重建数据：静止（NM-PET）、无门控呼吸运动（NG-PET）和DDG门控呼吸运动（DDG-PET）组。对于图像质量，在每个PET组中评价对比度百分比（Q（H））;最大、峰值和平均标准化摄取值（SUV）;背景区域;和可检测性指数（DI）。还进行了目视评估。结果与NM-PET相比，呼吸运动组的Q（H）和SUV恶化。与NG-PET相比，DDG-PET在6 mm以上的球体中显著改善了Q（H）和SUV。8 mm球的SUVmax、SUVpeak和Q（H）值在NM-PET中最高，其次是DDG-PET和NG-PET。在视觉评估中，在所有PET组中检测到大于6 mm的球体。DDG应用没有检测到新的病变，但它增加了DI和视觉评分。结论.基于主成分分析（PCA）的DDG算法的应用程序，提高了图像质量和定量SUV在亚厘米级病变测量超过6毫米。虽然DDG应用程序不能检测到新的亚厘米级病变，它增加了视觉指数。
Introduction. The application of data-driven respiratory gating (DDG) for subcentimeter lesions with respiratory movement remains poorly understood. Hence, this study aimed to clarify DDG application for subcentimeter lesions and the ability of digital Positron emission tomography/computed tomography (PET/CT) system combined with DDG to detect these lesions under three-axis respiration. Methods. Discovery MI PET/CT system and National Electrical Manufacturers Association (NEMA) body phantom with Micro Hollow Sphere (4, 5, 6, 8, 10, and 13 mm) were used. The NEMA phantom was filled with F-18-FDG solutions of 42.4 and 5.3 kBq/ml for each hot sphere and background region. The 3.6 s cycles of three-axis respiratory motion were reproduced using the motion platform UniTraQ. The PET data acquisition was performed in stationary and respiratory-moving states. The data were reconstructed in three PET groups: stationary (NM-PET), no gating with respiratory movement (NG-PET), and DDG gating with respiratory movement (DDG-PET) groups. For image quality, percent contrast (Q(H)); maximum, peak, and mean standardized uptake value (SUV); background region; and detectability index (DI) were evaluated in each PET group. Visual assessment was also conducted. Results. The groups with respiratory movement had deteriorated Q(H) and SUVs compared with NM-PET. Compared with NG-PET, DDG-PET has significantly improved Q(H) and SUVs in spheres above 6 mm. The background region showed no significant difference between groups. The SUVmax, SUVpeak, and Q(H) values of 8 mm sphere were highest in NM-PET, followed by DDG-PET and NG-PET. In visual assessment, the spheres above 6 mm were detected in all PET groups. DDG application did not detect new lesions, but it increased DI and visual score. Conclusions. The application of principal component analysis (PCA)-based DDG algorithm improves both image quality and quantitative SUVs in subcentimeter lesions measuring above 6 mm. Although DDG application cannot detect new subcentimeter lesions, it increases the visual indices.