Park Hye Lim, Park Sonya Youngju, Kim Mingeon, Paeng Soyeon, Min Eun Jeong, Hong Inki, Jones Judson, Han Eun Ji
Division of Nuclear Medicine, Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Division of Nuclear Medicine, Department of Radiology, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 10, 63-ro, Yeongdeungpo-gu, Seoul, 07345, Republic of Korea.
EJNMMI Phys. 2024 Jun 14;11(1):49. doi: 10.1186/s40658-024-00653-z.
Head motion during brain positron emission tomography (PET)/computed tomography (CT) imaging degrades image quality, resulting in reduced reading accuracy. We evaluated the performance of a head motion correction algorithm using F-flutemetamol (FMM) brain PET/CT images.
FMM brain PET/CT images were retrospectively included, and PET images were reconstructed using a motion correction algorithm: (1) motion estimation through 3D time-domain signal analysis, signal smoothing, and calculation of motion-free intervals using a Merging Adjacent Clustering method; (2) estimation of 3D motion transformations using the Summing Tree Structural algorithm; and (3) calculation of the final motion-corrected images using the 3D motion transformations during the iterative reconstruction process. All conventional and motion-corrected PET images were visually reviewed by two readers. Image quality was evaluated using a 3-point scale, and the presence of amyloid deposition was interpreted as negative, positive, or equivocal. For quantitative analysis, we calculated the uptake ratio (UR) of 5 specific brain regions, with the cerebellar cortex as a reference region. The results of the conventional and motion-corrected PET images were statistically compared.
In total, 108 sets of FMM brain PET images from 108 patients (34 men and 74 women; median age, 78 years) were included. After motion correction, image quality significantly improved (p < 0.001), and there were no images of poor quality. In the visual analysis of amyloid deposition, higher interobserver agreements were observed in motion-corrected PET images for all specific regions. In the quantitative analysis, the UR difference between the conventional and motion-corrected PET images was significantly higher in the group with head motion than in the group without head motion (p = 0.016).
The motion correction algorithm provided better image quality and higher interobserver agreement. Therefore, we suggest that this algorithm be adopted as a routine post-processing protocol in amyloid brain PET/CT imaging and applied to brain PET scans with other radiotracers.
脑正电子发射断层扫描（PET）/计算机断层扫描（CT）成像过程中的头部运动降低了图像质量，导致阅片准确性下降。我们使用F-氟代甲磺酸美他莫（FMM）脑PET/CT图像评估了一种头部运动校正算法的性能。
回顾性纳入FMM脑PET/CT图像，并使用一种运动校正算法重建PET图像：（1）通过三维时域信号分析、信号平滑以及使用合并相邻聚类方法计算无运动间隔来进行运动估计；（2）使用求和树结构算法估计三维运动变换；（3）在迭代重建过程中使用三维运动变换计算最终的运动校正图像。两名阅片者对所有传统和运动校正后的PET图像进行了视觉评估。使用三点量表评估图像质量，并将淀粉样蛋白沉积的存在解释为阴性、阳性或可疑。为了进行定量分析，我们计算了5个特定脑区的摄取率（UR），以小脑皮质作为参考区域。对传统和运动校正后的PET图像结果进行了统计学比较。
总共纳入了108例患者（34例男性和74例女性；中位年龄78岁）的108组FMM脑PET图像。运动校正后，图像质量显著改善（p<0.001），且没有质量差的图像。在淀粉样蛋白沉积的视觉分析中，对于所有特定区域，运动校正后的PET图像中观察者间的一致性更高。在定量分析中，有头部运动的组中传统和运动校正后的PET图像之间的UR差异显著高于无头部运动的组（p=0.016）。
该运动校正算法提供了更好的图像质量和更高的观察者间一致性。因此，我们建议将该算法作为淀粉样蛋白脑PET/CT成像的常规后处理方案，并应用于使用其他放射性示踪剂的脑PET扫描。
