Medical Systems Division, Shimadzu Corporation, 1, Nishinokyo Kuwabara-cho, Nakagyo-ku, Kyoto, 604-8511, Japan.
Technology Research Laboratory, Shimadzu Corporation, Kyoto, Japan.
Ann Nucl Med. 2022 Nov;36(11):998-1006. doi: 10.1007/s12149-022-01788-8. Epub 2022 Sep 28.
This study evaluates the phantom attenuation correction (PAC) method as an alternative to maximum-likelihood attenuation correction factor (ML-ACF) correction in time-of-flight (TOF) brain positron emission tomography (PET) studies.
In the PAC algorithm, a template emission image [Formula: see text] and a template attenuation coefficient image [Formula: see text] are prepared as a data set based on phantom geometry. Position-aligned attenuation coefficient image [Formula: see text] is derived by aligning [Formula: see text] using parameters that match the template emission image [Formula: see text] to measured emission image [Formula: see text]. Then, attenuation coefficient image [Formula: see text] combined with a headrest image is used for scatter and attenuation correction in the image reconstruction. To evaluate the PAC algorithm as an alternative to ML-ACF, Hoffman 3D brain and cylindrical phantoms were measured to obtain the image quality indexes of contrast and uniformity. These phantoms were also wrapped with a radioactive sheet to obtain attenuation coefficient images using ML-ACF. Emission images were reconstructed with attenuation correction by PAC and ML-ACF, and the results were compared using contrast and uniformity as well as visual assessment. CT attenuation correction (CT-AC) was also applied as a reference.
The contrast obtained by ML-ACF was slightly overestimated due to its unique experimental condition for applying ML-ACF in Hoffman 3D brain phantom but the uniformity was almost equivalent among ML-ACF, CT-AC, and PAC. PAC showed reasonable result without overestimation compared to ML-ACF and CT-AC.
PAC is an attenuation correction method that can ensure the performance in phantom test, and is considered to be a reasonable alternative to clinically used ML-ACF-based attenuation correction.
本研究评估了幻影衰减校正（PAC）方法作为飞行时间（TOF）脑正电子发射断层扫描（PET）研究中最大似然衰减校正因子（ML-ACF）校正的替代方法。
在 PAC 算法中，根据幻影几何形状准备模板发射图像 [Formula: see text] 和模板衰减系数图像 [Formula: see text] 作为数据集。通过使用与模板发射图像 [Formula: see text] 匹配的参数将 [Formula: see text] 与测量的发射图像 [Formula: see text] 对齐，得出位置对齐的衰减系数图像 [Formula: see text]。然后，将衰减系数图像 [Formula: see text] 与头枕图像结合，用于图像重建中的散射和衰减校正。为了评估 PAC 算法作为 ML-ACF 的替代方法，使用 Hoffman 3D 脑和圆柱形幻影进行了测量，以获得对比度和均匀性等图像质量指标。这些幻影还包裹了放射性薄片，以使用 ML-ACF 获得衰减系数图像。使用 PAC 和 ML-ACF 进行衰减校正后对发射图像进行重建，并使用对比度和均匀性以及视觉评估进行比较。还应用了 CT 衰减校正（CT-AC）作为参考。
由于在 Hoffman 3D 脑幻影中应用 ML-ACF 的独特实验条件，ML-ACF 获得的对比度略有高估，但均匀性在 ML-ACF、CT-AC 和 PAC 之间几乎相同。与 ML-ACF 和 CT-AC 相比，PAC 没有高估，显示出合理的结果。
PAC 是一种衰减校正方法，可以确保在幻影测试中的性能，并且被认为是临床使用的基于 ML-ACF 的衰减校正的合理替代方法。
