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 Apr;36(4):420-426. doi: 10.1007/s12149-022-01721-z. Epub 2022 Feb 9.
The aim of this study was to evaluate an image reconstruction algorithm, including a new maximum-likelihood attenuation correction factor (ML-ACF) for time of flight (TOF) brain positron emission tomography (PET).
The implemented algorithm combines an ML-ACF method that simultaneously estimates both the emission image and attenuation sinogram from TOF emission data, and a scaling method based on anatomical features. To evaluate the algorithm's quantitative accuracy, three-dimensional brain phantom images were acquired and soft-tissue attenuation coefficients and emission values were analyzed.
The heterogeneous distributions of attenuation coefficients in soft tissue, skull, and nasal cavity were sufficiently visualized. The attenuation coefficient of soft tissue remained within 5% of theoretical value. Attenuation-corrected emission showed no lateral differences, and significant differences among soft tissue were within the error range.
The ML-ACF-based attenuation correction implemented for TOF brain PET worked well and obtained practical levels of accuracy.
本研究旨在评估一种图像重建算法，包括一种新的用于飞行时间（TOF）脑正电子发射断层扫描（PET）的最大似然衰减校正因子（ML-ACF）。
所实现的算法结合了一种 ML-ACF 方法，该方法可以从 TOF 发射数据中同时估计发射图像和衰减正弦图，以及一种基于解剖特征的缩放方法。为了评估算法的定量准确性，采集了三维脑体模图像，并分析了软组织衰减系数和发射值。
软组织、颅骨和鼻腔中的衰减系数的不均匀分布得到了充分的可视化。软组织的衰减系数保持在理论值的 5%以内。衰减校正后的发射没有横向差异，软组织之间的显著差异在误差范围内。
针对 TOF 脑 PET 实施的基于 ML-ACF 的衰减校正效果良好，并且获得了实用的准确度水平。
