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[F]氟代去甲肾上腺素淀粉样蛋白PET图像的贝叶斯惩罚似然重建算法中惩罚函数的优化

Optimization of penalization function in Bayesian penalized likelihood reconstruction algorithm for [F]flutemetamol amyloid PET images.

作者信息

Fukuda Shohei, Wagatsuma Kei, Miwa Kenta, Yakushiji Yu, Kamitaka Yuto, Yamao Tensho, Miyaji Noriaki, Ishii Kenji

机构信息

Medical Engineering, Kitasato University Graduate School of Medical Sciences, 1-15-1 Kitazato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan.

Research Team for Neuroimaging, Tokyo Metropolitan Institute for Geriatrics and Gerontology, 35-2, Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan.

出版信息

Phys Eng Sci Med. 2024 Dec;47(4):1627-1637. doi: 10.1007/s13246-024-01476-z. Epub 2024 Aug 12.

DOI:10.1007/s13246-024-01476-z
PMID:39133373
Abstract

Point-spread-function (PSF) correction is not recommended for amyloid PET images due to Gibbs artifacts. Q.Clear™, a Bayesian Penalized Likelihood (BPL) reconstruction method without incorporating PSF correction reduces these artifacts but degrades image contrast by our previous findings. The present study aimed to recover lost contrast by optimizing reconstruction parameters in time-of-flight (TOF) BPL reconstruction of amyloid PET images without PSF correction. We selected candidate conditions based on a phantom study and then determined which were optimal in a clinical study. Phantom images were reconstructed under conditions of 1‒9 iterations, β 300-1000 and γ factors from 2 to 10 in TOF-BPL without PSF correction. We evaluated the %contrast and the coefficients of variation (CV, %). Standardized uptake value ratios (SUVr) and Centiloid scales (CL) were calculated from PET images acquired from 71 participants after an [F]flutemetamol injection. Both %contrast and CV were independent of iterations, whereas a trade-off was found between γ factors and β. We selected a γ factors of 5 without PSF correction (iterations, 1; β, 500) and of 10 without PSF correction (iterations, 1; β, 800) as candidates for clinical investigation. The SUVr and CL remained stable across various conditions, and CL scales effectively discriminated amyloid PET using measured values. The optimal reconstruction parameters of TOF-BPL for [F]flutemetamol PET images were γ factor 10, iterations 1 and β 800, without PSF correction.

摘要

由于吉布斯伪影,不建议对淀粉样蛋白PET图像进行点扩散函数(PSF)校正。Q.Clear™是一种不包含PSF校正的贝叶斯惩罚似然(BPL)重建方法,根据我们之前的研究结果,该方法可减少这些伪影,但会降低图像对比度。本研究旨在通过优化无PSF校正的淀粉样蛋白PET图像飞行时间(TOF)BPL重建中的重建参数来恢复丢失的对比度。我们基于体模研究选择候选条件,然后在临床研究中确定哪些条件是最佳的。在无PSF校正的TOF-BPL中,在1至9次迭代、β值为300 - 1000以及γ因子为2至10的条件下重建体模图像。我们评估了对比度百分比和变异系数(CV,%)。从71名参与者注射[F]氟代脱氧葡萄糖后采集的PET图像中计算标准化摄取值比率(SUVr)和百分位量表(CL)。对比度百分比和CV均与迭代次数无关,而在γ因子和β之间发现了一种权衡。我们选择无PSF校正(迭代次数为1;β为500)时γ因子为5以及无PSF校正(迭代次数为1;β为800)时γ因子为10作为临床研究的候选条件。SUVr和CL在各种条件下保持稳定,并且CL量表使用测量值有效地鉴别了淀粉样蛋白PET。对于[F]氟代脱氧葡萄糖PET图像,TOF-BPL的最佳重建参数为γ因子10、迭代次数1和β 800,且无PSF校正。

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