S. S. Sanabria Bohórquez, Suzanne Baker, P. Manser, Matteo Tonietto, Christopher Galli, Kristin R. Wildsmith, Yixuan Zou, G. Kerchner, R. Weimer, E. Teng
{"title":"使用线性混合效应模型评估部分体积校正和分析阿尔茨海默病的纵向[18F]GTP1 tau PET 成像","authors":"S. S. Sanabria Bohórquez, Suzanne Baker, P. Manser, Matteo Tonietto, Christopher Galli, Kristin R. Wildsmith, Yixuan Zou, G. Kerchner, R. Weimer, E. Teng","doi":"10.3389/fnimg.2024.1355402","DOIUrl":null,"url":null,"abstract":"We evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [18F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM).We applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. 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引用次数: 0
摘要
我们评估了部分容积校正(PVC)方法对阿尔茨海默病纵向[18F]GTP1 tau正电子发射断层扫描(PET)量化的影响,以及使用线性混合效应模型(LMEM)描述tau病理负担时间轨迹的适宜性。我们将 Van Cittert 迭代解卷积 (VC)、2 室和 3 室以及几何转移矩阵加基于区域的体素方法应用于一项阿尔茨海默病自然史研究中在单个成像站点获取的 18 个月的数据。我们通过比较诊断组和 tau 负担水平组之间的标准化摄取值比变化(%ΔSUVR)以及 LMEM 得出的纵向可重复性,确定了最佳 PVC 方法。在一项自然史研究和一项针对前驱期至轻度阿尔茨海默病的semorinemab多点临床试验中,通过将结果与传统的每次探访估计值进行比较,评估了LMEM分析法计算%ΔSUVR的性能。在不使用PVC的情况下,受试者内变异性最低,组间分离得分也可接受。结果表明,在纵向[18F]GTP1 PET 数据的量化方面,测试的 PVC 方法与非 PVC 图像相比没有明显的优势或改进。LMEM为纵向tau PET量化提供了一个稳健的框架,纵向测试-再测试变异性较低。
Evaluation of partial volume correction and analysis of longitudinal [18F]GTP1 tau PET imaging in Alzheimer's disease using linear mixed-effects models
We evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [18F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM).We applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden–level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates.The VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability.The results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [18F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test–retest variability.NCT02640092 and NCT03289143.