Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
Department of Radiology, University of Michigan, Ann Arbor, MI, United States.
Neuroimage. 2022 Feb 1;246:118775. doi: 10.1016/j.neuroimage.2021.118775. Epub 2021 Dec 7.
The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smoothing of amyloid-PET scans performed with any of the FDA-approved radiotracers (F-florbetapir/FBP, F-florbetaben/FBB or F-flutemetamol/FLUTE). Each image undergoes spatial normalization based on weighted PET templates and data-driven differential smoothing, then allowing users to perform their quantification of choice. Prior to normalization, users can choose whether to automatically reset the origin of the image to the center of mass or proceed with the pipeline with the image as it is. We validate rPOP with n = 740 (514 FBP, 182 FBB, 44 FLUTE) amyloid-PET scans from the Imaging Dementia-Evidence for Amyloid Scanning - Brain Health Registry sub-study (IDEAS-BHR) and n = 1,518 scans from the Alzheimer's Disease Neuroimaging Initiative (n = 1,249 FBP, n = 269 FBB), including heterogeneous acquisition and reconstruction protocols. After running rPOP, a standard quantification to extract Standardized Uptake Value ratios and the respective Centiloids conversion was performed. rPOP-based amyloid status (using an independent pathology-based threshold of ≥24.4 Centiloid units) was compared with either local visual reads (IDEAS-BHR, n = 663 with complete valid data and reads available) or with amyloid status derived from an MRI-based PET processing pipeline (ADNI, thresholds of >20/>18 Centiloids for FBP/FBB). Finally, within the ADNI dataset, we tested the linear associations between rPOP- and MRI-based Centiloid values. rPOP achieved accurate warping for N = 2,233/2,258 (98.9%) in the first pass. Of the N = 25 warping failures, 24 were rescued with manual reorientation and origin reset prior to warping. We observed high concordance between rPOP-based amyloid status and both visual reads (IDEAS-BHR, Cohen's k = 0.72 [0.7-0.74], ∼86% concordance) or MRI-pipeline based amyloid status (ADNI, k = 0.88 [0.87-0.89], ∼94% concordance). rPOP- and MRI-pipeline based Centiloids were strongly linearly related (R:0.95, p<0.001), with this association being significantly modulated by estimated PET resolution (β= -0.016, p<0.001). rPOP provides reliable MRI-free amyloid-PET warping and quantification, leveraging widely available software and only requiring an attenuation-corrected amyloid-PET image as input. The rPOP pipeline enables the comparison and merging of heterogeneous datasets and is publicly available at https://github.com/leoiacca/rPOP.
用于淀粉样蛋白-PET 定量的参考标准在多中心研究和临床试验中都需要结构 MRI(sMRI)进行预处理。在这里,我们描述了 rPOP(稳健的仅 PET 处理),这是一个基于 MATLAB 的无 MRI 管道,可实现使用任何 FDA 批准的放射性示踪剂(F-氟比他滨/FBP、F-氟比苯丙氨酸/FBB 或 F-氟代甲氧基苯丙氨酸/FLUTE)进行的淀粉样蛋白-PET 扫描的非线性变形和差异平滑。每个图像都基于加权 PET 模板进行空间归一化,并进行数据驱动的差异平滑,然后允许用户进行他们选择的定量。在归一化之前,用户可以选择是否自动将图像的原点重置为质心,或者使用图像本身继续进行管道处理。我们使用来自成像痴呆症-淀粉样蛋白扫描证据登记研究(IDEAS-BHR)的 n=740(514 FBP、182 FBB、44 FLUTE)淀粉样蛋白-PET 扫描和来自阿尔茨海默病神经影像学倡议(ADNI)的 n=1,518 扫描(n=1,249 FBP,n=269 FBB)来验证 rPOP,包括异构采集和重建协议。在运行 rPOP 后,进行标准定量以提取标准化摄取比值和相应的百分位值转换。使用独立的基于病理学的≥24.4 百分位单位的阈值)与局部视觉读数(IDEAS-BHR,n=663 个具有完整有效数据和可用读数)或与基于 MRI 的 PET 处理管道衍生的淀粉样蛋白状态(ADNI,FBP/FBB 的>20/>18 百分位的阈值)进行比较。最后,在 ADNI 数据集内,我们测试了 rPOP 和基于 MRI 的百分位值之间的线性关联。rPOP 在第一阶段实现了 N=2,233/2,258(98.9%)的准确变形。在 N=25 个变形失败中,有 24 个在变形前通过手动重新定向和原点重置得到了挽救。我们观察到 rPOP 基于淀粉样蛋白状态与视觉读数(IDEAS-BHR,k=0.72[0.7-0.74],86%一致性)或 MRI 管道基于淀粉样蛋白状态(ADNI,k=0.88[0.87-0.89],94%一致性)之间具有高度一致性。rPOP 和基于 MRI 的百分位值之间存在强烈的线性关系(R:0.95,p<0.001),这种关联受到估计的 PET 分辨率的显著调节(β=-0.016,p<0.001)。rPOP 提供可靠的无 MRI 淀粉样蛋白-PET 变形和定量,利用广泛可用的软件,仅需要一个衰减校正的淀粉样蛋白-PET 图像作为输入。rPOP 管道能够比较和合并异构数据集,可在 https://github.com/leoiacca/rPOP 上获得。