Image harmonization has been proposed to minimize heterogeneity in brain PET scans acquired in multi-center studies. However, standard validated methods and software tools are lacking. Here, we assessed the performance of a framework for the harmonization of brain PET scans in a multi-center European clinical trial. Hoffman 3D brain phantoms were acquired in 28 PET systems and reconstructed using site-specific settings. Full Width at Half Maximum (FWHM) of the Effective Image Resolution (EIR) and harmonization kernels were estimated for each scan. The target EIR was selected as the coarsest EIR in the imaging network. Using “Hoffman 3D brain Analysis tool,” indicators of image quality were calculated before and after the harmonization: The Coefficient of Variance (COV%), Gray Matter Recovery Coefficient (GMRC), Contrast, Cold-Spot RC, and left-to-right GMRC ratio. A COV% ≤ 15% and Contrast ≥ 2.2 were set as acceptance criteria. The procedure was repeated to achieve a 6-mm target EIR in a subset of scans. The method’s robustness against typical dose-calibrator-based errors was assessed. The EIR across systems ranged from 3.3 to 8.1 mm, and an EIR of 8 mm was selected as the target resolution. After harmonization, all scans met acceptable image quality criteria, while only 13 (39.4%) did before. The harmonization procedure resulted in lower inter-system variability indicators: Mean ± SD COV% (from 16.97 ± 6.03 to 7.86 ± 1.47%), GMRC Inter-Quartile Range (0.040–0.012), and Contrast SD (0.14–0.05). Similar results were obtained with a 6-mm FWHM target EIR. Errors of ± 10% in the DRO activity resulted in differences below 1 mm in the estimated EIR. Harmonizing the EIR of brain PET scans significantly reduced image quality variability while minimally affecting quantitative accuracy. This method can be used prospectively for harmonizing scans to target sharper resolutions and is robust against dose-calibrator errors. Comparable image quality is attainable in brain PET multi-center studies while maintaining quantitative accuracy.

中文翻译：

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使用霍夫曼体模扫描协调多中心 PET 研究中的脑部 PET 图像

图像协调已被提出，以最大限度地减少多中心研究中获得的大脑 PET 扫描的异质性。然而，缺乏标准的验证方法和软件工具。在此，我们在欧洲多中心临床试验中评估了脑部 PET 扫描协调框架的性能。Hoffman 3D 大脑模型是在 28 个 PET 系统中获取的，并使用特定地点的设置进行重建。每次扫描都会估计有效图像分辨率 (EIR) 的半高全宽 (FWHM) 和协调内核。目标 EIR 被选为成像网络中最粗的 EIR。使用“霍夫曼 3D 大脑分析工具”，计算协调前后的图像质量指标：方差系数 (COV%)、灰质恢复系数 (GMRC)、对比度、冷点 RC 和左到右正确的 GMRC 比率。COV% ≤ 15% 和对比度 ≥ 2.2 被设置为验收标准。重复该过程以在扫描子集中实现 6 毫米目标 EIR。评估了该方法针对典型剂量校准器误差的稳健性。跨系统的 EIR 范围为 3.3 至 8.1 mm，选择 8 mm 的 EIR 作为目标分辨率。协调后，所有扫描都符合可接受的图像质量标准，而之前只有 13 个 (39.4%) 符合。协调程序导致较低的系统间变异性指标：平均值±SD COV%（从16.97±6.03到7.86±1.47%）、GMRC四分位数范围（0.040–0.012）和对比度SD（0.14–0.05）。使用 6 毫米 FWHM 目标 EIR 也获得了类似的结果。DRO 活动中 ± 10% 的误差导致估计 EIR 的差异低于 1 毫米。协调大脑 PET 扫描的 EIR 可以显着降低图像质量变异性，同时将对定量准确性的影响降至最低。该方法可以前瞻性地用于协调扫描以实现更清晰的分辨率，并且对于剂量校准器误差具有鲁棒性。在大脑 PET 多中心研究中可以获得可比较的图像质量，同时保持定量准确性。