Aim: In PET imaging, the different types of radiotracers and accumulations, as well as the diversity of disease patterns, make the analysis of molecular imaging data acquired in vivo challenging. Here, we evaluate and validate a semi-automated MRI template-based data analysis tool that allows preclinical PET images to be aligned to a self-created PET template. Based on the user-defined volume-of-interest (VOI), image data can then be evaluated using three different semi-quantitative parameters: normalized activity, standardized uptake value, and uptake ratio. Materials and methods: The nuclear medicine Data Processing Analysis tool (NU_DPA) was implemented in Matlab. Testing and validation of the tool was performed using two types of radiotracers in different kinds of stroke-related brain diseases in rat models. The radiotracers used are 2-[18F]fluoro-2-deoxyglucose ([18F]FDG), a metabolic tracer with symmetrical distribution in brain, and [68Ga]Ga-Fucoidan, a target-selective radioligand specifically binding to p-selectin. After manual image import, the NU_DPA tool automatically creates an averaged PET template out of the acquired PET images, to which all PET images are then aligned onto. The added MRI template-based information, resized to the lower PET resolution, defines the VOI and also allows a precise subdivision of the VOI into individual sub-regions. The aligned PET images can then be evaluated semi-quantitatively for all regions defined in the MRI atlas. In addition, a statistical analysis and evaluation of the semi-quantitative parameters can then be performed in the NU_DPA tool. Results: Using ischemic stroke data in Wistar rats as an example, the statistical analysis of the tool should be demonstrated. In this [18F]FDG-PET experiment, three different experimental states were compared: healthy control state, ischemic stroke without electrical stimulation, ischemic stroke with electrical stimulation. Thereby, statistical data evaluation using the NU_DPA tool showed that the glucose metabolism in a photothrombotic lesion can be influenced by electrical stimulation. Conclusion: Our NU_DPA tool allows a very flexible data evaluation of small animal PET data in vivo including statistical data evaluation. Using the radiotracers [18F]FDG and [68Ga]Ga-Fucoidan, it was shown that the semi-automatic MRI-template based data analysis of the NU_DPA tool is potentially suitable for both metabolic radiotracers as well as target-selective radiotracers.

中文翻译：

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开发和验证啮齿动物半自动、临床前、基于 MRI 模板的 PET 图像数据分析工具


目的：在 PET 成像中，不同类型的放射性示踪剂和累积物以及疾病模式的多样性使得对体内获得的分子成像数据的分析具有挑战性。在这里，我们评估和验证基于半自动 MRI 模板的数据分析工具，该工具允许临床前 PET 图像与自行创建的 PET 模板对齐。基于用户定义的感兴趣体积 (VOI)，然后可以使用三种不同的半定量参数来评估图像数据：标准化活动、标准化摄取值和摄取比率。材料和方法：核医学数据处理分析工具（NU_DPA）在Matlab中实现。使用两种类型的放射性示踪剂在不同类型的中风相关脑部疾病的大鼠模型中对该工具进行了测试和验证。使用的放射性示踪剂是2-[18F]氟-2-脱氧葡萄糖（[18F]FDG）（一种在大脑中对称分布的代谢示踪剂）和[68Ga]Ga-岩藻依聚糖（一种与p-选择素特异性结合的靶选择性放射性配体）。手动图像导入后，NU_DPA 工具会自动根据采集的 PET 图像创建平均 PET 模板，然后将所有 PET 图像对齐到该模板上。添加的基于 MRI 模板的信息调整为较低的 PET 分辨率，定义了 VOI，并且还允许将 VOI 精确细分为各个子区域。然后可以对 MRI 图集中定义的所有区域进行半定量评估对齐的 PET 图像。此外，还可以在 NU_DPA 工具中对半定量参数进行统计分析和评估。结果：以 Wistar 大鼠的缺血性中风数据为例，应该证明该工具的统计分析。 在这个[18F]FDG-PET实验中，比较了三种不同的实验状态：健康对照状态、无电刺激的缺血性中风、有电刺激的缺血性中风。因此，使用 NU_DPA 工具的统计数据评估表明，光血栓病变中的葡萄糖代谢可能受到电刺激的影响。结论：我们的 NU_DPA 工具可以对小动物体内 PET 数据进行非常灵活的数据评估，包括统计数据评估。使用放射性示踪剂 [18F]FDG 和 [68Ga]Ga-岩藻依聚糖，结果表明，基于 NU_DPA 工具的半自动 MRI 模板数据分析可能适用于代谢放射性示踪剂以及目标选择性放射性示踪剂。