Schadt Fabian, Israel Ina, Samnick Samuel
Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany.
Front Neuroinform. 2021 Jun 8;15:639643. doi: 10.3389/fninf.2021.639643. eCollection 2021.
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 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.
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-[F]fluoro-2-deoxyglucose ([F]FDG), a metabolic tracer with symmetrical distribution in brain, and [Ga]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.
Using ischemic stroke data in Wistar rats as an example, the statistical analysis of the tool should be demonstrated. In this [F]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.
Our NU_DPA tool allows a very flexible data evaluation of small animal PET data including statistical data evaluation. Using the radiotracers [F]FDG and [Ga]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.
在正电子发射断层扫描（PET）成像中，不同类型的放射性示踪剂和积聚情况，以及疾病模式的多样性，使得对所获取的分子成像数据进行分析具有挑战性。在此，我们评估并验证一种基于磁共振成像（MRI）模板的半自动数据分析工具，该工具可使临床前PET图像与自行创建的PET模板对齐。然后，基于用户定义的感兴趣体积（VOI），可以使用三种不同的半定量参数对图像数据进行评估：归一化活性、标准化摄取值和摄取率。
核医学数据处理分析工具（NU_DPA）在Matlab中实现。使用两种放射性示踪剂在大鼠模型的不同类型与中风相关的脑部疾病中对该工具进行测试和验证。所使用的放射性示踪剂为2-[F]氟-2-脱氧葡萄糖（[F]FDG），一种在脑中分布对称的代谢示踪剂，以及[Ga]镓-岩藻聚糖，一种特异性结合p-选择素的靶向选择性放射性配体。手动导入图像后，NU_DPA工具会根据所获取的PET图像自动创建一个平均PET模板，然后将所有PET图像与之对齐。添加的基于MRI模板的信息，调整大小以适应较低的PET分辨率，定义了VOI，还允许将VOI精确细分为各个子区域。然后可以对MRI图谱中定义的所有区域的对齐PET图像进行半定量评估。此外，可以在NU_DPA工具中对这些半定量参数进行统计分析和评估。
以Wistar大鼠的缺血性中风数据为例，展示该工具的统计分析。在这个[F]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。由此，使用NU_DPA工具进行的统计数据评估表明，光血栓形成病变中的葡萄糖代谢会受到电刺激的影响。
我们的NU_DPA工具允许对小动物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[F]FDG和[Ga]镓-岩藻聚糖表明，基于MRI模板的NU_DPA工具半自动数据分析对于代谢放射性示踪剂以及靶向选择性放射性示踪剂都可能适用。
