Papadimitroulas P, Loudos G, Le Maitre A, Efthimiou N, Visvikis D, Nikiforidis G, Kagadis G C
University of Patras, Rion, Ahaia.
Technical educational Institute of Athens, Athens, Attiki.
Med Phys. 2012 Jun;39(6Part5):3645. doi: 10.1118/1.4734805.
In the present study a patient-specific dataset of realistic PET simulations was created, taking into account the variability of clinical oncology data. Tumor variability was tested in the simulated results. A comparison of the produced simulated data was performed to clinical PET/CT data, for the validation and the evaluation of the procedure.
Clinical PET/CT data of oncology patients were used as the basis of the simulated variability inserting patient-specific characteristics in the NCAT and the Zubal anthropomorphic phantoms. GATE Monte Carlo toolkit was used for simulating a commercial PET scanner. The standard computational anthropomorphic phantoms were adapted to the CT data (organ shapes), using a fitting algorithm. The activity map was derived from PET images. Patient tumors were segmented and inserted in the phantom, using different activity distributions.
The produced simulated data were reconstructed using the STIR opensource software and compared to the original clinical ones. The accuracy of the procedure was tested in four different oncology cases. Each pathological situation was illustrated simulating a) a healthy body, b) insertion of the clinical tumor with homogenous activity, and c) insertion of the clinical tumor with variable activity (voxel-by-voxel) based on the clinical PET data. The accuracy of the presented dataset was compared to the original PET/CT data. Partial Volume Correction (PVC) was also applied in the simulated data.
In this study patient-specific characteristics were used in computational anthropomorphic models for simulating realistic pathological patients. Voxel-by-voxel activity distribution with PVC within the tumor gives the most accurate results. Radiotherapy applications can utilize the benefits of the accurate realistic imaging simulations, using the anatomicaland biological information of each patient. Further work will incorporate the development of analytical anthropomorphic models with motion and cardiac correction, combined with pathological patients to achieve high accuracy in tumor imaging. This research was supported by the Joint Research and Technology Program between Greece and France; 2009-2011 (protocol ID: 09FR103).
在本研究中，创建了一个考虑临床肿瘤学数据变异性的患者特异性真实PET模拟数据集。在模拟结果中测试了肿瘤变异性。将生成的模拟数据与临床PET/CT数据进行比较，以验证和评估该程序。
将肿瘤患者的临床PET/CT数据作为模拟变异性的基础，在NCAT和祖巴尔人体模型中插入患者特异性特征。使用GATE蒙特卡罗工具包模拟商用PET扫描仪。使用拟合算法将标准计算人体模型调整为适应CT数据（器官形状）。活性图源自PET图像。使用不同的活性分布对患者肿瘤进行分割并插入到模型中。
使用STIR开源软件重建生成的模拟数据，并与原始临床数据进行比较。在四个不同的肿瘤病例中测试了该程序的准确性。通过模拟a）健康身体、b）具有均匀活性的临床肿瘤插入以及c）基于临床PET数据具有可变活性（逐体素）的临床肿瘤插入来说明每种病理情况。将所呈现数据集的准确性与原始PET/CT数据进行比较。还对模拟数据应用了部分容积校正（PVC）。
在本研究中，在计算人体模型中使用患者特异性特征来模拟真实的病理患者。肿瘤内具有PVC的逐体素活性分布给出了最准确的结果。放射治疗应用可以利用精确真实成像模拟的优势，利用每个患者的解剖和生物学信息。进一步的工作将包括开发具有运动和心脏校正的分析人体模型，并结合病理患者以在肿瘤成像中实现高精度。本研究得到了希腊和法国联合研究与技术计划的支持；2009 - 2011年（协议编号：09FR103）。
