Quantitative FDG-PET for Hepatomacellular Carcinoma

描述(由申请人提供)： 这项研究是一项更大的长期努力的一部分，目的是帮助开发基于体内多模式成像的放射干预措施，主要是定量PET成像，用于癌症诊断和治疗。这些影像引导的介入手术包括活检、微创药物输送和肿瘤消融术。目前，使用[18F]-氟代脱氧葡萄糖(FDG)进行肿瘤检测的PET成像并没有充分发挥其临床潜力。因此，我们的研究项目解决了PET测量的示踪剂转运速率参数(在该项目中用于FDG)与组织病理学评估的癌症预后因素之间的相关性。这些癌症预后因素包括病理类型和分级、增殖率、P53表达等。它们对患者的分类更有用，对治疗决策更关键，对早期评估介入治疗的结果更重要，因为它们提供了细胞水平的信息和癌症的微环境。我们的初步目标是建立肝细胞癌的土拨鼠模型，用于FDG-PET的定量成像。通过多模式成像，我们将使PET、CT和组织学的图像保持一致。利用功能分析，我们将把FDG转运参数与癌症预后因素联系起来。我们已经组建了一支强大的研究团队，拥有所需的专业知识，以实现我们的目标，即BRG项目。我们希望，如果这种相关性得到确立，将导致更成功的癌症预后和治疗效果的早期预测，从而对患者管理产生巨大影响。这项研究开发的方法论可以应用于其他示踪剂，并用于其他具体问题的研究。

DESCRIPTION (provided by applicant): This research is part of a larger, long-term effort to aid the development of radiological interventions based on in vivo multimodal imaging, mainly quantitative PET imaging, for cancer diagnosis and treatment. These image-guided interventional procedures include biopsy, minimally invasive drug delivery and tumor ablation. Currently, PET imaging using [18F]-fluorodeoxyglucose (FDG) for tumor-detection does not utilize its full clinical potential. Accordingly, our research project addresses the correlation between PET measured tracer transport rate parameters (for FDG in this project) and histopathologically evaluated cancer prognostic factors. These cancer prognostic factors include pathologic type and grade, proliferation rate, p53 expression, etc. They are more useful for patient categorization, more crucial for treatment decisions, and more important for early assessment of the outcome of interventional procedures because they provide cellular level information as well as the microenvironment of the cancer. Our initial objective is to establish the woodchuck model of Hepatocellular Carcinoma (HCC) for quantitative FDG-PET imaging. Through multimodal imaging, we will align images from PET, CT and histology. Using functional analysis, we will correlate FDG transport parameters with cancer prognostic factors. We have assembled a strong research team with the needed expertise to accomplish our goal this BRG project. We hope that such correlation, if established, will lead to more successful cancer prognosis and early prediction of treatment efficacy and will thus have a huge impact on patient management. The methodology developed in this research can be applied to other tracers and used for other problem-specific research.