MRI Evaluation of Tumor Growth and Treatment Response

描述（由申请人提供）：本研究旨在发展和应用磁共振成像（MRI）在理论、临床前和临床层面定量评估肿瘤生长和治疗反应的新方法。特别是，我们建议开发和实施使用动态对比增强MRI （DCE-MRI）定量组织表征的新方法，并将这些测量与来自其他成像方式和MR方法的定量指标相结合。这些方法可以无创地获取肿瘤细胞密度、坏死部分、新生血管和血管内皮完整性等信息——所有这些都被证明是肿瘤生长和治疗反应的有希望的报告。因此，一个主要的目标是开发无创成像生物标志物，可以作为疾病反应的替代品。我们将把其他现有的和新兴的成像方法纳入拟议的DCE-MRI研究；即弥散加权MRI （DW-MRI）、FDG-PET、CT和光学方法，并比较它们单独和组合的相对性能。DW-MRl测量报告组织的细胞结构，并已被证明与良好的治疗反应相关；FDG-PET报告了组织代谢，从而提供了细胞增殖率的信息；CT提供了高分辨率的结构信息，这将有助于MR和PET指数的共同配准；光学成像将用于定位小鼠肿瘤模型中的转移灶。结合DCE-MR1技术提供的功能信息、DW-MRI和CT提供的结构信息以及FDG-PET提供的代谢信息，为评估肿瘤生长和治疗反应提供了强有力的手段。据我们所知，这种肿瘤的定量多参数研究尚未进行。此外，这些研究将利用高场（人类3T；动物9.4T） MRI，提供以前无法获得的更高的信噪比测量。

DESCRIPTION (provided by applicant): The research proposed aims to develop and apply new methods for the quantitative evaluation of tumor growth and treatment response by magnetic resonance imaging (MRI) at the theoretical, pre-clinical, and clinical levels. In particular, we propose to develop and implement novel approaches to quantitative tissue characterization using dynamic contrast enhanced MRI (DCE-MRI), and to integrate these measurements with quantitative metrics derived from other imaging modalities and MR methods. These methods can non-invasively acquire information on, for example, a tumor's cell density, necrotic fraction, neovascularization, and vascular endothelial integrity -- all of which have been shown to be promising reporters on tumor growth and treatment response. Thus, a major goal is to develop noninvasive imaging biomarkers that can serve as surrogates for disease response. We will incorporate other existing and emerging imaging methods into the proposed DCE-MRI studies; namely, diffusion weighted MRI (DW-MRI), FDG-PET, CT, and optical methods, and compare their relative performance separately and in combination. DW-MRl measurements report on a tissue's cellularity and have been shown to correlate with favorable treatment response; FDG-PET reports on tissue metabolism and therefore provides information on cell proliferation rates; CT provides high resolution structural information which will facilitate co-registration of the MR and PET indices; and optical imaging will be employed to locate metastases in a mouse tumor model. Combing the functional information provided by DCE-MR1 techniques, the structural information provided by DW-MRI and CT, and the metabolic information of FDG-PET provides a formidable means of assessing of tumor growth and treatment response. To the best of our knowledge, such quantitative multi-parametric studies of tumors have not yet been performed. Moreover, these studies will make use of high field (3T for humans; 9.4T for animals) MRI which offer higher signal-to-noise ratio measurements not previously obtainable. To realize the goal of developing quantitative, accurate, reproducible, and easily implemented methods to characterize tumor growth and treatment response, we have identified three basic Specific Aims: I) development of appropriate mathematical models to evaluate DCE-MRI data accurately and quantitatively; II) apply and validate these methods in the MMTV-PyVT transgenic mouse model of human breast cancer; III) apply a subset of these methods to evaluate human breast cancer treatment response.