MRI Evaluation of Tumor Growth and Treatment Response

描述(申请人提供)：提出的研究旨在开发和应用新的方法，通过磁共振成像(MRI)在理论、临床前和临床水平对肿瘤生长和治疗反应进行定量评估。特别是，我们建议开发和实施使用动态对比增强MRI(DCE-MRI)的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方法的定量度量相结合。这些方法可以非侵入性地获取信息，例如，肿瘤的细胞密度、坏死率、新生血管和血管内皮完整性--所有这些都被证明是关于肿瘤生长和治疗反应的有希望的记者。因此，一个主要的目标是开发非侵入性成像生物标记物，作为疾病反应的替代品。我们将在拟议的DCE-MRI研究中加入其他现有和新兴的成像方法，即扩散加权MRI(DW-MRI)、FDG-PET、CT和光学方法，并分别和组合比较它们的相对性能。DW-MRL测量报告组织的细胞性，已被证明与有利的治疗反应相关；FDG-PET报告组织代谢，因此提供关于细胞增殖率的信息；CT提供高分辨率结构信息，这将有助于MR和PET指数的共同配准；光学成像将被用于定位小鼠肿瘤模型中的转移。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的代谢信息，为评估肿瘤的生长和治疗反应提供了强大的手段。就我们所知，这种对肿瘤的定量多参数研究还没有进行过。此外，这些研究将利用高场磁共振(人类为3T，动物为9.4T)，提供以前无法获得的更高的信噪比测量。 为了实现开发定量、准确、可重复性和易于实施的方法来表征肿瘤生长和治疗反应的目标，我们确定了三个基本的具体目标：i)开发合适的数学模型来准确和定量地评估DCE-MRI数据；ii)在MMTV-PyVT转基因小鼠乳腺癌模型中应用和验证这些方法；iii)应用这些方法的子集来评估人类乳腺癌的治疗反应。

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.