Quantitative imaging tools to derive DW-MRI oncological biomarkers

摘要： 我们建议开发、优化和验证新型DW-MRI采集和建模方法， 通过扩散峰度成像和非高斯成像解决非高斯水扩散和灌注效应， 高斯体素内非相干运动成像，并提供组织结构和 生物学此外，我们还将开发和实施先进的图像处理工具，以最大限度地提高生物成像质量。 来自由成像数据提供的肿瘤/组织的信息。我们及时提出的建议的精髓在于 作为第一个多中心，成像试验，以确定定量成像生物标志物作为早期反应， 治疗指标，根据NCI的中心使命询问肿瘤生物学 定量成像网络。它将解决临床试验中复发性/转移性 （R/M）头颈部癌症。本UO 1提案是对PAR-14-116和所概述的具体目标的回应 目标1：开发和标准化多b值缩减视场（rFOV） DW-MRI采集方法和用于肿瘤学应用的非单指数建模DW-MRI;目标2： 开发和实施具有先进图像分割和图像特征的优化模型方法 HN地区R/M恶性肿瘤患者的肿瘤学应用分析;目标3：建立 下一代DW-MRI生物标志物作为实验性治疗中的早期治疗反应指标 使用R/M HN鳞状细胞癌（SCC）作为原理模型的证明。我们假设成像 从较新的方法得到的度量可以用作定量成像生物标志物，用于评估早期 在R/M HNSCC中的治疗功效。识别稳健、可靠和定量成像的原则 从DW-MRI和图像特征分析得到的生物标志物保持相似，并且这样的成像方案， 适当的改编，可以有更广泛的临床应用，包括它们在治疗其他实体肿瘤中的用途。

Abstract: We propose to develop, optimize and validate novel DW-MRI acquisition and modeling methods, which address non-Gaussian water diffusion and perfusion effects through diffusion kurtosis imaging and non- Gaussian intravoxel incoherent motion imaging and provide more specific measures of tissue structure and biology. Additionally, we will develop and implement advanced image processing tools to maximize the biologic information from the tumor/tissue provided by the imaging data. The essence of our timely proposal lies in it being the first multi-center, imaging trial to identify quantitative imaging biomarkers as early response to therapy indicators, which interrogate tumor biology in accordance with the central mission of the NCI Quantitative Imaging Network. It will address an urgent, unmet need in clinical trials for recurrent/metastatic (R/M) head and neck cancers. This UO1 proposal is in response to PAR-14-116 and the specific aims outlined in the proposal are as follows: Aim 1: To develop and standardize a multi b-value reduced field of view (rFOV) DW-MRI acquisition method and non-mono exponential modeling DW-MRI for oncology applications; Aim 2: To develop and implement optimal model methodology with advanced image segmentation and image feature analysis in patients with R/M malignancies in the HN region for oncology applications; and Aim 3: To establish the next generation DW-MRI biomarkers as early response to therapy indicators in experimental therapies using R/M HN squamous cell carcinoma (SCC) as a proof of principle model. We hypothesize that imaging metrics derived from newer methods can be used as quantitative imaging biomarkers for assessing early therapeutic efficacy in R/M HNSCC. The principles of identifying robust, reliable and quantitative imaging biomarkers derived from DW-MRI and image feature analysis remain similar and such imaging protocols, after appropriate adaptation, can have a wider clinical application, including their use in treating other solid tumors.