ADVANCED MR FOR PROBING TUMOR MICROENVIRONMENT

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 该项目是一项广泛的努力，以提高我们监测肿瘤微环境的能力。 有三个子项目。 首先，众所周知，实体瘤中的缺氧甚至缺氧区域可能限制非手术治疗的疗效，包括放射治疗、光动力治疗、化学治疗。在肿瘤生长的各个阶段和对干预/治疗的响应中对肿瘤氧合的准确评估可以提供对肿瘤发展的更好理解，并且可以作为治疗结果的预后指标，可能允许个体化癌症治疗。我们最近确定了一个1H MRI探针pO 2：六甲基二硅氧烷（HMDSO）。PI开发了一种新的基于HMDSO的定量MR血氧测定技术PISTOL（用于绘制组织氧合水平的硅烷质子成像），用于绘制组织间质pO 2。本项目已将该技术应用于肿瘤微血管反应的研究。第一个子项目的目标是优化基于HMDSO的纳米乳剂的合成和表征，作为基于1H MRI的oximentry的pO 2纳米探针（资金来源1），并使用它们研究肿瘤对联合化疗的反应。第二个子项目（资金来源2）的目标是研究高压氧与pO 2纳米探针癌症pO 2敏感光动力疗法相结合的反应。 在技术发展的另一个领域，三维化学位移成像（3D-CSI）是一种基于MR的非侵入性方法，用于临床量化和监测这些代谢物。3D-CSI的常规临床使用中的主要障碍是较长的采集时间，因此患者在扫描仪中花费的时间较长。因此，迫切需要解决这个问题，以使临床医生能够常规使用这种强大的技术。该项目旨在通过使用压缩传感来克服这一限制，这在过去几年中已经成为一项革命性的发明。该技术已成功应用于MRI，有望成为减少MRI扫描采集时间的新途径。我们计划对脑和乳腺CSI数据集进行回顾性分析，以便将使用传统k空间重建方法获得的代谢物图谱与使用欠采样数据进行的基于压缩感知的重建进行比较。我们假设，通过利用k空间的稀疏性以及频谱数据，我们可能能够将患者的CSI扫描时间减少2倍，而不会显着降低数据质量。 第三个研究领域涉及乳腺癌的造影剂。 小分子造影剂对乳腺癌检测具有高灵敏度，但对检测到的病变的表征具有有限的特异性。使用大分子（大分子）造影剂的类似方法可以提供这种组织分化，但灵敏度较低。不能同时使用这两种药剂，因为无法区分两者的效果。一类新的造影剂，称为PARACEST剂，最近已被提出用于MRI应用，并迫切需要在体内进行评估，因为理论上预测的灵敏度，这些代理商是高于传统的Gd为基础的代理。这些试剂还具有使用射频脉冲随意开启图像对比度的优点。我们计划研究这种大分子PARACEST试剂白蛋白-EuDOTA-4Am-（Gly）2（OBz-Ser）2在大鼠肿瘤中的动力学，随后施用常规小分子造影剂Gd-DTPA。这两种试剂使用不同的机制影响图像对比度，因此在Gd-DTPA之前给予PARACEST试剂不会影响随后的Gd-DTPA对比度。本课题的具体目标是：1）优化PARACEST成像序列和对比度参数。2)研究肌肉组织和肿瘤中动态PARACEST对比增强（DPCE）动力学，并建立动力学模型。3)使用DPCE动力学研究两种肿瘤细胞系对抗血管生成治疗的反应。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. This project is a broad effort to improve our ability to monitor the microenvironment of a tumor. There are three sub-projects. First, It is well-known that hypoxic or even anoxic regions in solid-growing tumors may limit the efficacy of non-surgical therapy, including radiotherapy, photodynamic therapy, chemotherapy. Accurate assessment of tumor oxygenation at various stages of tumor growth and in response to interventions/therapy may provide a better understanding of tumor development and may serve as a prognostic indicator for treatment outcome, potentially allowing individualized cancer therapy. We have recently identified a 1H MRI probe of pO2: hexamethyldisiloxane (HMDSO). The PI has developed a new, HMDSO-based quantitative MR oximetry technique PISTOL (Proton Imaging of Silanes to Map Tissue Oxygenation Levels) for mapping of tissue interstitial pO2. This technique has been applied to study the tumor microenvironmenental response to therapy in this project. The goal of the first subproject is to optimize synthesis and characterization of HMDSO based nanoemulsions as pO2 nanoprobes (funding source 1) for 1H MRI based oximentry and uses them to study tumor response to combination chemotherapy. The goal of the second subproject (funding source 2) is to study the response of combining hyperbaric oxygen with pO2-sensitive photodynamic therapy of cancer with pO2 nanoprobes. In another area of technology development, three dimensional Chemical Shift Imaging (3D-CSI) is an MR-based non-invasive approach used in the clinic to quantify and monitor these metabolites. A major hurdle in routine clinical use of 3D-CSI is the long acquisition time and hence the time spent by the patient in the scanner. Therefore a strong need to address this problem exists to enable clinicians to make routine use of this powerful technology. The proposed project aims to overcome this limitation by the use of compressive sensing, which has been a revolutionary invention in the past few years. This technique has been successfully implemented for MRI and promises to be a new path for reducing acquisition times for MRI scans. We plan to conduct a retrospective analysis of brain and breast CSI data sets in order to compare metabolite maps obtained with conventional k-space reconstruction method to compressive sensing based reconstruction using undersampled data. We hypothesize that by exploiting the sparsity of k-space as well as the spectral data, we may be able to reduce CSI scan times for patients by a factor of 2 without significant reduction in the quality of data. A third area of investigation involves contrast agents for breast cancer. Small molecular contrast agents have a high sensitivity for breast cancer detection but a limited specificity for the characterization of the detected lesions. A similar approach, which uses large molecular (macromolecular) contrast agents, can provide this tissue differentiation but the sensitivity is low. One cannot use these two types of agents together as it would be impossible to distinguish between effects of the two. A novel class of contrast agents, called PARACEST agents, have been recently proposed for MRI applications and need to be urgently evaluated in vivo as the theoretically predicted sensitivity of these agents is higher than conventional Gd-based agents. These agents also have the advantage of having image contrast turned on at will using radio-frequency pulses. We planned to study the kinetics of such a macromolecular PARACEST agent albumin-EuDOTA-4Am-(Gly)2(OBz-Ser)2 in rat tumors and subsequently administer a conventional small molecular contrast agent Gd-DTPA. These two agents affect the image contrast using different mechanisms and hence administering the PARACEST agent before Gd-DTPA will not affect the subsequent Gd-DTPA contrast. Specific aims of this project are: 1) Optimization of PARACEST imaging sequence and contrast parameters. 2) Study dynamic PARACEST contrast enhancement (DPCE) kinetics in muscle tissue and tumors and develop kinetic model. 3) Use DPCE kinetics to study response to antiangiogenic therapy in two tumor lines.