Cell invasion, motility, and proliferation level estimate maps in gliomas

神经胶质瘤中的细胞侵袭、运动和增殖水平估计图

• 批准号: 8283486
• 负责人: Benjamin M. Ellingson
• 金额: $ 20.1万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-17 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8283486
• 关键词: Amino Acids; Animal Model; Area; Biological; Biological Markers; Biopsy; Brain Neoplasms; Cell Density; Cell Proliferation; Cells; Cellularity; Characteristics; Clinical; Clinical assessments; Communities; Consensus; Data; Diffusion; Diffusion Magnetic Resonance Imaging; Diffusion weighted imaging; Employee Strikes; Failure; Functional disorder; Future; Glioblastoma; Glioma; Goals; Growth; Human; Image; Imagery; Imaging Techniques; Individual; Kidney Neoplasms; Laboratories; Literature; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Malignant - descriptor; Malignant Glioma; Mammary Neoplasms; Manuscripts; Maps; Measurement; Methods; Microscopic; Modeling; Monitor; Newly Diagnosed; Noise; Paper; Patients; Pharmaceutical Preparations; Positron-Emission Tomography; Publishing; Radiation therapy; Recurrence; Relative (related person); Reporting; Resolution; Signal Transduction; Skin Neoplasms; Solutions; Stroke; Swelling; Techniques; Testing; Thymidine; Time; Tissues; Translating; Translations; Tumor Cell Invasion; Validation; Weight; base; bevacizumab; cell motility; chemotherapy; density; improved; in vivo; molecular imaging; neoplastic cell; neuro-oncology; novel; outcome forecast; research study; response; spatiotemporal; success; temozolomide; tool; tumor; tumor growth; tumor progression; uptake; water diffusion

DESCRIPTION (provided by applicant): Standard clinical assessment of brain tumor response to treatment consists of examining contrast enhancement and T2-weighted signal abnormalities on standard magnetic resonance imaging (MRI) scans. While these techniques provide important information regarding tumor pathophysiology, they do not enable direct visualization of tumor growth and invasion. Numerous studies over the past 20 years have shown that tumor cell invasion extends well beyond the margins of abnormalities detected on traditional MRI scans, and this invasion is the primary reason for poor prognosis and 100% fatality rate in glioblastoma multiforme (GBM), the most common and malignant type of brain tumor. Therefore, the overall goal of this project is to establish a valuable clinical imaging biomarker fr visualization and quantification of brain tumor growth and invasion using diffusion MRI techniques. We have demonstrated in our preliminary data that diffusion MRI is sensitive to tumor cell density, and voxel-wise changes in diffusion MRI over time can be used to predict the response to both chemotherapy and anti-angiogenic therapies. In a recent manuscript, we have developed a novel spatiotemporal model of ADC change aimed at quantifying voxel-wise microscopic proliferation and cell invasion rates termed Cell Invasion, Motility, and Proliferation Level Estimate (CIMPLE) maps. Our preliminary data suggests CIMPLE maps correlate with MR spectroscopy measurements of malignant potential, correlate with tumor grade, may predict regions of future contrast enhancement, predict survival in patients with recurrent glioblastoma treated with bevacizumab, and spatially correlates well with abnormal positron emission tomography measurements of amino acid uptake. Despite promising preliminary results from our laboratory, more testing and improvements are necessary as outlined in the specific experiments in the current proposal. Specific Aim #1 focuses on improving the diffusion-weighted image acquisition for advanced CIMPLE map applications by exploring the use of high angular resolution diffusion imaging (HARDI). Success of this specific aim will allow CIMPLE maps to be calculated with high accuracy through higher signal-to-noise diffusion images as well as create a tensor-based solution to CIMPLE maps that may provide directionally-specific maps of tumor invasion. Specific Aim #2 will focus on testing whether CIMPLE maps calculated during radiotherapy are early predictive biomarkers of tumor response to standard therapy. Specifically, we aim to determine whether CIMPLE maps accurately predict spatial regions of future tumor progression as well as predict six- and twelve-month progression-free and overall survival. Lastly, Specific Aim #3 will focus on validating CIMPLE maps through the use of histological information at tumor recurrence and 18F-fluoro-thymidine positron emission tomography measurements of tumor proliferation. Successful completion of this aim will provide additional evidence validating non-invasive CIMPLE map measurements of proliferation and invasion rate. PUBLIC HEALTH RELEVANCE: There is a general consensus in the neuro-oncology community that current methods of monitoring malignant glioma growth and response to treatment are inadequate, particularly when trying to detect brain tumor invasion. This project aims to further establish, validate, and clinically translate CIMPLE maps as a non-invasive imaging surrogate for quantification of tumor cell invasion and proliferation in gliomas. Successful completion of this project will help establish CIMPLE maps as a personalized clinical monitoring tool that will help tailor drug selection and detect drug failure in individual patients much sooner than conventional techniques.

描述（由申请方提供）：脑肿瘤治疗反应的标准临床评估包括检查标准磁共振成像（MRI）扫描的对比度增强和T2加权信号异常。虽然这些技术提供了关于肿瘤病理生理学的重要信息，但它们不能直接可视化肿瘤生长和侵袭。过去20年的大量研究表明，肿瘤细胞的侵袭远远超出了传统MRI扫描检测到的异常边缘，这种侵袭是多形性胶质母细胞瘤（GBM）预后不良和100%死亡率的主要原因，GBM是最常见和恶性的脑肿瘤类型。因此，本项目的总体目标是建立一种有价值的临床成像生物标志物，用于使用扩散MRI技术可视化和定量脑肿瘤生长和侵袭。我们已经在我们的初步数据中证明，扩散MRI对肿瘤细胞密度敏感，并且扩散MRI随时间的体素变化可用于预测对化疗和抗血管生成治疗的反应。在最近的一份手稿中，我们开发了一种新的ADC变化时空模型，旨在量化体素微观增殖和细胞侵袭率，称为细胞侵袭，运动和增殖 水平估计（CIMPLE）图。我们的初步数据表明，CIMPLE图与MR波谱测量的恶性潜能相关，与肿瘤分级相关，可以预测未来的对比度增强区域，预测贝伐单抗治疗复发性胶质母细胞瘤患者的生存率，并与异常正电子发射断层扫描测量的氨基酸摄取空间相关。尽管我们实验室的初步结果令人鼓舞，但正如当前提案中的具体实验所概述的那样，还需要进行更多的测试和改进。具体目标#1侧重于通过探索高角分辨率扩散成像（HARDI）的使用来改善高级CIMPLE标测应用的扩散加权图像采集。这一特定目标的成功将允许通过更高的信噪比扩散图像以高精度计算CIMPLE图，并创建CIMPLE图的基于张量的解决方案，该解决方案可以提供肿瘤侵袭的方向特异性图。具体目标#2将集中于测试在放射治疗期间计算的CIMPLE图是否是肿瘤对标准疗法的反应的早期预测生物标志物。具体来说，我们的目标是确定CIMPLE地图是否准确地预测未来肿瘤进展的空间区域，以及预测6个月和12个月的无进展生存期和总生存期。最后，具体目标#3将侧重于通过使用肿瘤复发时的组织学信息和肿瘤增殖的18 F-氟胸苷正电子发射断层扫描测量来验证CIMPLE图。这一目标的成功完成将提供额外的证据，验证非侵入性CIMPLE地图测量的增殖和侵袭率。 公共卫生相关性：神经肿瘤学界普遍认为，目前监测恶性胶质瘤生长和治疗反应的方法是不够的，特别是在试图检测脑肿瘤侵袭时。该项目旨在进一步建立，验证和临床翻译CIMPLE地图作为一种非侵入性的成像替代定量肿瘤细胞的侵袭和增殖胶质瘤。该项目的成功完成将有助于建立CIMPLE地图作为个性化的临床监测工具，这将有助于定制药物选择和检测个体患者的药物失败 比传统技术快得多。