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（由申请人提供）：对治疗的脑肿瘤反应的标准临床评估包括检查对比度增强和T2加权信号异常（标准磁共振成像（MRI）扫描）。尽管这些技术提供了有关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。在过去的20年中，许多研究表明，肿瘤细胞侵袭远远超出了传统MRI扫描中检测到的异常范围，而这种侵袭是预后不良和多形胶质细胞瘤（GBM）死亡率100％死亡率的主要原因，是最常见和最常见的和恶性的脑肿瘤类型。因此，该项目的总体目标是建立有价值的临床成像生物标志物FR可视化以及使用扩散MRI技术对脑肿瘤生长和侵袭的定量。我们在初步数据中证明了扩散MRI对肿瘤细胞密度敏感，并且随着时间的推移，扩散MRI的体素变化可用于预测对化疗和抗血管生成疗法的反应。在最近的手稿中，我们开发了一种新型的ADC变化时空模型 水平估计（CIMPLE）图。我们的前提数据表明，CIMPLE映射与MR光谱测量恶性潜力的测量相关，与肿瘤等级相关，可以预测未来对比度增强的区域，可预测用Bevacizumab复发性胶质母细胞瘤患者的存活率，并在空间上与异常相关，与异常的Potitron Potromal Protromal Proticron Ensifectry Aminlo Aminlo酸度及时相关。尽管我们的实验室有希望的初步结果，但在当前建议中的特定实验中概述了更多的测试和改进。特定的目标＃1专注于通过探索高角度分辨率扩散成像（HARDI）的使用来改善高级CIMPLE MAP应用的扩散加权图像采集。该特定目标的成功将使CIMPLE地图通过更高的信号到噪声扩散图像来高精度计算，并为CIMPLE地图创建基于张量的解决方案，以提供可能提供方向特异性的肿瘤侵入地图。具体目标＃2将集中于测试放射治疗期间计算的CIMPLE图是否是肿瘤对标准治疗的反应的早期预测生物标志物。具体而言，我们旨在确定CIMPLE地图是否准确预测了未来肿瘤进展的空间区域，并预测了六个月和十二个月的无进展和整体存活。最后，特定的目标＃3将专注于通过在肿瘤复发和18F-氟胸腺胺正电子发射断层扫描术测量肿瘤增殖时使用组织学信息来验证CIMPLE图。该目标的成功完成将提供其他证据，以验证非侵入性的CIMPLE地图测量结果的增殖和入侵率。 公共卫生相关性：神经肿瘤学社区中有一个普遍的共识，当前监测恶性神经胶质瘤生长和对治疗的反应的方法不足，尤其是在试图检测脑肿瘤侵袭时。该项目旨在进一步建立，验证和在临床上翻译CIMPLE图作为一种非侵入性成像替代物，以定量神经胶质瘤中的肿瘤细胞浸润和增殖。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，该工具将有助于定制药物选择并检测到个别患者的药物衰竭 比传统技术早得多。