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

基本信息

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
项目类别：
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

项目摘要

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）：脑肿瘤对治疗反应的标准临床评估包括检查标准磁共振成像（MRI）扫描上的对比增强和 T2 加权信号异常。虽然这些技术提供了有关肿瘤病理生理学的重要信息，但它们无法直接可视化肿瘤生长和侵袭。过去20年的大量研究表明，肿瘤细胞侵袭远远超出了传统MRI扫描检测到的异常范围，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。常见且恶性的脑肿瘤。因此，该项目的总体目标是利用扩散MRI技术建立一种有价值的临床成像生物标志物，用于脑肿瘤生长和侵袭的可视化和量化。我们在初步数据中证明，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，我们开发了一种新颖的 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、运动和增殖级别估计 (CIMPLE) 地图。我们的初步数据表明，CIMPLE 图与恶性潜能的 MR 波谱测量相关，与肿瘤分级相关，可以预测未来对比度增强的区域，预测接受贝伐单抗治疗的复发性胶质母细胞瘤患者的生存率，并且与异常正电子发射断层扫描测量的空间相关性良好氨基酸的摄取。尽管我们实验室的初步结果很有希望，但仍需要进行更多测试和改进，如当前提案中的具体实验所述。具体目标#1 侧重于通过探索高角分辨率扩散成像 (HARDI) 的使用来改进高级 CIMPLE 地图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信噪比的扩散图像高精度地计算 CIMPLE 图，并为 CIMPLE 图创建基于张量的解决方案，该解决方案可以提供肿瘤侵袭的定向特异性图。具体目标#2 将重点测试放疗期间计算的 CIMPLE 图是否是肿瘤对标准治疗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 图是否准确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 将重点通过使用肿瘤复发的组织学信息和肿瘤增殖的 18F-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为验证非侵入性 CIMPLE 图测量增殖和侵袭率提供额外的证据。公共健康相关性：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不足，特别是在试图检测脑肿瘤侵袭时。该项目旨在进一步建立、验证和临床转化 CIMPLE 图谱，作为量化胶质瘤中肿瘤细胞侵袭和增殖的非侵入性成像替代品。该项目的成功完成将有助于建立 CIMPLE 图作为个性化临床监测工具，有助于定制药物选择并检测个体患者的药物失败比传统技术快得多。