Quantitative MRSI for the prediction of response to chemoradiation therapy in GBM

定量 MRSI 用于预测 GBM 放化疗反应

基本信息

批准号：
9016499
负责人：
James Scott Cordova
金额：
$ 1.85万
依托单位：
EMORY UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-03-01 至 2016-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9016499
关键词：
Accounting Adjuvant Aftercare Algorithms Alkylating Agents Architecture Bioinformatics Biological Markers Brain Brain Neoplasms Caliber Cell Death Chemicals Classification Classification Scheme Clinical Clinical Trials Coupling Data Data Analyses Data Set Deterioration Development Diffusion Disease Effectiveness Epigenetic Process Excision Exhibits Future Glioblastoma Goals Health Heterogeneity Histone Deacetylase Inhibitor Human Image Imaging technology Incidence Individual Infiltration Location MRI Scans Magnetic Resonance Imaging Magnetism Malignant - descriptor Maps Measurement Measures Metabolic Metabolism Methods Modeling Molecular Monitor Necrosis Newly Diagnosed Operative Surgical Procedures Outcome Outcome Measure Patient-Focused Outcomes Patients Permeability Pharmaceutical Preparations Physicians Physiological Prediction of Response to Therapy Procedures Process Progression-Free Survivals Property Protocols documentation Radiation Radiation therapy Recurrence Residual Tumors Resolution Sampling Scientist Signal Transduction Spatial Distribution Stable Disease Steroids Technical Expertise Techniques Technology Testing Therapeutic Effect Tissues Training Tumor Debulking Tumor Volume Universities University Hospitals Validation Vorinostat Water Weight Work base blood product cancer imaging career chemoradiation computerized data processing contrast enhanced cytotoxicity density design early experience image guided radiation therapy image guided therapy imaging software indexing interest magnetic resonance spectroscopic imaging neuroimaging personalized management response restoration spectroscopic imaging standard of care targeted treatment temozolomide treatment response tumor tumor progression two-dimensional vector

项目摘要

DESCRIPTION (provided by applicant): The current standard for monitoring glioblastoma multiforme (GBM) progression relies heavily on the changes of enhancing tumor regions on contrast-enhanced, T1-weighted MRI using the Macdonald Criteria (MC). However, the inherent heterogeneity of GBM along with the volume and physiological changes associated with surgical resection make this two-dimensional assessment strategy problematic. Moreover, the addition of temozolomide (TMZ) to radiation therapy significantly increases the incidence of pseudo progression, further complicating response determination. It has become apparent that in the present era of molecularly-targeted therapy, when cytotoxicity may not be the primary therapeutic effect, contrast- enhanced MRI is inadequate for monitoring response and progression. More sophisticated and reliable techniques are desperately needed. Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a promising technique that offers a non-invasive means to differentiate tumor progression from post-treatment changes based on the unique magnetic properties of molecular species within tissues. Furthermore, 1H-MRSI can be used to monitor response to therapies that cause widespread metabolic alterations -like suberoylanilide hydroxamic acid (SAHA), a histone deacetylase inhibitor -if 1H-MRS biomarkers are quantified and standardized. As such, this work proposes to implement state-of-the-art 1H-MRSI technology to generate three-dimensional metabolite maps of the entire brain that can be co-registered with other imaging studies in a clinically useful fashion. By analyzing numerous data sets from clinical trials at Emory University processed in this fashion, 1) a segmentation algorithm for determining tumor volume and intracellular signal density will be developed, and 2) the spatial coherence of 1H-MRS-visible metabolites with standard MR image volumes will be determined. These standardized algorithms will then be used 3) to produce response vectors that will be tested against currently used response criteria and observed clinical outcomes to evaluate their effectiveness in determining tumor response to TMZ, radiation, and SAHA therapy. The intended outcome of this work is to make 1H-MRSI and the associated bioinformatic techniques practical for clinical use and a part of the standard assessment of brain tumor patients. Lastly, the proposed project will serve as a framework for the applicant's training plan, which is specifically designed to integrate basic analytical techniques and tumor imaging technology to assist the applicant in achieving the career goal of becoming a physician-scientist with a focus in image-guided therapy planning for malignant disease.

描述（由申请人提供）：目前监测多形性胶质母细胞瘤（GBM）进展的标准在很大程度上依赖于使用麦克唐纳标准（MC）的对比增强、T1加权MRI上增强肿瘤区域的变化。然而，GBM 固有的异质性以及与手术切除相关的体积和生理变化使得这种二维评估策略存在问题。此外，在放射治疗中添加替莫唑胺（TMZ）会显着增加假性进展的发生率，使反应确定进一步复杂化。很明显，在当今分子靶向治疗时代，当细胞毒性可能不是主要治疗效果时，对比增强 MRI 不足以监测反应和进展。迫切需要更复杂和可靠的技术。质子磁共振波谱成像 (1H-MRSI) 是一种很有前途的技术，它提供了一种非侵入性方法，可以根据组织内分子种类的独特磁性来区分肿瘤进展和治疗后的变化。此外，如果 1H-MRS 生物标志物被量化和标准化，1H-MRSI 可用于监测引起广泛代谢改变的治疗的反应，例如辛二酰苯胺异羟肟酸 (SAHA)，一种组蛋白脱乙酰酶抑制剂。因此，这项工作建议采用最先进的 1H-MRSI 技术来生成整个大脑的三维代谢图，该图可以以临床有用的方式与其他成像研究共同注册。通过分析以这种方式处理的埃默里大学临床试验的大量数据集，1) 将开发一种用于确定肿瘤体积和细胞内信号密度的分割算法，2) 1H-MRS 可见代谢物与标准 MR 图像的空间相干性数量将被确定。然后将使用这些标准化算法 3) 生成响应向量，并根据当前使用的响应标准进行测试并观察临床结果，以评估其在确定肿瘤对 TMZ、放射和 SAHA 治疗的响应方面的有效性。这项工作的预期结果是使 1H-MRSI 和相关生物信息学技术在临床上实用，并成为脑肿瘤患者标准评估的一部分。最后，拟议的项目将作为申请人培训的框架计划，专门设计用于整合基本分析技术和肿瘤成像技术，以帮助申请人实现成为一名专注于恶性疾病的图像引导治疗规划的医师科学家的职业目标。