MR Metabolic Markers for Evaluation of Patients with Recurrent Glioma

描述（由申请人提供）：本研究的目标是开发强大的工具来获取和分析复发性胶质瘤患者的体内MR代谢数据，这些数据将与最先进的MR成像方法相结合，为连续监测治疗反应提供改进的指标。这解决了一个重要的临床问题，它混淆了对新疗法的评估，并使对患者护理做出明智的决定变得困难。对于高级别胶质瘤患者，肿瘤复发引起的形态学改变与胶质瘤、水肿等治疗效果之间存在歧义。根据该R01当前周期的结果，对确定肿瘤复发的真实程度感兴趣的代谢产物是肌醇（myo-I）、n -乙酰天冬氨酸（NAA）、肌酸（Cr）和胆碱（Cho）。对于最初诊断为低级别胶质瘤的受试者，其病变的大小正在增加，关键问题是确定他们何时经历了向更恶性表型的转变，需要积极的治疗。从我们对组织样本的离体分析中，本病例中感兴趣的其他代谢物是myo-I，谷氨酸，谷氨酰胺，甘氨酸，谷胱甘肽和2-羟基戊二酸（2HG）。在具体目标1和2中，我们将优化并评估自动短TE 3D mri的测试-重测精度，以及单体素光谱编辑和2- d COSY序列，这些序列将用于检测具有复杂耦合模式和重叠共振的体内代谢物水平。这将对3T和7T扫描仪进行，以确定哪种方法和场强将为患者研究提供最明确的结果。在Specific Aim 3中，我们将对复发性低级别胶质瘤患者应用优化的2HG检测方法，以确定与进展时间和总生存期相关的代谢参数。在Specific Aim 4中，我们将对复发性高级别胶质瘤患者进行分析，使用最可靠的策略获得短期TE 3D MRSI数据。这项研究的结果将为评估对治疗的反应和选择替代治疗提供新的指标。

DESCRIPTION (provided by applicant): The goal of this study is to develop robust tools for acquiring and analyzing in vivo MR metabolic data in patients with recurrent glioma that will be integrated with state of the art MR imaging methods to provide improved metrics for serially monitoring response to therapy. This addresses an important clinical problem, which is confounding the evaluation of novel treatments and making it difficult to make informed decisions about patient care. For subjects with high grade glioma, there is ambiguity between morphological changes that are caused by recurrent tumor and treatment effects such as gliosis and edema. Based on results from the current cycle of this R01, metabolites of interest for mapping out the true extent of recurrent tumor are myo-inositol (myo-I), N-acetylasparate (NAA), creatine (Cr) and choline (Cho). For subjects with an original diagnosis of low grade glioma who have a lesion which is increasing in size, the critical issue is to determine when they have undergone transformation to a more malignant phenotype that requires aggressive therapy. From our ex vivo analysis of tissue samples, additional metabolites of interest in this case are myo-I, glutamate, glutamine, glycine, glutathione and 2-hydroxyglutarate (2HG). In Specific Aims 1 and 2 we will optimize and then evaluate the test-retest accuracies of automated short TE 3D MRSI, as well as single voxel spectral editing and 2-D COSY sequences that will be used to detect in vivo levels of metabolites with complex coupling patterns and overlapping resonances. This will be done for both 3T and 7T scanners in order to determine which method and field strength will provide the most definitive results for patient studies. In Specific Aim 3 we will apply methods optimized for detecting 2HG to patients with recurrent low grade glioma to identify metabolic parameters associated with time to progression and overall survival. In Specific Aim 4, we will perform an analysis in patients with recurrent hig grade glioma using the most reliable strategy for obtaining short TE 3D MRSI data. The results from this study will provide new metrics for assessing response to therapy and for selecting alternative treatments.