MR Metabolic Markers for Evaluation of Patients with Recurrent Glioma

描述(申请人提供)：这项研究的目标是开发强大的工具来获取和分析复发胶质瘤患者的体内磁共振代谢数据，这些工具将与最先进的磁共振成像方法相结合，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，该问题混淆了对新疗法的评估，并使其难以做出关于患者护理的知情决定。对于高级别胶质瘤患者，肿瘤复发引起的形态变化与胶质增生和水肿等治疗效果之间存在歧义。根据当前R01周期的结果，用于绘制肿瘤复发真实范围的感兴趣的代谢物是肌醇(myo-I)、N-乙酰天冬氨酸(NAA)、肌酸(Cr)和胆碱(Cho)。对于最初被诊断为低级别胶质瘤的患者，如果他们的病变正在扩大，关键问题是确定他们何时经历了向需要积极治疗的更恶性表型的转变。从我们对组织样本的体外分析中，本病例中其他感兴趣的代谢物是肌醇-I、谷氨酸、谷氨酰胺、甘氨酸、谷胱甘肽和2-羟基戊二酸(2HG)。在具体的目标1和2中，我们将优化并评估自动短TE 3D MRSI以及单体素光谱编辑和2-D COSY序列的测试重新测试精度，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，以确定哪种方法和磁场强度将为患者研究提供最明确的结果。在具体目标3中，我们将对复发的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。在特定目标4中，我们将使用获得短TE 3D MRSI数据的最可靠策略对复发的高级别胶质瘤患者进行分析。这项研究的结果将为评估治疗反应和选择替代治疗提供新的衡量标准。

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.