PREDICTING TUMOR RESPONSE BY 31-P MRS

描述：此应用程序来自纪念斯隆-凯特琳(MSK)。 先前对小鼠肿瘤的31-P核磁共振波谱研究表明 从光谱中预测肿瘤反应可能是可行的 改变。来自多个机构的初步临床研究，研究 一系列的肿瘤，使用不同的扫描仪，有太多不同的 技术表明，尽管光谱变化在 病人和小鼠肿瘤似乎是完全不同的，然而， 有可能根据以下因素预测临床肿瘤反应 光谱变化。在一些研究中，有人提出光谱 所获得的预处理可能是肿瘤反应的指标。这个 因此，申请者提出了一种多机构合作类型 关于核磁共振波谱能否先验问题的研究 预测肿瘤反应(根据预处理谱)和2)成为 监测光谱变化对肿瘤反应的早期预测 肿瘤缩小前的第一个化疗周期。这个 申请人建议使用信息技术(线圈、数据分析、 获取技术、1H去耦合、体积定位等)，以便 从一个机构到另一个机构，光谱是可以比较的。这个 申请者建议研究四种不同的肿瘤(四肢肉瘤， 晚期乳腺癌、非霍奇金淋巴瘤和鳞状细胞癌 头部和颈部)。这些肿瘤部位有一个共同的因素 肤浅，因此预计本地化将是 更容易(也更准确)，更好地发出噪声信号。这两个因素 如果要准确地测量肿瘤代谢物， 浓度。上面列举的假设将通过以下方式进行测试 光谱变化与肿瘤反应、无病生存期、 存活率和其他临床标志物在这些方面正在获得 病人。除了解决这些重要的临床问题外， 这项研究还应该通过以下方式对磷脂代谢提供洞察 监测磷脂、合成代谢和分解代谢的变化。 磷脂代谢可能是判断肿瘤的重要因素 生长、细胞周期分布、转移和其他重要方面 肿瘤生物学和核磁共振研究可能会对此产生新的见解 区域。

DESCRIPTION: This application is from Memorial Sloan-Kettering (MSK). Previous 31-P NMR spectroscopic studies of murine tumors has suggested that it may be feasible to predict tumor responses from spectral changes. Preliminary clinical studies from many institutions, studying a range of tumors, using different scanners, with a plethora of varied techniques, have suggested that although the spectral changes in patients and murine tumors appear to be quite different, nevertheless, it may be possible to predict clinical tumor response on the basis of spectral changes. In some studies it has been suggested that spectra obtained pretreatment may be indicative of tumor response. The applicants are therefore proposing a multi institutional cooperative type study to answer the questions of whether NMR spectroscopy can 1) a priori predict tumor response (from the pretreatment spectrum) and 2) be an early predictor of tumor response by monitoring spectral changes during the first cycle of chemotherapy prior to tumor shrinkage. The applicants propose to use inform techniques (coils, data analysis, acquisition techniques, 1H decoupling, volume localization etc) so that the spectra are comparable from one institution to the other. The applicants propose to study four different tumors (extremity sarcomas, advanced breast cancer, non Hodgkin's lymphoma, and squamous cell cancer of the head and neck). These tumor sites have the common factor of being superficial and therefore it is expected that localization will be easier (and more accurate) and signal to noise better. These two factors are critical if one is to accurately measure tumor metabolite concentrations. The hypotheses enumerated above will be tested by correlating spectral changes with tumor response, disease free survival, survival, and other clinical markers that are being obtained on these patients. In addition to addressing these important clinical questions, this study should also provide insight into phospholipid metabolism by monitoring changes in phospholipid anabolite and catabolite. Phospholipid metabolism may be an important factor in determining tumor growth, cell cycle distribution, metastases and other important facets of tumor biology and the NMR studies may yield new insights into this area.