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Quantification of Tumor Malignancy with MRI

Quantification of Tumor Malignancy with MRI
MRI 定量肿瘤恶性肿瘤
批准号:
7777245
负责人:
GLYN JOHNSON
金额:
$29.21万
依托单位国家:
美国
项目类别:
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-04-10 至 2013-02-28

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中文摘要
翻译
广泛的长期目标:确定哪些MR指标能够预测疾病进展/生存时间, 特别是在低级别神经胶质瘤中,为神经胶质瘤治疗分类中的组织学提供第二参考标准。 健康相关性:目前的手术和术后胶质瘤治疗是基于常规MRI和组织学检查。 神经胶质瘤的特征然而,MRI和组织学在预测真正的生物学特征方面存在局限性。 胶质瘤的行为。MR指标,其可以提供整个组织的真实生物侵袭性的指示。 病变在体内,将是有用的,在确定手术切除的程度,直接组织标本,为进一步 组织学/分子分析,以及手术后辅助化疗和放疗的分类。 具体目的:1)确定从常规MRI、灌注MR和MR中获得哪些MR指标 低级别胶质瘤的光谱成像能够预测进展/生存时间。假设1:一个或多个 MR指标将能够预测肿瘤生物学行为。2)将MR指标与其他已知的预后指标进行比较 因素(如组织学)预测进展/生存时间。假设2:定量MR指标将具有 在预测肿瘤生物学行为方面,增加了组织病理学评估的价值。3)为了确定MR是否 度量可以用作化学敏感性的分子标记的成像相关物。假设3:MR指标,如 rCBV(和其他)可以与肿瘤进展、血管生成、侵袭、增殖的分子标志物相关。 和化疗敏感性,如HIF-1 α、FAK、VEGF/VPF、Ipl 9 q缺失,并且反过来可以用作指导治疗的标志物。 进一步的分子分析、治疗和预测预后。 研究设计:1)获取常规MRI、灌注(DSC MRI)和光谱(MRSI)数据集,以获得 研究患者的定量MR指标。2)Weibull生存模型分析和Kaplan-Meier生存曲线将 用于确定哪些指标可以预测进展/生存时间。将病理结果与病理结果进行比较 和其他预后因素来预测结果。3)最后,MR指标将与以下分子标记物相关: 肿瘤进展、血管生成、增殖和化学敏感性,如HIF-1 α、FAK、VEGF/VPF、Ip 19 q 删除。将使用PCR通过杂合性丢失评估分子研究。DNA将从石蜡中提取 将使用脑切片和指甲剪的卷曲和以下引物:1.D1S1592; 2. D19S219,D19S412。
英文摘要
Broad long-term objectives: To determine which MR metrics are able to predict time to progression/survival, particularly in low grade gliomas, to provide a second reference standard to histology in glioma therapy triage. Health-relatedness: Current surgical and post-surgical glioma therapy is based on the conventionalMRI andhistologic features of a glioma. However, there are limitations with both MRI and histology in predicting the true biologic behavior of gliomas. MR metrics, which can provide an indication of the true biologic aggressiveness of an entire lesion in vivo, will be useful in determining the extent of surgical resection, direct tissue specimens for further histologic/ molecular analysis, and the triage of adjuvant chemotherapy and radiation therapy following surgery. Specific aims: 1) To determine which MR metrics obtained from conventional MRI, perfusion MR and MR spectroscopic imaging in low-grade gliomas are able to predict time to progression/survival.Hypothesis 1: One or more MR metrics will be able to predict tumor biologic behavior. 2) To compare MR metrics with other known prognostic factors (such as histology) in predicting time to progression/survival. Hypothesis 2: QuantitativeMR metrics will have added value in and above histopathologic assessment in predicting tumor biologic behavior. 3) To determine if MR metrics can serve as imaging correlates for molecular signatures of chemosensitivity. Hypothesis 3: MR metrics such as rCBV (and others) can be correlated with molecular markers of tumor progression, angiogenesis, invasion, proliferation and chemosensitivity such as HIF-la, FAK, VEGF/VPF, Ipl9q deletions and in turn can be used as marker for guiding further molecular analysis, therapy and predicting prognosis. Research Design: 1) Acquire conventional MRI, perfusion (DSC MRI) and spectroscopic (MRSI) data sets to obtain quantitative MR metrics from study patients. 2) Weibull survival model analysis and Kaplan-Meier survivalcurves will be used to determine which metrics can predict time to progression/survival. Metrics will be compared with pathology and other prognostic factors in predicting outcome. 3) Finally MR metrics will be correlated with molecularmarkersof tumor progression, angiogenesis, proliferation and chemosensitivity such as HIF-la, FAK, VEGF/VPF, Ipl9q deletions. Molecular studies will be assessed by loss of heterozygosity using PCR. DNA will be extracted from paraffin curls of brain section and nail clippings and the followingprimers will be used: 1.D1S1592; 2. D19S219, D19S412.
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