Quantification of Tumor Malignancy with MRI

MRI 定量肿瘤恶性肿瘤

• 批准号: 7564022
• 负责人: GLYN JOHNSON
• 金额: $ 29.21万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-10 至 2011-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7564022
• 关键词: Academic Medical Centers; Adjuvant; Adjuvant Chemotherapy; Age; Algorithms; Appearance; Behavior; Biopsy; Biopsy Specimen; Brain; Cause of Death; Central Nervous System Neoplasms; Cessation of life; Choline; Chromosomes; Classification; Clip; DNA; Data Set; Diagnosis; Doctor of Medicine; Excision; Glioma; Goals; Gold; Healthcare Systems; Histologic; Histology; Histopathology; Image; Institution; Intracranial Neoplasms; Investigation; Karnofsky Performance Status; Laws; Lesion; Location; Loss of Heterozygosity; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Malignant - descriptor; Malignant Glioma; Malignant Neoplasms; Measurement; Metric; Modeling; Molecular; Molecular Analysis; Molecular Profiling; Morbidity - disease rate; Nail plate; Nature; Neoplasms; New York; Operative Surgical Procedures; Outcome; PTK2 gene; Paraffin; Pathologist; Pathology; Patients; Performance; Perfusion; Primary Brain Neoplasms; Prognostic Factor; Radiation; Radiation therapy; Radio; Reference Standards; Research Design; Research Personnel; Resected; Sampling; Sampling Errors; Specimen; Subgroup; Surgeon; System; Testing; Time; Tissue Sample; Tissues; Triage; Tumor Tissue; Uncertainty; Vascular Endothelial Growth Factors; Vascular Permeabilities; angiogenesis; base; chemotherapy; cost; improved; in vivo; molecular marker; oligodendroglioma; outcome forecast; premature; programs; spectroscopic imaging; tumor; tumor progression

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.

广泛的长期目标：为了确定哪些MR指标能够预测进展/存活时间， 特别是在低级别胶质瘤中，为组织学在胶质瘤治疗分流中提供第二个参考标准。 与健康相关：目前脑胶质瘤的手术和术后治疗都是基于常规的MRI和组织学 神经胶质瘤的特征。然而，核磁共振和组织学在预测真正的生物学方面都有局限性。 胶质瘤的行为。MR指标，它可以提供整个 在活体病变中，将有助于确定手术切除的范围，直接为进一步的组织标本 组织学/分子分析，手术后辅助化疗和放射治疗的分流。 具体目标：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/存活的时间。假设1：一个或多个 磁共振测量将能够预测肿瘤的生物学行为。2)将MR指标与其他已知预后指标进行比较 预测进展时间/生存时间的因素(如组织学)。假设2：QuantitativeMR指标将具有 组织病理学评估在预测肿瘤生物学行为中的附加值。3)确定MR是否 指标可以作为化疗敏感性的分子标记的成像相关性。假设3：MR指标，如 RCBV(及其他)可与肿瘤进展、血管生成、侵袭、增殖的分子标志物相关 而化疗敏感性如HIF-1a、FAK、VEGF/VPF、Ipl9q缺失等可作为指导治疗的标志物 进一步的分子分析、治疗和预后预测。 研究设计：1)获取常规MRI、灌注成像(DSC MRI)和磁共振波谱(MRSI)数据集 来自研究患者的定量磁共振指标。2)威布尔生存模型分析和Kaplan-Meier生存曲线 用于确定哪些指标可以预测进展时间/生存时间。指标将与病理进行比较 以及其他预后因素对预后的预测。3)最后，磁共振指标将与以下分子标记相关联 肿瘤进展、血管生成、增殖和化疗敏感性如HIF-1a、FAK、VEGF/VPF、Ipl9q 删除。分子研究将通过使用聚合酶链式反应的杂合性损失进行评估。将从石蜡中提取DNA 将使用卷曲的脑切片和指甲剪片以及以下引物：1.D1S1592；2.D19S219、D19S412。