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BREAST CANCER DIAGNOSIS AND PREDICTION OF CHEMOTHERAPEUTIC RESPONSES W MRS & MR

BREAST CANCER DIAGNOSIS AND PREDICTION OF CHEMOTHERAPEUTIC RESPONSES W MRS & MR
W MRS 乳腺癌诊断和化疗反应预测
批准号:
7721351
负责人:
MICHAEL GARWOOD
金额:
$8.92万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-06-01 至 2009-05-31

项目摘要

项目成果

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中文摘要
翻译
这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金, 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 为了确定从初次系统治疗(PST)前到首次治疗后24小时内胆碱类化合物(TCHO)浓度的变化是否能够预测局部晚期乳腺癌患者的临床反应
英文摘要
This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. To determine if changes in the concentration of choline-containing compounds (tCho) from before primary systemic therapy (PST) to within 24 hours after the first treatment enable prediction of clinical response in patients with locally advanced breast cancer
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会议论文
Angular Dependency of T1 Relaxation Time in Cerebral White Matter in Ultrahigh Field MRI
  • 批准号:
    9983056
  • 项目类别:
  • 资助金额:
    $7.7万
  • 财政年份:
    2019
  • 负责人:
    MICHAEL GARWOOD
  • 依托单位:
Imaging Human Brain Function with Minimal Mobility Restrictions: SUPPLEMENT: Administrative Supplement for Research on Bioethical Issues
  • 批准号:
    9928254
  • 项目类别:
  • 资助金额:
    $15.14万
  • 财政年份:
    2017
  • 负责人:
    MICHAEL GARWOOD
  • 依托单位:
Imaging Human Brain Function with Minimal Mobility Restrictions
  • 批准号:
    10240647
  • 项目类别:
  • 资助金额:
    $149.18万
  • 财政年份:
    2017
  • 负责人:
    MICHAEL GARWOOD
  • 依托单位:
Imaging Brain Function in Real World Environments & Populations with Portable MRI
  • 批准号:
    8822705
  • 项目类别:
  • 资助金额:
    $39.38万
  • 财政年份:
    2014
  • 负责人:
    MICHAEL GARWOOD
  • 依托单位:
国内基金
海外基金
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data