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Breast Cancer Screening with Quantitative Ultra-Fast DCEMRI and Clinical Risk Assessment

Breast Cancer Screening with Quantitative Ultra-Fast DCEMRI and Clinical Risk Assessment
使用定量超快速 DCEMRI 进行乳腺癌筛查和临床风险评估
批准号:
10174859
负责人:
Gregory S. Karczmar
金额:
$57.66万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-06-15 至 2022-05-31

项目摘要

项目成果

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中文摘要
翻译
摘要 核磁共振有可能显著改善乳腺癌筛查,特别是对患有高密度乳腺癌的女性。 乳房和患乳腺癌风险高于平均水平的女性。然而,改进了 在使用MRI对大量女性进行筛查之前,需要诊断的准确性。这个 由Kuhl和他的同事设计的简写MRI扫描(AB-MRI)是一种非常有前途的MRI方法。 筛查,但依靠单次T1加权扫描后对比剂注射来评估增强。这个 缺乏有关造影剂摄取动力学的信息可能会降低诊断的准确性。这项研究 这里提出的建议将检验这样一个假设,即在AB-MRI中添加超快MRI可以提高诊断能力 精确度。我们认为AB-MRI结合超快DCE-MRI可以提供有效的筛查 价格合理,对患者的不便最小。这将导致可靠地检测到 临床上有意义的乳腺癌比目前的筛查方法早几年,因此显著 降低乳腺癌的发病率和死亡率。 一项全国ECOG-ACRIN AB-MRI筛查临床试验将于2016年底开始。的基本协议 该试验为10分钟扫描,单次增强后T1加权扫描。然而,根据以下结果, 本实验室,ECOG ACRIN试验的领导者强烈支持将定量超快DCE-MRI纳入 加州大学芝加哥分校的AB-MRI(请参阅主席的支持信)。我们建议: 1.优化将超快DCE-MRI整合到AB-MRI中,总时程小于10分钟。这个 超快的DCE-MRI扫描每张图像的时间分辨率将低于3秒。 2.开展超快数据的定量分析,以测量初始增强时间(TIE), 基于一种简化的计算方法--损伤传递函数的定量KTRANS测量 (LTF)和病变通过时间(LTT)。此外,我们还将测量损伤的初始动力学。 增强纹理。 3.评价DCE-MRI药代动力学参数诊断的准确性。将对数据进行分析 分两个阶段。首先,我们将使用UChicago目前正在获取的数据来确定大多数 来自超快DCE-MRI的有希望的参数可用于进一步评估。第二,我们将评估最多的 “测试组”中的参数前景看好。ROC分析将用于确定参数是否来自 超快成像可提高MRI筛查的诊断准确率。 4.使用两种读卡器比较AB-MRI使用和不使用超快DCE-MRI的诊断准确性 研究和定量分析。 新的超快DCE-MRI,集成到AB-MRI扫描中,将显著降低发病率和死亡率 治疗乳腺癌,同时显著降低成本和提高效率。
英文摘要
Abstract MRI has potential to significantly improve breast cancer screening, particularly for women with dense breasts and women who are at higher than average risk for breast cancer. However, improvements in diagnostic accuracy are needed before MRI can be used to screen large numbers of women. The abbreviated MRI scan (AB-MRI) designed by Kuhl and colleagues is a very promising approach to MRI- screening, but relies on a single T1-weighted scan post contrast injection to evaluate enhancement. The lack of information regarding contrast media uptake kinetics may reduce diagnostic accuracy. The research proposed here will test the hypothesis that addition of ultrafast MRI to AB-MRI improves diagnostic accuracy. We propose that AB-MRI combined with ultrafast DCE-MRI can provide effective screening with at a reasonable cost, and with minimal inconvenience for patients. This would result in reliable detection of clinically significant breast cancer years earlier than current screening methods, and thus significantly reduce morbidity and mortality due to breast cancer. A national ECOG-ACRIN clinical trial of AB-MRI screening will begin in late 2016. The basic protocol for this trial is a 10 minute scan with a single post-contrast T1-weighted scan. However, based on results from this lab, the leaders of the ECOG ACRIN trial strongly support inclusion of quantitative ultrafast DCE-MRI in AB-MRI at UChicago (please see the letter of support from the Chair). We propose to: 1. Optimize ultrafast DCE-MRI integrated into AB-MRI with total duration of less than 10 minutes. The ultrafast DCE-MRI scan will have time resolution of less than 3 seconds per image. 2. Develop quantitative analysis of ultrafast data to measure time of initial enhancement (TIE), quantitative Ktrans measurements based on a simplified computational approach, lesion transfer function (LTF) and lesion transit Time(LTT). In addition, we will measure the initial kinetics of lesion enhancement texture. 3. Evaluate the diagnostic accuracy of pharmacokinetic parameters from DCE-MRI. Data will be analyzed in two stages. First, we will use data that is currently being acquired at UChicago to identify the most promising parameters from ultrafast DCE-MRI for further evaluation. Second, we will evaluate the most promising parameters in a ‘testing group’. ROC analysis will be used to determine whether parameters from ultrafast imaging can increase the diagnostic accuracy of MRI screening. 4. Compare the diagnostic accuracy of AB-MRI with and without ultrafast DCE-MRI, using both a Reader study and quantitative analysis. New ultrafast DCE-MRI, integrated into AB-MRI scans will significantly reduce morbidity and mortality due to breast cancer, while significantly reducing costs and increasing efficiency.
期刊论文(8)
专著(0)
科研奖励(0)
会议论文
Parametric maps of spatial two-tissue compartment model for prostate dynamic contrast enhanced MRI - comparison with the standard Tofts model in the diagnosis of prostate cancer.
前列腺动态对比增强 MRI 空间两组织室模型的参数图 - 与诊断前列腺癌的标准 Tofts 模型进行比较。
DOI: 10.21203/rs.3.rs-2539644/v1
发表时间: 2023
期刊: Research square
影响因子: --
作者: [Zhou,Xueyan, Fan,Xiaobing, Chatterjee,Aritrick, Yousuf,Ambereen, Antic,Tatjana, Oto,Aytekin, Karczmar,GregoryS]
通讯作者: Karczmar,GregoryS
DOI: 10.1371/journal.pone.0286123
发表时间: 2023
期刊: PloS one
影响因子: 3.7
作者: []
通讯作者:
DOI: 10.1002/mp.12747
发表时间: 2018-03
期刊: Medical physics
影响因子: 3.8
作者: [Pineda FD, Easley TO, Karczmar GS]
通讯作者: Karczmar GS
DOI: 10.1186/s13058-021-01489-6
发表时间: 2021-11-27
期刊: Breast cancer research : BCR
影响因子: --
作者: [Virostko J, Sorace AG, Slavkova KP, Kazerouni AS, Jarrett AM, DiCarlo JC, Woodard S, Avery S, Goodgame B, Patt D, Yankeelov TE]
通讯作者: Yankeelov TE
Detection of prostate Cancer Specific Signals with Hybrid Multi-Dimensional MRI
  • 批准号:
    10365985
  • 项目类别:
  • 资助金额:
    $52.35万
  • 财政年份:
    2019
  • 负责人:
    Gregory S. Karczmar
  • 依托单位:
Detection of prostate Cancer Specific Signals with Hybrid Multi-Dimensional MRI
  • 批准号:
    10600041
  • 项目类别:
  • 资助金额:
    $52.48万
  • 财政年份:
    2019
  • 负责人:
    Gregory S. Karczmar
  • 依托单位:
Detection of prostate Cancer Specific Signals with Hybrid Multi-Dimensional MRI
  • 批准号:
    9906218
  • 项目类别:
  • 资助金额:
    $53.04万
  • 财政年份:
    2019
  • 负责人:
    Gregory S. Karczmar
  • 依托单位:
Breast Cancer Screening with Quantitative Ultra-Fast DCEMRI and Clinical Risk Assessment
  • 批准号:
    9370492
  • 项目类别:
  • 资助金额:
    $57.82万
  • 财政年份:
    2017
  • 负责人:
    Gregory S. Karczmar
  • 依托单位:
海外基金