MRI-Based Elasticity Imaging
MRI-Based Elasticity Imaging
批准号:
6616320
负责人:
JOHN B WEAVER
金额:
$16.87万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-08-01 至 2003-07-31
关键词:
automated data processing bioengineering /biomedical engineering bioimaging /biomedical imaging breast neoplasm /cancer diagnosis breast neoplasms clinical research computer simulation diagnosis design /evaluation early diagnosis elasticity female human subject human tissue image enhancement image processing magnetic resonance imaging mammography mechanical stress neoplasm /cancer classification /staging neoplastic process women's health
中文摘要
乳腺癌是女性死亡的第二大原因,尽管存在一些问题,但人们普遍认为,及早发现恶性肿瘤可以提高成功治疗的机会。越来越多的证据表明,组织弹性可能是检测和分类乳房病变的一种手段,因为硬度是一种与癌症密切相关的属性。体检在乳腺癌筛查中具有并将继续占据突出地位,这一点突显了这一理由。支持项目I的主要假设是,乳房组织的弹性特性是病理的敏感和特异的预测因子。我们将致力于五个具体目标:1)发展我们的数据采集技术,以(I)在更多的组织中引起更大的位移,(Ii)通过改进的脉冲序列设计来缩短图像采集时间,以及(Iii)使用连续振动操作模式来采集数据。2)与计算核心合作推进我们的基于模型的图像重建方法,包括(I)组织抑制,(Ii)多值属性恢复,(Iii)瞬时效应和(Iv)重叠区域优化,首先是二维,然后是三维。3)进行瞬变效应;(4)重叠区域优化,先二维后三维。3)在受控条件下进行广泛的模拟和体模成像实验,以确定AIMS#1和#2中研究的最佳机械刺激、图像采集和性能评估选项。4)开发临床系统,在合理的时间内评估双侧乳房的机械性能,证明其可行性,并在有限数量的志愿者身上改进手术方案。5)恢复乳房X光照片正常和异常患者的乳房组织的机械性能,首先通过评估的测试阶段,然后与临床核心合作执行前瞻性验证研究。项目一寻求现有的和新的想法的综合,这将解决目前与乳房弹性成像相关的许多问题。首先,将开发产生压缩或扩张位移的简谐机械刺激。谐波位移的相位对比测量也将有助于减少患者的运动伪影,而多光谱振动刺激的使用将提供考虑耗散效应的机会。其次,将采用基于模型的属性重建方法来开发可以在三维中精确测量的多维位移场梯度。此外,由所提出的MR系统提供的体积地下位移数据提供了比基于模型的图像重建环境中通常可用的组织响应观察更广泛的组织响应观察,这可能转化为相对于迄今为止利用弹性成像实现的空间和对比度分辨率的改善。
英文摘要
Breast cancer is the second leading cause of death in women and, despite some questions, it is generally agreed that early detection of malignancies improves the chances of successful treatment. There is mounting evidence to suggests that tissue elasticity might be a means to detect and classify breast lesions because hardness is a property strongly associated with cancer. This rationale is underscore by the prominent place that physical examination has and continues to hold in breast cancer screening. The principle hypotheses which underpins Project I is that breast tissue elastic properties are sensitive and specific predictors of pathology. We will address five specific aims: 1) Advance our data acquisition techniques to (i) induce larger displacements in more mass of tissue, (ii) decrease the image acquisition time through improved pulse sequence designs, and (iii) acquire data using a continuous vibration mode of operation. 2) Advance our model-based image reconstruction methodology in collaboration with the Computational Core to include (i) tissue dampening, (ii) multi-valued property recovery, (iii) transient effects and (iv) overlapping zone optimization, first in two and then in three dimensions. 3) Conduct transient effects and (iv) overlapping zone optimization, first in two and then in three-dimensions. 3) Conduct extensive simulations and phantom imaging experiments under controlled conditions to identify optimal mechanical stimulation, image acquisition and property estimation options from those investigated in Aims #1 and #2. 4) Develop a clinical system to estimate the mechanical properties of both breasts in reasonable times, demonstrate its feasibility and refine procedural protocols on a limited number of volunteers. 5) Recover the mechanical properties of breast tissue on patients with normal and abnormal mammograms, first through a test phase of evaluation followed by a prospective validation study executed in collaboration with the Clinical Core. Project I pursues a synthesis of existing and novel ideas which will address many of the current problems associated with breast elasticity imaging. First, harmonic mechanical stimuli which produce compressional or dilatational displacements will be developed. Phase contrast measurements of harmonic displacement will also serve to reduce patient motion artifacts while the use of multi-spectral vibrational stimuli will afford the opportunity to account for dissipational effects. Second, model-based property reconstruction methods will be deployed to exploit the multi-dimensional displacement field gradients which can be accurately measured in three dimensions. Further, the volumetric subsurface displacement data provided by the proposed MR system provides tissue response observations that are more extensive than those typically available in the model-based image reconstruction context which is likely to translate into improved spatial and contrast resolutions relative to those which have been achieved with elasticity imaging to date.
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科研奖励(0)
会议论文
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MRI-Based Elasticity Imaging
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