Determining properties of subvoxel objects from MRI images

描述（由申请人提供）：人体组织的磁性测量正迅速成为磁共振成像（MRI）和分子成像研究疾病的关键因素。在MRI中，亚体素物体的磁性通常不能从给定的大小图像中确定。尽管物体与其周围组织之间的磁化率差异会导致附近组织的信号丢失，但幅度和相位图像的组合可以用于量化MR图像中任何给定物体的磁性。本文将充分开发一种利用这一特征的新的反演方法，特别是针对少量体素或亚体素对象。该方法需要使用复杂的MRI数据，自然考虑到部分体积效应、去相效应（即信号损失）和相位混叠效应。与其他方法相比，该方法不需要感兴趣对象的任何先验信息。该方法的不确定度取决于图像的信噪比和分辨率。本研究提出了三个具体目标。第一个目标是确定一个球形物体和一个无限长的圆柱形物体的磁矩。前者代表一个3D问题，而后者代表一个2D问题。基本电磁学保证了三维空间中任何小物体的磁矩都可以很好地近似于球体的磁矩。将进行仿真和模拟实验来验证该方法并研究该方法的不确定性。第二个目标是将该方法应用于现有的人类和动物图像。这是为了证明该方法在实际图像上的可行性。第三个目标是分别求解物体的磁化率和体积。由于图像中远小于体素的物体（如纳米颗粒）的体积显然无法确定，因此研究所提出方法的局限性非常重要。这项工作可能会通过使用纳米粒子对研究衰老或分子成像产生重大影响。有证据表明2-淀粉样蛋白斑块与阿尔茨海默病有关。动物研究表明，淀粉样蛋白沉积会导致阿尔茨海默病早期的低血糖斑。量化每个个体黑斑的特性可能成为监测疾病进展的预测指标。目前，除了计数之外，没有任何非侵入性工具可用于准确量化大脑中的微出血或低血压点。纳米粒子在核磁共振成像中被广泛应用于分子成像中的细胞标记。需要一种可靠的体内方法来量化与病变组织相互作用的纳米颗粒标记细胞的浓度。这种方法可以用许多相同的纳米颗粒来做到这一点。综上所述，本研究有可能有助于MRI更好地诊断和功能疾病。

DESCRIPTION (provided by applicant): The measurement of magnetic properties of tissues in the human body is fast becoming a key element in studying disease with magnetic resonance imaging (MRI) and in molecular imaging. The magnetic properties of a subvoxel object usually cannot be determined from a given magnitude image in MRI. Although the magnetic susceptibility difference between an object and its surrounding tissue leads to a signal loss in the nearby tissue, the combination of magnitude and phase images can be used to quantify the magnetic property of any given object in MR images. A novel inverse method using this feature will be fully developed in this proposal, especially for a few voxel or subvoxel objects. This method requires the use of complex MRI data and naturally accounts for the partial volume effect, dephasing effect (i.e., signal loss), and the phase aliasing effect. Compared to other methods, this method does not require any a priori information of the object of interest. The uncertainty of the method depends on the signal-to-noise ratio and resolution of images. Three specific aims are proposed in this research. The first aim is to determine the magnetic moment of a spherical object and an infinitely long cylindrical object. The former represents a 3D problem while the latter represents a 2D problem. Fundamental electromagnetism guarantees that the magnetic moment of any small object in 3D can be well approximated by the magnetic moment of a sphere. Both simulations and phantom experiments will be conducted to validate the method and investigate the uncertainty of the method. The second aim is to apply the method on existing human and animal images. This is to demonstrate the feasibility of the method on practical images. The third aim is to resolve the magnetic susceptibility and volume of the object individually. Since it is obvious that the volume of an object much less than a voxel such as a nanoparticle in images cannot be determined, it is important to study the limitation of the proposed method. This work could have a major impact on studying aging or molecular imaging through the use of nanoparticles. Evidence indicates that 2-amyloid plaque is related to Alzheimer's disease. Animal studies have shown that amyloid deposits lead to hypointense spots at an early stage of Alzheimer's disease. Quantification of the property of each individual dark spot may become a predictor for monitoring the progression of the disease. Currently, no non-invasive tool other than number counting is available for accurately quantifying microbleeds or hypointense spots in the brain. Nanoparticles have been widely used in MRI for tagging cells in molecular imaging. A reliable in vivo method is needed to quantify the concentration of nanoparticles labeling cells that interact with diseased tissue. This method can do that with numerous identical nanoparticles. In summary, this research has the potential to contribute to the better diagnosis and function of disease in MRI. PUBLIC HEALTH RELEVANCE: The proposed method may become a predictor of Alzheimer's disease in the long run. It may become a useful tool for the design of personalized medicine. The benefit of this research to the public health is obvious.