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CoS-MRXI - Compressed sensing for magnetorelaxometry imaging of magnetic nanoparticles

CoS-MRXI - 用于磁性纳米颗粒磁松弛测量成像的压缩传感

基本信息

批准号：
273505405
负责人：
Professor Dr.-Ing. Daniel Baumgarten
金额：
--
依托单位：
Projektträger DESY
依托单位国家：
德国
项目类别：
Priority Programmes
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/273505405?language=en
关键词：
CoS MRXI Compressed sensing magnetorelaxometry

项目摘要

Magnetic nanoparticles offer a large variety of promising biomedical applications, particularly in cancer therapy. For the safety and efficiency of these applications, quantitative knowledge about the distribution of the particles is required. Until today, no imaging technology is clinically available for the quantitative in-vivo detection of the particles. Magnetorelaxometry imaging (MRXI) with inhomogeneous excitation fields is able to quantitatively detect distributions of magnetic nanoparticles in vivo. Recently, the potential of this technique has been demonstrated in experimental measurements. In these experiments, excitation coils, positioned in regular arrays, were consecutively activated and the magnetic relaxation of the particles was measured in each step. By solving an inverse problem, the distribution of the particles was reconstructed from these measurements. While the imaging results were promising, a long measurement time was required with respect to the consecutive activation of single coils Furthermore, large amounts of data needed to be recorded.In this project, the methods of compressed sensing will be adapted and expanded to the application of magnetorelaxometry imaging of magnetic nanoparticles. We aim at developing appropriate excitation sequences for existing systems as well as design approaches for excitation coils and sensor setups. These developments will finally lead to a substantial advancement in the imaging technology including a substantial enhancement in spatial resolution and a considerable reduction of the number of coils and the measurement times. From a theoretical point of view, we expect an improved understanding of compressed sensing paradigms for only partly given sensing matrices, yielding practical impact in other biomedical imaging applications. Furthermore, quantitative reconstruction algorithms should be developed by compressed sensing paradigms.To achieve the project objectives, the mathematical background of compressed sensing for MRXI will be worked out and sparsity-based reconstruction algorithms will be adapted the MRXI setting. Furthermore, compressed sensing methods will be investigated for the solution of bilinear and trilinear optimization problems. In order to incorporate prior knowledge about the biological particle distribution in the reconstruction algorithms, the properties of these distributions will be studied and a respective model will be set up. We will develop compressed sensing based excitation schemes for existing experimental MRXI setups by optimizing the weight vectors and checking the respective recovery conditions. A particularly novel aspect is that natural sparsity constraints will be used for the design variables of the system as well. These approaches will later be extended to the design of excitation coils and sensor systems. Finally, the developments will be thoroughly investigated in simulation studies and validated in experimental phantom measurements.

磁性纳米颗粒在生物医学领域有着广泛的应用前景，尤其是在癌症治疗方面。为了这些应用的安全和效率，需要关于颗粒分布的定量知识。直到今天，临床上还没有成像技术可用于体内颗粒的定量检测。非均匀激发场磁松弛成像(MRXI)能够定量检测磁性纳米粒子在体内的分布。最近，这种技术的潜力已经在实验测量中得到了证明。在这些实验中，连续激活排列成规则阵列的激励线圈，并在每一步测量粒子的磁弛豫。通过求解反问题，根据这些测量结果重建了颗粒的分布。本课题将压缩传感技术应用于磁性纳米颗粒的磁弛豫法成像，虽然成像效果良好，但单个线圈的连续激活需要较长的测量时间，而且需要记录大量数据。我们的目标是为现有系统开发合适的励磁序列，以及励磁线圈和传感器设置的设计方法。这些发展最终将导致成像技术的实质性进步，包括空间分辨率的大幅提高，以及线圈数量和测量时间的大幅减少。从理论的角度来看，我们期待着对压缩传感范例的理解有所改善，仅针对部分给定的传感矩阵，从而在其他生物医学成像应用中产生实际影响。为了达到项目目标，将研究基于压缩感知的MRXI的数学背景，并将基于稀疏性的重建算法应用于MRXI的设置。此外，还将研究用于解决双线性和三线性优化问题的压缩感知方法。为了将有关生物粒子分布的先验知识融入到重建算法中，将研究这些分布的性质并建立各自的模型。我们将通过优化权重向量和检查各自的恢复条件，为现有的实验MRXI设置开发基于压缩传感的激励方案。一个特别新颖的方面是，自然稀疏性约束也将用于系统的设计变量。这些方法稍后将扩展到励磁线圈和传感器系统的设计。最后，这些发展将在模拟研究中得到彻底的调查，并在实验模型测量中得到验证。