Modeling of the Magnetic Particle Imaging Signal Due to Magnetic Nanoparticles

磁性纳米粒子产生的磁性粒子成像信号的建模

• 批准号: 9024525
• 负责人: Carlos M Rinaldi-Ramos
• 金额: $ 18万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-03-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9024525
• 关键词: Accounting; Algorithms; Angiography; Anisotropy; Arteries; Attention; Caliber; Cells; Characteristics; Chronic Kidney Failure; Coagulation Process; Computer Simulation; Contrast Media; Coronary; Coronary artery; Dependence; Detection; Development; Disadvantaged; Environment; Equation; Foundations; Future; Future Generations; Health; Hybrids; Image; Imaging Techniques; Inflammation; Location; Magnetic Resonance Imaging; Magnetic nanoparticles; Magnetism; Maps; Measurement; Mission; Modeling; Monitor; Motion; Organ; Patients; Performance; Property; Relaxation; Research; Resolution; Rotation; Scanning; Shipping; Ships; Signal Transduction; Solid; Spatial Distribution; Suspension substance; Suspensions; Time; Tissues; Tracer; Translations; Viscosity; Work; bioimaging; cancer imaging; contrast imaging; cost effective; design; experience; image processing; improved; innovation; interest; iron oxide; magnetic dipole; magnetic field; nanoparticle; novel; operation; particle; response; simulation; theories

 DESCRIPTION (provided by applicant): Magnetic Particle Imaging (MPI) is a new tomographic imaging technique that maps the spatial distribution of iron oxide magnetic nanoparticles (MNPs) in real time and with spatial resolution that is on par or better than other biomedical imaging techniques. Because iron oxide MNPs are nontoxic, MPI is a safe imaging alternative for Chronic Kidney Disease (CKD) patients and due to its sensitivity it is suitable for angiography, cell tracking, cancer imaging, inflammation imaging, imaging major organs, and imaging of coronary arteries. Recently attention has shifted towards development of MNPs with ideal MPI signal characteristics. Unfortunately, these efforts are hampered by a lack of theories that predict the MPI signal due to MNP tracers, taking into account the finite relaxation dynamics of MNPs in time-varying magnetic fields typical of MPI. Because of this, most prior work on development of MNP MPI tracers has been limited to trial-and-error characterization of synthesized particles, without a theory guiding their rational design. What is needed is a solid theoretical foundation that will allow rational design of future generations of MNP MPI tracers and tuning of MPI magnetic field conditions to yield optimal image contrast and resolution. The proposed research will develop a theoretical foundation relating MNP properties (e.g., core size, hydrodynamic diameter, domain magnetization, magnetic anisotropy, particle-particle interactions, etc.) and MPI magnetic field conditions (strength of bias and excitation field, magnetic field gradient strength, scan rate, etc.) to the MPI signal strength and resolution. The proposed approach is unique and distinct from other work because we will develop stochastic computer simulation models of the response of MNPs to the magnetic fields typical of MPI, taking into account nanoparticle translation, physical rotation, internal dipole rotation, and particle-particle magnetic interactions. These models will enable systematic study of the large parameter space of particle properties and magnetic field conditions typical of MPI. The proposed work is significant because it will provide a much-needed theoretical understanding of the relation- ship between particle properties, MPI magnetic field conditions, and MPI signal strength and resolution. The proposed work is also significant because it will yield rules for the rational design of MNP MPI tracers with optimal signal strength and resolution and could also suggest novel applications of MPI beyond imaging of MNP tracer location and motion. The proposed work is innovative because it will yield this theoretical foundation through development of computer simulation platforms to model the response of MNPs to the magnetic fields generated in MPI through a combination of Brownian dynamics simulations of particle translation and rotation and the Landau-Lifshitz-Gilbert equation describing internal magnetic dipole rotation, an approach that is currently unexplored. The proposed work is also innovative because these computer simulation platforms will be used to explore the dependence of the MPI signal on MNP properties and MPI magnetic field conditions, yielding design rules to guide development of future generations of MPI tracers and MPI applications.

 描述（由申请人提供）：磁粒子成像（MPI）是一种新型断层扫描成像技术，可实时绘制氧化铁磁性纳米粒子（MNP）的空间分布图，其空间分辨率与其他生物医学成像技术相当或更好。由于氧化铁 MNP 无毒，MPI 是慢性肾脏病 (CKD) 患者的安全成像替代方案，并且由于其敏感性，它适用于 血管造影、细胞追踪、癌症成像、炎症成像、主要器官成像和冠状动脉成像。最近的注意力已转向开发具有理想 MPI 信号特性的 MNP。不幸的是，这些努力因缺乏预测 MNP 示踪剂导致的 MPI 信号的理论而受到阻碍，同时考虑到 MNP 在 MPI 典型的时变磁场中的有限弛豫动力学。因此，大多数先前开发 MNP MPI 示踪剂的工作仅限于合成粒子的试错表征，没有指导其合理设计的理论。我们需要的是坚实的理论基础，以便合理设计未来几代 MNP MPI 示踪剂并调整 MPI 磁场条件，以产生最佳的图像对比度和分辨率。拟议的研究将建立MNP特性（例如，核心尺寸、流体动力学直径、磁畴磁化强度、磁各向异性、颗粒间相互作用等）和MPI磁场条件（偏置和激励场的强度、磁场梯度强度、扫描速率等）与MPI信号强度和分辨率相关的理论基础。所提出的方法是独特的，与其他工作不同，因为我们将开发 MNP 对 MPI 典型磁场响应的随机计算机模拟模型，同时考虑纳米粒子平移、物理旋转、内部偶极子旋转和粒子-粒子磁相互作用。这些模型将能够系统地研究 MPI 典型的颗粒特性和磁场条件的大参数空间。这项工作意义重大，因为它将为粒子特性、MPI 磁场条件以及 MPI 信号强度和分辨率之间的关系提供急需的理论理解。所提出的工作也很重要，因为它将产生合理设计具有最佳信号强度和分辨率的 MNP MPI 示踪剂的规则，并且还可以建议 MPI 超越 MNP 示踪剂位置和运动成像的新应用。所提出的工作具有创新性，因为它将通过开发计算机模拟平台来模拟 MNP 对 MPI 中产生的磁场的响应，通过结合粒子平移和旋转的布朗动力学模拟以及描述内部磁偶极子旋转的 Landau-Lifshitz-Gilbert 方程（目前尚未探索的一种方法）来提供这一理论基础。所提出的工作也是创新的，因为这些计算机模拟平台将用于探索 MPI 信号对 MNP 特性和 MPI 磁场条件的依赖性，产生设计规则来指导未来几代 MPI 示踪剂和 MPI 应用的开发。

项目成果

Thermal Decomposition Synthesis of Iron Oxide Nanoparticles with Diminished Magnetic Dead Layer by Controlled Addition of Oxygen.

• DOI: 10.1021/acsnano.7b00609
• 发表时间: 2017-02-28
• 期刊: ACS nano
• 影响因子: 17.1
• 作者: Unni M;Uhl AM;Savliwala S;Savitzky BH;Dhavalikar R;Garraud N;Arnold DP;Kourkoutis LF;Andrew JS;Rinaldi C
• 通讯作者: Rinaldi C

Design and validation of magnetic particle spectrometer for characterization of magnetic nanoparticle relaxation dynamics.

• DOI: 10.1063/1.4978003
• 发表时间: 2017-05
• 期刊: AIP advances
• 影响因子: 1.6
• 作者: Garraud N;Dhavalikar R;Maldonado-Camargo L;Arnold DP;Rinaldi C
• 通讯作者: Rinaldi C

Theoretical Predictions for Spatially-Focused Heating of Magnetic Nanoparticles Guided by Magnetic Particle Imaging Field Gradients.

• DOI: 10.1016/j.jmmm.2016.06.038
• 发表时间: 2016-12-01
• 期刊: Journal of magnetism and magnetic materials
• 影响因子: 2.7
• 作者: Dhavalikar R;Rinaldi C
• 通讯作者: Rinaldi C

Magnetic Particle Imaging-Guided Heating in Vivo Using Gradient Fields for Arbitrary Localization of Magnetic Hyperthermia Therapy.

• DOI: 10.1021/acsnano.8b00893
• 发表时间: 2018-04-24
• 期刊: ACS nano
• 影响因子: 17.1
• 作者: Tay ZW;Chandrasekharan P;Chiu-Lam A;Hensley DW;Dhavalikar R;Zhou XY;Yu EY;Goodwill PW;Zheng B;Rinaldi C;Conolly SM
• 通讯作者: Conolly SM

Benchtop magnetic particle relaxometer for detection, characterization and analysis of magnetic nanoparticles.

• DOI: 10.1088/1361-6560/aad97d
• 发表时间: 2018-09-06
• 期刊: Physics in medicine and biology
• 影响因子: 3.5
• 作者: Garraud N;Dhavalikar R;Unni M;Savliwala S;Rinaldi C;Arnold DP
• 通讯作者: Arnold DP