A sparse reconstruction algorithm for superparamagnetic relaxometry

超顺磁弛豫测量的稀疏重建算法

• 批准号: 9319535
• 负责人: Sara Lynn Loupot Thrower
• 金额: $ 2.8万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9319535
• 关键词: 3-Dimensional; ABCG2 gene; Algorithms; Biological; Biomedical Technology; Cells; Characteristics; Clinic; Collection; Computer Simulation; Data; Development; Devices; Disease; Early Diagnosis; Electromagnetics; Environment; Future; Geometry; Goals; Imaging Techniques; Knowledge; Laws; Learning Skill; Literature; Location; Magnetism; Malignant Neoplasms; Measurement; Measures; Methods; Modeling; Noise; One-Step dentin bonding system; Outcome; Performance; Physics; Property; Research; Research Personnel; Resolution; Sensitivity and Specificity; Signal Transduction; Site; Source; System; Techniques; Technology; Testing; Training; Translating; Translations; Uncertainty; Work; base; cancer cell; cancer site; career; clinical application; design; detector; experimental study; high risk; image guided; improved; magnetic dipole; mouse model; nanoparticle; new technology; novel; particle; pre-clinical trial; preclinical study; reconstruction; response; source localization; superconducting quantum interference device; treatment response; tumor

Project Summary Superparamagnetic relaxometry (SPMR) is a novel nanoparticle imaging technique that utilizes the magnetic properties of biologically targeted superparamagnetic nanoparticles to potentially detect as few as 15,000 cancer cells. Source reconstruction in SPMR requires solving the ill-posed magnetic inverse problem. There is currently a gap in knowledge about how to solve this inverse problem in order to determine which of the many possible solutions represents the true location of bound particles. The long-term goal of this project is to translate SPMR into the clinic as an early detection technique for cancer. The objective for this project is to develop an algorithm that can reconstruct the location of cancer-bound nanoparticles in 3 dimensions without any prior knowledge of the number of sites with bound particles. The hypothesis of the work is that a sparse reconstruction algorithm based on physics models and tuned to the SPMR environment will reliably reconstruct the 3-dimensional distribution of cancer-bound nanoparticles. We plan to test this hypothesis with these specific aims: Specific Aim 1: Develop an experimentally informed forward model. The forward model for the sparse reconstruction algorithm will be based on the application of the Biot-Savart law to the physical conditions of the MRX device. The model will then be adjusted to best simulate data collected from the device. Specific Aim 2: Apply and characterize the performance of the inverse algorithm. A sparse reconstruction algorithm will be implemented to reconstruct the distribution of particles from the signal returned by the detectors. The sensitivity, resolution and accuracy of the algorithm across a range of environmental and user-defined variables will then be characterized and optimized. The expected outcome of these aims is a novel reconstruction algorithm that will significantly improve source localization and quantification in magnetic relaxometry. The development of a robust and well characterized reconstruction method will positively impact the field of SPMR by opening it up to possible applications in image guidance and novel early detection techniques. The knowledge that gained of the minimum detectability of the algorithm and the characterization of its response with respect to environmental noise and optimization parameters will inform the design of future experiments towards preclinical studies. The robust reconstruction algorithm developed by this project will bring this novel technology one step closer to realizing its potential to detect early disease with unparalleled sensitivity and specificity.

项目摘要 超顺磁弛豫法（SPMR）是一种新型的纳米颗粒成像技术， 生物靶向超顺磁性纳米颗粒的磁性， 一万五千个癌细胞SPMR源场重建需要求解病态的磁反问题。 目前，关于如何解决该逆问题以确定 许多可能的解代表了结合粒子的真实位置。这个项目的长期目标是 是将SPMR作为癌症的早期检测技术应用于临床。该项目的目标是 开发一种算法，可以在三维空间中重建与癌症结合的纳米颗粒的位置， 而不需要任何关于具有结合颗粒的位点数目的先验知识。这项工作的假设是， 基于物理模型并调整到SPMR环境的稀疏重建算法将可靠地 重建癌症结合纳米颗粒的三维分布。我们计划用 这些具体目标：具体目标1：开发一个基于实验的前向模型。前向 稀疏重建算法的模型将基于Biot-Savart定律对 MRX器械的物理条件。然后将调整模型，以最佳模拟从 设备.具体目标2：应用并表征逆算法的性能。稀疏 将实施重建算法以从返回的信号重建颗粒的分布 通过探测器。该算法的灵敏度、分辨率和准确度在一系列环境和 然后将对用户定义的变量进行表征和优化。这些目标的预期结果是 一种新的重建算法，将显着改善磁源定位和量化 弛豫测量法一个强大的和良好的重建方法的发展将产生积极的影响， SPMR领域，使其在图像引导和新的早期检测中有可能应用 技术.获得的算法最小可检测性的知识和表征 它对环境噪声的响应和优化参数将为未来的设计提供信息。 实验转向临床前研究。该项目开发的鲁棒重建算法将 使这项新技术更接近于实现其以无与伦比的速度检测早期疾病的潜力。 敏感性和特异性。

项目成果

A compressed sensing approach to immobilized nanoparticle localization for superparamagnetic relaxometry.

用于超顺磁弛豫测量的固定纳米粒子定位的压缩传感方法。

• DOI: 10.1088/1361-6560/ab3c06
• 发表时间: 2019
• 期刊: Physics in medicine and biology
• 影响因子: 3.5
• 作者: Thrower,SL;Kandala,SK;Fuentes,D;Stefan,W;Sowko,N;Huang,M;Mathieu,K;Hazle,JD
• 通讯作者: Hazle,JD