A compressed sensing approach to immobilized nanoparticle localization for superparamagnetic relaxometry.
A compressed sensing approach to immobilized nanoparticle localization for superparamagnetic relaxometry.
复制标题
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
复制
发表时间：
2019
影响因子：
3.5
通讯作者：
Hazle,JD
中科院分区：
文献类型：
--
作者：
Thrower,SL;Kandala,SK;Fuentes,D;Stefan,W;Sowko,N;Huang,M;Mathieu,K;Hazle,JD
超顺磁性弛豫法（SPMR）利用靶向超顺磁性氧化铁纳米颗粒（SPIO）的独特磁性来检测少量癌细胞。癌症结合的纳米颗粒的空间分布的重建需要解决一个不适定的逆问题。目前的方法，多源分析（MSA），使用最小二乘拟合来确定预定数量的磁偶极子的强度和位置。在这个概念验证的研究中，我们提出了一个稀疏平均重加权算法（SARA）的体积重建的固定化纳米粒子分布的应用。我们首先校准的参数，定义的位置的传感器在测量物理的前向模型。使用这个优化的模型，我们评估了各种配置的单点源和多点源幻影的算法的性能。我们研究了数据保真度参数，体素的大小，和迭代重加权重建产生的SARA的效果。我们发现，校准的物理模型可以预测的检测到的字段值的测量数据的5%以内。当仅存在单一来源时，两种算法都能够检测到低至0.5 µg的固定化颗粒。然而，当同时测量两个来源时，MSA未能检测到含有多达10 µg颗粒的来源，而SARA检测到含有至少5 µg颗粒的所有来源。我们表明，一个合适的数据保真度参数可以客观地选择，和总的振幅和位置的点源重建的SARA是不敏感的体素大小。检测和定位多个小的纳米颗粒簇是基于SPMR的诊断应用中的关键步骤。我们的算法克服了需要知道重建前的偶极子的数量，并提高了重建的灵敏度时，存在多个源。
Superparamagnetic relaxometry (SPMR) exploits the unique magnetic properties of targeted superparamagnetic iron oxide nanoparticles (SPIOs) to detect small numbers of cancer cells. Reconstruction of the spatial distribution of cancer-bound nanoparticles requires solving an ill-posed inverse problem. The current method, multiple source analysis (MSA), uses a least-squares fit to determine the strength and location of a pre-determined number of magnetic dipoles. In this proof-of-concept study, we propose the application of a sparsity averaged reweighting algorithm (SARA) for volumetric reconstruction of immobilized nanoparticle distributions. We first calibrate the parameters that define the location of the sensors in the forward model of measurement physics. Using this optimized model, we evaluated the performance of the algorithms on various configurations of single and multiple point-source phantoms. We investigated the effect of the data fidelity parameter, voxel size, and iterative reweighting on the reconstruction produced by SARA. We found that the calibrated physics model can predict the detected field values within 5% of the measured data. When only a single source was present, both algorithms were able to detect as little as 0.5 µg of immobilized particles. However, when two sources were measured simultaneously, MSA failed to detect sources containing as much as 10 µg of particles, while SARA detected all of the sources containing at least 5 µg of particles. We show that a suitable data fidelity parameter can be selected objectively, and the total magnitude and location of a point source reconstructed by SARA is not sensitive to voxel size. Detection and localization of multiple small clusters of nanoparticles is a crucial step in SPMR-based diagnostic applications. Our algorithm overcomes the need to know the number of dipoles before reconstruction and improves the sensitivity of the reconstruction when multiple sources are present.