Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing, China.
Tsinghua University, School of Medicine, Department of Biomedical Engineering, Beijing, ChinabTsinghua University, Center for Biomedical Imaging Research, Beijing, China.
J Biomed Opt. 2017 Apr 1;22(4):46003. doi: 10.1117/1.JBO.22.4.046003.
Imaging of the pharmacokinetic parameters in dynamic fluorescence molecular tomography (DFMT) can provide three-dimensional metabolic information for biological studies and drug development. However, owing to the ill-posed nature of the FMT inverse problem, the relatively low quality of the parametric images makes it difficult to investigate the different metabolic processes of the fluorescent targets with small distances. An excitation-resolved multispectral DFMT method is proposed; it is based on the fact that the fluorescent targets with different concentrations show different variations in the excitation spectral domain and can be considered independent signal sources. With an independent component analysis method, the spatial locations of different fluorescent targets can be decomposed, and the fluorescent yields of the targets at different time points can be recovered. Therefore, the metabolic process of each component can be independently investigated. Simulations and phantom experiments are carried out to evaluate the performance of the proposed method. The results demonstrated that the proposed excitation-resolved multispectral method can effectively improve the reconstruction accuracy of the parametric images in DFMT.
动态荧光分子断层成像（DFMT）中药物代谢动力学参数的成像可以为生物研究和药物开发提供三维代谢信息。然而，由于 FMT 反问题的不适定性，相对较差的参数图像质量使得难以研究具有较小距离的荧光靶标之间的不同代谢过程。提出了一种基于激发分辨的多光谱 DFMT 方法，它基于这样一个事实，即具有不同浓度的荧光靶标在激发光谱域中表现出不同的变化，可以被视为独立的信号源。使用独立成分分析方法，可以分解不同荧光靶标的空间位置，并恢复目标在不同时间点的荧光产率。因此，可以独立研究每个组件的代谢过程。进行了模拟和体模实验来评估所提出方法的性能。结果表明，所提出的激发分辨多光谱方法可以有效地提高 DFMT 中参数图像的重建准确性。
