Fluorescence molecular tomography (FMT) is a powerful modality for resolving the three-dimensional (3D) distribution of fluorescent targets inside biological tissues. However, the inverse problem of the FMT is severely ill-posed due to the strong scattering effects of photons inside biological tissues. Previously, regularization-based methods have been widely used to mitigate the ill-posedness of FMT. Due to the complex iterative computation and time-consuming reconstruction process, the FMT remains an intractable challenge for achieving accurate and fast 3D reconstructions. In this work, we propose a multi-attention prior based residual encoder-decoder network (MAP-REDN) to perform FMT reconstruction. Firstly, the multi-attention mechanism can provide weighted a priori information to the fluorescence source, enabling MAP-REDN to effectively mitigate the ill-posedness and enhance the reconstruction accuracy. Secondly, since the direct reconstruction strategy is adopted, the complex iterative computation process in the traditional regularization-based algorithms can be avoided, thus tremendously accelerating the reconstruction process. The experimental results demonstrate the feasibility of the MAP-REDN in achieving accurate and fast FMT reconstruction.
Significance: Pharmacokinetic parametric images in dynamic fluorescence molecular tomography (FMT) can describe three-dimensional (3D) physiological and pathological information inside biological tissues, potentially providing quantitative assessment tools for biological research and drug development.
Aim:In vivo imaging of the liver tumor with pharmacokinetic parametric images from dynamic FMT based on the differences in metabolic properties of indocyanine green (ICG) between normal liver cells and tumor liver cells inside biological tissues.
Approach: First, an orthotopic liver tumor mouse model was constructed. Then, with the help of the FMT/computer tomography (CT) dual-modality imaging system and the direct reconstruction algorithm, 3D imaging of liver metabolic parameters in nude mice was achieved to distinguish liver tumors from normal tissues. Finally, pharmacokinetic parametric imaging results were validated against in vitro anatomical results.
Results: This letter demonstrates the ability of dynamic FMT to monitor the pharmacokinetic delivery of the fluorescent dye ICG in vivo, thus, enabling the distinction between normal and tumor tissues based on the pharmacokinetic parametric images derived from dynamic FMT.
Conclusions: Compared with CT structural imaging technology, dynamic FMT combined with compartmental modeling as an analytical method can obtain quantitative images of pharmacokinetic parameters, thus providing a more powerful research tool for organ function assessment, disease diagnosis and new drug development.
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