Unmixing multiple adjacent fluorescent targets with multispectral excited fluorescence molecular tomography.

Fluorescence molecular tomography (FMT) can visualize biological activities at cellular and molecular levels in vivo, and has been extensively used in drug delivery and tumor detection research of small animals. The ill-posedness of the FMT inverse problem makes it difficult to reconstruct and unmix multiple adjacent fluorescent targets that have different functional features but are labeled with the same fluorochrome. A method based on independent component analysis for multispectral excited FMT was proposed in our previous study. It showed that double fluorescent targets with certain edge-to-edge distance (EED) could be unmixed by the method. In this study, the situation is promoted to unmix multiple adjacent fluorescent targets (i.e., more than two fluorescent targets and EED=0). Phantom experiments on the resolving ability of the proposed algorithm demonstrate that the algorithm performs well in unmixing multiple adjacent fluorescent targets in both lateral and axial directions. And also, we recovered the locational information of each independent fluorescent target and described the variable trends of the corresponding fluorescent targets under the excitation spectrum. This method is capable of unmixing multiple fluorescent targets with small EED but labeled with the same fluorochrome, and may be used in imaging of nonspecific probe targeting and metabolism of drugs.

Effects of temperature on multiparametric evaluation of hindlimb ischemia with dynamic fluorescence imaging.

Quantitative evaluation of hindlimb ischemia is essential for early diagnosis and therapy of peripheral arterial disease (PAD). Dynamic imaging using near-infrared (NIR) fluorophore indocyanine green (ICG) is a noninvasive and effective tool to monitor multiple vascular parameters including perfusion rate (PR), perfusion vascular density (PVD) and hemodynamics. It has been previously demonstrated that temperature changes could lead to significant variations of blood flow rate and vascular perfusion. In this paper, multiparametric evaluation of hindlimb ischemia was performed at different temperatures. Five different parameters were extracted from dynamic fluorescence imaging, including PR, PVD, rising time (Trise ), blood flow index (BFI) and mean fluorescence intensity (MFI). Temperatures varied from 15 °C to 40 °C were set on a mouse model of hindlimb ischemia. The aforementioned five parameters were obtained at each temperature. The results suggest that PVD, BFI and MFI could be effective indicators to distinguish ischemic tissues from normal tissues in mouse hindlimb at different temperatures. In contrast, PR is effective only when the temperature is higher than 25 °C, while Trise is effective only when the temperature is lower than 35 °C. The parameters of PVD, BFI and MFI could provide quantitative and comprehensive evaluation for PAD at different temperatures. (A) Bright-field image of the normal (left) and ischemic (right) hindlimbs. (B-D) Parametric images of perfusion vascular density, blood flow index and mean fluorescence intensity.

Multiparametric evaluation of hindlimb ischemia using time-series indocyanine green fluorescence imaging.

Peripheral arterial disease (PAD) can further cause lower limb ischemia. Quantitative evaluation of the vascular perfusion in the ischemic limb contributes to diagnosis of PAD and preclinical development of new drug. In vivo time-series indocyanine green (ICG) fluorescence imaging can noninvasively monitor blood flow and has a deep tissue penetration. The perfusion rate estimated from the time-series ICG images is not enough for the evaluation of hindlimb ischemia. The information relevant to the vascular density is also important, because angiogenesis is an essential mechanism for post-ischemic recovery. In this paper, a multiparametric evaluation method is proposed for simultaneous estimation of multiple vascular perfusion parameters, including not only the perfusion rate but also the vascular perfusion density and the time-varying ICG concentration in veins. The target method is based on a mathematical model of ICG pharmacokinetics in the mouse hindlimb. The regression analysis performed on the time-series ICG images obtained from a dynamic reflectance fluorescence imaging system. The results demonstrate that the estimated multiple parameters are effective to quantitatively evaluate the vascular perfusion and distinguish hypo-perfused tissues from well-perfused tissues in the mouse hindlimb. The proposed multiparametric evaluation method could be useful for PAD diagnosis. The estimated perfusion rate and vascular perfusion density maps (left) and the time-varying ICG concentration in veins of the ankle region (right) of the normal and ischemic hindlimbs.

Iterative Correction Scheme Based on Discrete Cosine Transform and L1 Regularization for Fluorescence Molecular Tomography With Background Fluorescence.

GOAL: High-intensity background fluorescence is generally encountered in fluorescence molecular tomography (FMT), because of the accumulation of fluorescent probes in nontarget tissues or the existence of autofluorescence in biological tissues. The reconstruction results are affected or even distorted by the background fluorescence, especially when the distribution of fluorescent targets is relatively sparse. The purpose of this paper is to reduce the negative effect of background fluorescence on FMT reconstruction. METHODS: After each iteration of the Tikhonov regularization algorithm, 3-D discrete cosine transform is adopted to filter the intermediate results. And then, a sparsity constraint step based on L1 regularization is applied to restrain the energy of the objective function. RESULTS: Phantom experiments with different fluorescence intensities of homogeneous and heterogeneous background are carried out to validate the performance of the proposed scheme. The results show that the reconstruction quality can be improved with the proposed iterative correction scheme. CONCLUSION AND SIGNIFICANCE: The influence of background fluorescence in FMT can be reduced effectively because of the filtering of the intermediate results, the detail preservation, and noise suppression of L1 regularization.

Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis.

It is a challenging problem to resolve and identify drug (or non-specific fluorophore) distribution throughout the whole body of small animals in vivo. In this article, an algorithm of unmixing multispectral fluorescence tomography (MFT) images based on independent component analysis (ICA) is proposed to solve this problem. ICA is used to unmix the data matrix assembled by the reconstruction results from MFT. Then the independent components (ICs) that represent spatial structures and the corresponding spectrum courses (SCs) which are associated with spectral variations can be obtained. By combining the ICs with SCs, the recovered MFT images can be generated and fluorophore concentration can be calculated. Simulation studies, phantom experiments and animal experiments with different concentration contrasts and spectrum combinations are performed to test the performance of the proposed algorithm. Results demonstrate that the proposed algorithm can not only provide the spatial information of fluorophores, but also recover the actual reconstruction of MFT images.