In vivo quantitative reconstruction studies of bioluminescence tomography: effects of peak-wavelength shift and model deviation

Cone-beam X-ray luminescence computed tomography based on MLEM with adaptive FISTA initial image

BACKGROUND AND OBJECTIVE

As an emerging dual-mode optical molecular imaging, cone-beam X-ray luminescence computed tomography (CB-XLCT) has shown potential in early tumor diagnosis and other applications with increased depth and little autofluorescence. However, due to the low transfer efficiency of PNPs to convert X-ray energy to visible or near-infrared (NIR) light and X-ray dose limitation, the signal to noise ratio of projections is quite low, making the quality of CB-XLCT relatively poor.

METHODS

To improve the reconstruction quality of low-counts CB-XLCT imaging, an adaptive reconstruction algorithm (named ADFISTA-MLEM) based on the maximum likelihood expectation estimation (MLEM) framework is proposed for CB-XLCT reconstruction from Poisson distributed projections. In the proposed framework, the image reconstructed by fast iterative shrinkage-thresholding algorithm (FISTA) is used as the initial image for MLEM iterations to improve reconstruction accuracy, in which both the projection noise model and the sparsity constraint of the image could be considered. For relative quantitative imaging, a specific normalization is applied to the projection data and system matrix. To determine the hyperparameter of FISTA, which may be different for different projections, an adaptive strategy (ADFISTA) is then designed for adaptive update of the hyperparameter with reconstructed image in each iteration.

RESULTS AND CONCLUSIONS

Results from numerical simulations and phantom experiments indicate that the proposed framework can obtain superior reconstruction accuracy in terms of contrast to noise ratio and shape similarity. In addition, high intensity-concentration linearity between different probe targets indicates its potential for quantitative CB-XLCT imaging.

Bayesian sparse-based reconstruction in bioluminescence tomography improves localization accuracy and reduces computational time

Bioluminescence tomography (BLT) provides fundamental insight into biological processes in vivo. To fully realize its potential, it is important to develop image reconstruction algorithms that accurately visualize and quantify the bioluminescence signals taking advantage of limited boundary measurements. In this study, a new 2-step reconstruction method for BLT is developed by taking advantage of the sparse a priori information of the light emission using multispectral measurements. The first step infers a wavelength-dependent prior by using all multi-wavelength measurements. The second step reconstructs the source distribution based on this developed prior. Simulation, phantom and in vivo results were performed to assess and compare the accuracy and the computational efficiency of this algorithm with conventional sparsity-promoting BLT reconstruction algorithms, and results indicate that the position errors are reduced from a few millimeters down to submillimeter, and reconstruction time is reduced by 3 orders of magnitude in most cases, to just under a few seconds. The recovery of single objects and multiple (2 and 3) small objects is simulated, and the recovery of images of a mouse phantom and an experimental animal with an existing luminescent source in the abdomen is demonstrated. Matlab code is available at https://github.com/jinchaofeng/code/tree/master.

Multi-atlas registration and adaptive hexahedral voxel discretization for fast bioluminescence tomography

Bioluminescence tomography (BLT) has been a valuable optical molecular imaging technique to non-invasively depict the cellular and molecular processes in living animals with high sensitivity and specificity. Due to the inherent ill-posedness of BLT, a priori information of anatomical structure is usually incorporated into the reconstruction. The structural information is usually provided by computed tomography (CT) or magnetic resonance imaging (MRI). In order to obtain better quantitative results, BLT reconstruction with heterogeneous tissues needs to segment the internal organs and discretize them into meshes with the finite element method (FEM). It is time-consuming and difficult to handle the segmentation and discretization problems. In this paper, we present a fast reconstruction method for BLT based on multi-atlas registration and adaptive voxel discretization to relieve the complicated data processing procedure involved in the hybrid BLT/CT system. A multi-atlas registration method is first adopted to estimate the internal organ distribution of the imaged animal. Then, the animal volume is adaptively discretized into hexahedral voxels, which are fed into FEM for the following BLT reconstruction. The proposed method is validated in both numerical simulation and an in vivo study. The results demonstrate that the proposed method can reconstruct the bioluminescence source efficiently with satisfactory accuracy.

Mechanistic molecular imaging of cardiac cell therapy for ischemic heart disease

Cell-based myocardial regeneration has emerged as a promising therapeutic option for ischemic heart disease, though not yet at the level of routine clinical utility. Despite the encouraging results from initial preclinical studies that have demonstrated improved function and reduced infarct size of the ischemic myocardium following several candidate cell transplantation, the beneficial effects and molecular mechanisms of cardiac cell therapy are still unclear in clinical applications to date, and much remains to be optimized. To improve engraftment, accurate methods are required for tracking cell fate and quantifying functional outcome. In the present review, we summarized the current status and challenges of cardiac cell therapy for ischemic heart disease and discussed the strengths and limitations of currently available in vivo imaging techniques with special focus on the newly developed multimodality approaches for assessing the efficacy of engrafted donor cells. We also addressed the hurdles these imaging modalities are facing, including issues regarding immunogenicity and tumorigenicity of transplanted stem cells, and provided some the future perspectives on stem cell imaging.

Adipose stromal cells amplify angiogenic signaling via the VEGF/mTOR/Akt pathway in a murine hindlimb ischemia model: a 3D multimodality imaging study

Although adipose-derived stromal cell (ADSC) transplantation has been demonstrated as a promising therapeutic strategy for peripheral arterial disease (PAD), the mechanism of action behind the observed therapeutic efficacy of ADSCs remains unclear. This study was designed to investigate the long-term outcome and therapeutic behavior of engrafted ADSCs in a murine hindlimb ischemia model using multimodality molecular imaging approaches. ADSCs (1.0×10⁷) were isolated from Tg(Fluc-egfp) mice which constitutively express dual-reporter firefly luciferase and enhanced green fluorescent protein (Fluc⁺-eGFP⁺, mADSCs^Fluc+GFP+), then intramuscularly injected into the hindlimb of BALB/c-nu mice after unilateral femoral artery ligation and excision. Abbreviated survival (∼5 weeks) of post-transplant mADSCs within the ischemic hindlimb was longitudinally monitored using noninvasive bioluminescence imaging (BLI), fluorescence imaging (FRI), and bioluminescence tomography with micro-computed tomography (BLT/micro-CT). Use of the BLT/micro-CT system enabled quantitative 3-dimensional (3D) imaging of the cells’ distribution and kinetics in vivo. Engrafted mADSCs improved blood perfusion recovery, ambulatory performance and prognosis of the ischemic hindlimb, probably by inducing angiogenesis and formation of collateral vessels, which could be visualized using laser Doppler perfusion imaging (LDPI), micro-CT angiography, vascular-cast imaging, and immunofluorescence. mADSCs augmented activation of the pro-angiogenic VEGF/mTOR/Akt pathway in vivo, even though the cells failed to incorporate into the host microvasculature as functional components. Downregulation of VEGF/mTOR/Akt signaling using small molecule inhibitors counteracted mADSC-induced angiogenesis and perfusion restoration. This study demonstrates for the first time the spatiotemporal kinetics and functional survival of transplanted mADSCs in a PAD model using in vivo 3D multimodality imaging. Our study indicates that mADSCs potentiate pro-angiogenic signal amplification via a VEGF/mTOR/Akt-dependent pathway, and thereby promote recovery from hindlimb ischemia.

Three-dimensional noninvasive monitoring iodine-131 uptake in the thyroid using a modified Cerenkov luminescence tomography approach

Background

Cerenkov luminescence tomography (CLT) provides the three-dimensional (3D) radiopharmaceutical biodistribution in small living animals, which is vital to biomedical imaging. However, existing single-spectral and multispectral methods are not very efficient and effective at reconstructing the distribution of the radionuclide tracer. In this paper, we present a semi-quantitative Cerenkov radiation spectral characteristic-based source reconstruction method named the hybrid spectral CLT, to efficiently reconstruct the radionuclide tracer with both encouraging reconstruction results and less acquisition and image reconstruction time.

Methodology/Principal Findings

We constructed the implantation mouse model implanted with a 400 µCi Na¹³¹I radioactive source and the physiological mouse model received an intravenous tail injection of 400 µCi radiopharmaceutical Iodine-131 (I-131) to validate the performance of the hybrid spectral CLT and compared the reconstruction results, acquisition, and image reconstruction time with that of single-spectral and multispectral CLT. Furthermore, we performed 3D noninvasive monitoring of I-131 uptake in the thyroid and quantified I-131 uptake in vivo using hybrid spectral CLT. Results showed that the reconstruction based on the hybrid spectral CLT was more accurate in localization and quantification than using single-spectral CLT, and was more efficient in the in vivo experiment compared with multispectral CLT. Additionally, 3D visualization of longitudinal observations suggested that the reconstructed energy of I-131 uptake in the thyroid increased with acquisition time and there was a robust correlation between the reconstructed energy versus the gamma ray counts of I-131 (). The ex vivo biodistribution experiment further confirmed the I-131 uptake in the thyroid for hybrid spectral CLT.

Conclusions/Significance

Results indicated that hybrid spectral CLT could be potentially used for thyroid imaging to evaluate its function and monitor its treatment for thyroid cancer.