Abstract
Combining Fluorescent Molecular Tomography (FMT) with anatomical imaging, e.g. MRI facilitates interpreting functional information. Furthermore, using a heterogeneous model for light propagation has been shown in simulations to be superior to homogeneous modeling to quantify fluorescence. Here, we present a combined FMT-MRI system and apply it to heart and aorta molecular imaging, a challenging area due to strong tissue heterogeneity and the presence of air-voids due to lungs. First investigating performance in a phantom and mouse corpse, the MRI-enabled heterogeneous models resulted in an improved quantification of fluorescence reconstructions. The system was then used in mice for in vivo atherosclerosis molecular imaging. Results show that, when using the heterogeneous model, reconstructions were in agreement with the ex vivo measurements. Therefore, the proposed system might serve as a powerful imaging tool for atherosclerosis in mice.
Highlights
One of the advantages of combining fluorescence molecular tomography (FMT) with anatomical imaging is anatomical guidance for an improved quantification of reconstructions [1,2,3,4,5,6]
Combining the high sensitivity of FMT with the high spatial resolution of MRI, a hybrid FMT-MRI system is expected to improve in vivo atherosclerosis imaging in small animals
Phantom experiments were used to evaluate the impact of heterogeneous modeling on the quantification of fluorescence reconstructions
Summary
One of the advantages of combining fluorescence molecular tomography (FMT) with anatomical imaging is anatomical guidance for an improved quantification of reconstructions [1,2,3,4,5,6]. It was demonstrated in simulations that homogeneous forward models might induce significant quantification errors in the reconstruction, which could be improved by propagating light in a heterogeneous model [9]. In this context, especially working with continuous wave (CW) mode, in which. Combining the high sensitivity of FMT with the high spatial resolution of MRI, a hybrid FMT-MRI system is expected to improve in vivo atherosclerosis imaging in small animals
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