Abstract
Cerenkov luminescence tomography (CLT) was developed to reconstruct a three-dimensional (3D) distribution of radioactive probes inside a living animal. Reconstruction methods are generally performed within a unique framework by searching for the optimum solution. However, the ill-posed aspect of the inverse problem usually results in the reconstruction being non-robust. In addition, the reconstructed result may not match reality since the difference between the highest and lowest uptakes of the resulting radiotracers may be considerably large, therefore the biological significance is lost. In this paper, based on the minimization of a conformance error, a probability method is proposed that consists of qualitative and quantitative modules. The proposed method first pinpoints the organ that contains the light source. Next, we developed a 0-1 linear optimization subject to a space constraint to model the CLT inverse problem, which was transformed into a forward problem by employing a region growing method to solve the optimization. After running through all of the elements used to grow the sources, a source sequence was obtained. Finally, the probability of each discrete node being the light source inside the organ was reconstructed. One numerical study and two in vivo experiments were conducted to verify the performance of the proposed algorithm, and comparisons were carried out using the hp-finite element method (hp-FEM). The results suggested that our proposed probability method was more robust and reasonable than hp-FEM.
Highlights
Molecular imaging was designed to visualize the qualitative or quantitative measurements of biological processes at the molecular or cellular levels in vivo [1, 2]
The conformance error is defined as ε = 1− cos < Φc, Φm >, where Φc and Φm represent the CSPD resulting from the reconstructed source and the measured surface photon density (MSPD) respectively
In the experiments of the bladder, when we took the entire region of interest (ROI) as the permissible region (PR) and performed the region growing method there, the resulting reconstructed source was changed from the bladder to adipose
Summary
Molecular imaging was designed to visualize the qualitative or quantitative measurements of biological processes at the molecular or cellular levels in vivo [1, 2]. CLT model was solved iteratively using a preconditioned conjugate gradient method with Tikhonov regularization (TR) for bioluminescence tomography (BLT) [18, 30] Because this assumption is not necessarily true, Hu et al performed a heterogeneous CLT reconstruction [20], in which the adaptive hp-finite element method (hp-FEM) [34], originally designed for BLT, was employed for CLT reconstruction. A permissible region (PR) is usually used as the a priori information to improve the robustness of the finite element method (FEM) for diffuse optics reconstruction. In [22], the authors presented a single photon emission computed tomography (SPECT)-guided reconstruction method for CLT, in which a priori information of the permissible source region from the SPECT imaging results was incorporated to enhance the robustness of the reconstruction. The outline of hp-FEM algorithm, where p-refinement and h-refinement are subdivisions of a tetrahedron
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