Adaptive regularized method based on homotopy for sparse fluorescence tomography.

Determining an appropriate regularization parameter is often challenging work because it has a narrow range and varies with problems, which is likely to lead to large reconstruction errors. In this contribution, an adaptive regularized method based on homotopy is presented for sparse fluorescence tomography reconstruction. Due to the adaptive regularization strategy, the proposed method is always able to reconstruct sources accurately independent of the estimation of the regularization parameter. Moreover, the proposed method is about two orders of magnitude faster than the two contrasting methods. Numerical and in vivo mouse experiments have been employed to validate the robustness and efficiency of the proposed method.

Early detection of liver cancer based on bioluminescence tomography.

As a new modality of molecular imaging, bioluminescence imaging has been widely used in tumor detection and drug evaluation. However, BLI cannot present the depth of information for internal diseases such as a liver tumor in situ or a lung tumor in situ. In this paper, we describe a bioluminescence tomography (BLT) method based on the bioluminescent intensity attenuation calibration and applied it to the early detection of liver cancer in situ. In comparison with BLT without calibration, this method could improve the reconstruction accuracy by more than 10%. In comparison with micro-computed tomography and other traditional imaging modalities, this method can detect a liver tumor at a very early stage and provide reliable location information.

Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method.

Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction. Some innovative strategies including subspace projection, the bottom-up sparsity adaptive approach, and backtracking technique are associated with the SASP method, which guarantees the accuracy, efficiency, and robustness for FMT reconstruction. Three numerical experiments based on a mouse-mimicking heterogeneous phantom have been performed to validate the feasibility of the SASP method. The results show that the proposed SASP method can achieve satisfactory source localization with a bias less than 1mm; the efficiency of the method is much faster than mainstream reconstruction methods; and this approach is robust even under quite ill-posed condition. Furthermore, we have applied this method to an in vivo mouse model, and the results demonstrate the feasibility of the practical FMT application with the SASP method.

Comprehensive evaluation of the anti-angiogenic and anti-neoplastic effects of Endostar on liver cancer through optical molecular imaging.

Molecular imaging enables non-invasive monitoring of tumor growth, progression, and drug treatment response, and it has become an important tool to promote biological studies in recent years. In this study, we comprehensively evaluated the in vivo anti-angiogenic and anti-neoplastic effects of Endostar on liver cancer based on the optical molecular imaging systems including micro-computer tomography (Micro-CT), bioluminescence molecular imaging (BLI) and fluorescence molecular tomography (FMT). Firefly luciferase (fLuc) and green fluorescent protein (GFP) dual labeled human hepatocellular carcinoma cells (HCC-LM3-fLuc-GFP cells) were used to establish the subcutaneous and orthotopic liver tumor model. After the tumor cells were implanted 14∼18 days, Endostar (5 mg/kg/day) was administered through an intravenous tail vein injection for continuous 14 days. The computer tomography angiography (CTA) and BLI were carried out for the subcutaneous tumor model. FMT was executed for the orthotopic tumor model. The CTA data showed that tumor vessel formation and the peritumoral vasculature of subcutaneous tumor in the Endostar treatment group was significantly inhibited compared to the control group. The BLI data exhibited the obvious tumor inhibition day 8 post-treatment. The FMT detected the tumor suppression effects of Endostar as early as day 4 post-treatment and measured the tumor location. The above data confirmed the effects of Endostar on anti-angiogenesis and tumor suppression on liver cancer. Our system combined CTA, BLI, and FMT to offer more comprehensive information about the effects of Endostar on the suppression of vessel and tumor formation. Optical molecular imaging system enabled the non-invasive and reliable assessment of anti-tumor drug efficacy on liver cancer.

Novel registration for microcomputed tomography and bioluminescence imaging based on iterated optimal projection.

As a high-sensitivity imaging modality, bioluminescence tomography can reconstruct the three-dimensional (3-D) location of an internal luminescent source based on the 3-D surface light distribution. However, we can only get the multi-orientation two-dimensional (2-D) bioluminescence distribution in the experiments. Therefore, developing an accurate universal registration method is essential for following bioluminescent source reconstruction. We can then map the multi-orientation 2-D bioluminescence distribution to the 3-D surface derived from anatomical information with it. We propose a 2-D -to-3-D registration method based on iterated optimal projection and applied it in a registration and reconstruction study of three transgenic mice. Compared with traditional registration methods based on the fixed points, our method was independent of the markers and the registration accuracy of the three experiments was improved by 0.3, 0.5, and 0.4 pixels, respectively. In addition, based on the above two registration results using the two registration methods, we reconstructed the 3-D location of the inner bioluminescent source in the three transgenic mice. The reconstruction results showed that the average error distance between the center of the reconstructed element and the center of the real element were reduced by 0.32, 0.48, and 0.39 mm, respectively.

Detection of mouse liver cancer via a parallel iterative shrinkage method in hybrid optical/microcomputed tomography imaging.

Liver cancer is one of the most common malignant tumors worldwide. In order to enable the noninvasive detection of small liver tumors in mice, we present a parallel iterative shrinkage (PIS) algorithm for dual-modality tomography. It takes advantage of microcomputed tomography and multiview bioluminescence imaging, providing anatomical structure and bioluminescence intensity information to reconstruct the size and location of tumors. By incorporating prior knowledge of signal sparsity, we associate some mathematical strategies including specific smooth convex approximation, an iterative shrinkage operator, and affine subspace with the PIS method, which guarantees the accuracy, efficiency, and reliability for three-dimensional reconstruction. Then an in vivo experiment on the bead-implanted mouse has been performed to validate the feasibility of this method. The findings indicate that a tiny lesion less than 3 mm in diameter can be localized with a position bias no more than 1 mm; the computational efficiency is one to three orders of magnitude faster than the existing algorithms; this approach is robust to the different regularization parameters and the lp norms. Finally, we have applied this algorithm to another in vivo experiment on an HCCLM3 orthotopic xenograft mouse model, which suggests the PIS method holds the promise for practical applications of whole-body cancer detection.