Adaptive regularized method based on homotopy for sparse fluorescence tomography

An Artificial Intelligent Signal Amplification System for in vivo Detection of miRNA

MicroRNAs (miRNA) have been identified as oncogenic drivers and tumor suppressors in every major cancer type. In this work, we design an artificial intelligent signal amplification (AISA) system including double-stranded SQ (S, signal strand; Q, quencher strand) and FP (F, fuel strand; P, protect strand) according to thermodynamics principle for sensitive detection of miRNA in vitro and in vivo. In this AISA system for miRNA detection, strand S carries a quenched imaging marker inside the SQ. Target miRNA is constantly replaced by a reaction intermediate and circulatively participates in the reaction, similar to enzyme. Therefore, abundant fluorescent substances from S and SP are dissociated from excessive SQ for in vitro and in vivo visualization. The versatility and feasibility for disease diagnosis using this system were demonstrated by constructing two types of AISA system to detect Hsa-miR-484 and Hsa-miR-100, respectively. The minimum target concentration detected by the system in vitro (10 min after mixing) was 1/10th that of the control group. The precancerous lesions of liver cancer were diagnosed, and the detection accuracy were larger than 94% both in terms of location and concentration. The ability to establish this design framework for AISA system with high specificity provides a new way to monitor tumor progression and to assess therapeutic responses.

A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing

Fluorescence molecular tomography (FMT) is a promising tool for real time in vivo quantification of neurotransmission (NT) as we pursue in our BRAIN initiative effort. However, the acquired image data are noisy and the reconstruction problem is ill-posed. Further, while spatial sparsity of the NT effects could be exploited, traditional compressive-sensing methods cannot be directly applied as the system matrix in FMT is highly coherent. To overcome these issues, we propose and assess a three-step reconstruction method. First, truncated singular value decomposition is applied on the data to reduce matrix coherence. The resultant image data are input to a homotopy-based reconstruction strategy that exploits sparsity via ℓ₁ regularization. The reconstructed image is then input to a maximum-likelihood expectation maximization (MLEM) algorithm that retains the sparseness of the input estimate and improves upon the quantitation by accurate Poisson noise modeling. The proposed reconstruction method was evaluated in a three-dimensional simulated setup with fluorescent sources in a cuboidal scattering medium with optical properties simulating human brain cortex (reduced scattering coefficient: 9.2 cm^-1, absorption coefficient: 0.1 cm^-1) and tomographic measurements made using pixelated detectors. In different experiments, fluorescent sources of varying size and intensity were simulated. The proposed reconstruction method provided accurate estimates of the fluorescent source intensity, with a 20% lower root mean square error on average compared to the pure-homotopy method for all considered source intensities and sizes. Further, compared with conventional ℓ₂ regularized algorithm, overall, the proposed method reconstructed substantially more accurate fluorescence distribution. The proposed method shows considerable promise and will be tested using more realistic simulations and experimental setups.

Enhanced immunotherapy of SM5-1 in hepatocellular carcinoma by conjugating with gold nanoparticles and its in vivo bioluminescence tomographic evaluation

SM5-1 is a humanized mouse monoclonal antibody, targeting an over-expressed membrane protein of approximately 230 kDa in hepatocellular carcinoma (HCC). SM5-1 can be used for target therapy in hepatocellular carinoma due to its ability of inhibiting cell growth and inducing apoptosis. However, the tumor inhibition efficacy of SM5-1 in HCC cancer treatment remains low. In this study, we synthesized SM5-1-conjugated gold nanoparticles (Au-SM5-1 NPs) and investigated their anticancer efficacy in HCC both in vitro and in vivo. The tumor inhibition rates of Au-SM5-1 NPs for subcutaneous tumor mice were 40.10% ± 4.34%, 31.37% ± 5.12%, and 30.63% ± 4.87% on day 12, 18, and 24 post-treatment as determined by bioluminescent intensity. In addition, we investigated the antitumor efficacy of Au-SM5-1 NPs in orthotopic HCC tumor models. The results showed that the inhibition rates of Au-SM5-1 NPs can reach up to 39.64% ± 4.87% on day 31 post-treatment determined by the bioluminescent intensity of the abdomen in tumor-bearing mice. Furthermore, three-dimensional reconstruction results of the orthotopic tumor revealed that Au-SM5-1 NPs significantly inhibited tumor growth compared with SM5-1 alone. Our results suggested that the developed Au-SM5-1 NPs has great potential as an antibody-based nano-drug for HCC therapy.

Reconstruction algorithm for fluorescence molecular tomography using sorted L-one penalized estimation

Fluorescence molecular tomography (FMT) has been a promising imaging tool that provides convenience for accurate localization and quantitative analysis of the fluorescent probe. In this study, we present a reconstruction method combining sorted L-one penalized estimation with an iterative-shrinking permissible region strategy to reconstruct fluorescence targets. Both numerical simulation experiments on a three-dimensional digital mouse model and physical experiments on a cubic phantom were carried out to validate the accuracy, effectiveness, and robustness of the proposed method. The results indicate that the proposed method can produce better location and satisfactory fluorescent yield with computational efficiency, which makes it a practical and promising reconstruction method for FMT.

Improved sparse reconstruction for fluorescence molecular tomography with L1/2 regularization

Fluorescence molecular tomography (FMT) is a promising imaging technique that allows in vivo visualization of molecular-level events associated with disease progression and treatment response. Accurate and efficient 3D reconstruction algorithms will facilitate the wide-use of FMT in preclinical research. Here, we utilize L1/2-norm regularization for improving FMT reconstruction. To efficiently solve the nonconvex L1/2-norm penalized problem, we transform it into a weighted L1-norm minimization problem and employ a homotopy-based iterative reweighting algorithm to recover small fluorescent targets. Both simulations on heterogeneous mouse model and in vivo experiments demonstrated that the proposed L1/2-norm method outperformed the comparative L1-norm reconstruction methods in terms of location accuracy, spatial resolution and quantitation of fluorescent yield. Furthermore, simulation analysis showed the robustness of the proposed method, under different levels of measurement noise and number of excitation sources.

Localizing fluorophore (centroid) inside a scattering medium by depth perturbation

Fluorescence molecular tomography (FMT) imaging can be used to determine the location, size, and biodistribution of fluorophore biomarkers inside tissues. Yet when using FMT in the reflectance geometry it is challenging to accurately localize fluorophores. A depth perturbation method is proposed to determine the centroid of fluorophore inside a tissue-like medium. Through superposition of a known thin optical phantom onto the medium surface, the fluorophore depth is deliberately perturbed and signal localization is improved in a stable way. We hypothesize that the fluorophore centroid can be better localized through use of this fluorescent intensity variation resulting from the depth perturbation. This hypothesis was tested in tissue-like phantoms. The results show that a small-size fluorophore inclusion (1.2 mm(3)volume, depth up to 4.8 mm) can be localized by the method with an error of 0.2 to 0.3 mm. The method is also proven to be capable of handling multiple fluorescent inclusion conditions with the assistance of other strategies. Additionally, our further studies showed that the method's performance in the presence of background fluorophores indicated that the small inclusion could be located at a 1.8 (3.8) mm depth with accurate localization only when its concentration was not <10 (100) times the background level.

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.