Fluorescence Molecular Tomography Research Articles

An adaptive parameter selection strategy based on maximizing the probability of data for robust fluorescence molecular tomography reconstruction.

To alleviate the ill-posed of the inverse problem in fluorescent molecular tomography (FMT), many regularization methods based on L2 or L1 norm have been proposed. Whereas, the quality of regularization parameters affects the performance of the reconstruction algorithm. Some classical parameter selection strategies usually need initialization of parameter range and high computing costs, which is not universal in the practical application of FMT. In this paper, an universally applicable adaptive parameter selection method based on maximizing the probability of data (MPD) strategy was proposed. This strategy used maximum a posteriori (MAP) estimation and maximum likelihood (ML) estimation to establish a regularization parameters model. The stable optimal regularization parameters can be determined by multiple iterative estimates. Numerical simulations and in vivo experiments show that MPD strategy can obtain stable regularization parameters for both regularization algorithms based on L2 or L1 norm and achieve good reconstruction performance.

Preclinical Evaluation of CD36-Targeting Antiangiogenic Peptide ABT-510 for Near-Infrared Fluorescence Molecular Imaging of Colorectal Cancer.

Surgical resection constitutes the first choice of treatment for colorectal cancer (CRC). Despite advancements in intraoperative navigation, there remains a considerable lack of effective targeting probes for the imaging-guided surgical navigation of CRC owing to their high heterogeneity. Hence, developing a suitable fluorescent probe to detect the specific types of CRC populations is crucial. Herein, we labeled ABT-510, a small, CD36-targeting thrombospondin-1-mimetic peptide overexpressed in various cancer types, with fluorescein isothiocyanate or near-infrared dye MPA. We found that fluorescence-conjugated ABT-510 exhibited excellent selectivity and specificity toward cells or tissues with high CD36 expression. The tumor-to-colorectal signal ratios were 11.28 ± 0.61 (95% confidence interval) and 10.74 ± 0.07 (95% confidence interval) in subcutaneous HCT-116 and HT-29 tumor-bearing nude mice, respectively. Moreover, high signal contrast was observed in the orthotopic and liver metastatic CRC xenograft mouse models. Furthermore, MPA-PEG4-r-ABT-510 exhibited an antiangiogenic effect via tube information assay with human umbilical vein endothelial cells. Overall, MPA-PEG4-r-ABT-510 presents rapid and precise tumor delineation characteristics, thereby making it a desirable tool for CRC imaging and surgical navigation.

Reconstruction based on adaptive group least angle regression for fluorescence molecular tomography.

Fluorescence molecular tomography can combine two-dimensional fluorescence imaging with anatomical information to reconstruct three-dimensional images of tumors. Reconstruction based on traditional regularization with tumor sparsity priors does not take into account that tumor cells form clusters, so it performs poorly when multiple light sources are used. Here we describe reconstruction based on an "adaptive group least angle regression elastic net" (AGLEN) method, in which local spatial structure correlation and group sparsity are integrated with elastic net regularization, followed by least angle regression. The AGLEN method works iteratively using the residual vector and a median smoothing strategy in order to adaptively obtain a robust local optimum. The method was verified using numerical simulations as well as imaging of mice bearing liver or melanoma tumors. AGLEN reconstruction performed better than state-of-the-art methods with different sizes of light sources at different distances from the sample and in the presence of Gaussian noise at 5-25%. In addition, AGLEN-based reconstruction accurately imaged tumor expression of cell death ligand-1, which can guide immunotherapy.

Characterization of fluorescence lifetime of organic fluorophores for molecular imaging in the shortwave infrared window

SignificanceFluorescence lifetime imaging in the shortwave infrared (SWIR) is expected to enable high-resolution multiplexed molecular imaging in highly scattering tissue.AimTo characterize the brightness and fluorescence lifetime of commercially available organic SWIR fluorophores and benchmark them against the tail emission of conventional NIR-excited probes.ApproachCharacterization was performed through our established time-domain mesoscopic fluorescence molecular tomography system integrated around a time-correlated single-photon counting-single-photon avalanche diode array. Brightness and fluorescence lifetime were measured for NIR and SWIR probes >1000 nm. Simultaneous probe imaging was then performed to assess their potential for multiplexed studies.ResultsThe NIR probes outperformed SWIR probes in brightness while the mean fluorescence lifetimes of the SWIR probes were extremely short. The phantom study demonstrated the feasibility of lifetime multiplexing in the SWIR window with both NIR and SWIR probes.ConclusionsLong-tail emission of NIR probes outperformed the SWIR probes in brightness >1000 nm. Fluorescence lifetime was readily detectable in the SWIR window, where the SWIR probes showed shorter lifetimes compared to the NIR probes. We demonstrate the feasibility of lifetime multiplexing in the SWIR window, which paves the way for in vivo multiplexed studies of intact tissues at improved resolution.

Advances in Intravascular Ultrasound

Since its inception, intravascular ultrasound (IVUS) and optical coherence tomography (OCT) have played a significant role in evaluating the pathophysiology of coronary artery disease (CAD) guiding the interventional and medical management of CAD improving outcomes in patients. Although the benefits of each of these modalities have been proven, due to some limitations, no single intravascular imaging technique has been proven to provide a detailed and complete evaluation of all CAD lesions. The use of different intravascular imaging modalities sequentially may lead to complications, which are cumbersome, consume time, and add financial burden to the patient. Recently, hybrid imaging catheters that combine OCT and IVUS benefits have been developed to limit these problems. Intravascular imaging techniques we are using currently have some drawbacks that hinder accurate assessment of plaque morphology and pathobiology as demonstrated in many histological studies, causing difficulty in identifying high-risk plaques. To overcome these limitations, great efforts have been put into developing hybrid, dual-probe catheters by combining imaging modalities to get an accurate analysis of plaque characteristics, and high-risk lesions. At present, many dual-probe catheters are available including combined IVUS-OCT, near-infrared spectroscopy-IVUS that is available commercially, the OCT-near infrared fluorescence (NIRF) molecular imaging, IVUS-NIRF, and combined fluorescence lifetime-IVUS imaging. Application of this combined multimodal imaging in clinical practice overcomes the limitations of standalone imaging and helps in providing a comprehensive and accurate visualization of plaque characteristics, composition, and plaque biology. The present article summarizes the advances in hybrid intravascular imaging, analyses the technical hindrances that should be known to have a use in the different clinical circumstances, and the till date shreds of evidence available from their first clinical application aiming to bring these modalities into the limelight and their potential role in the study of CAD.

Robust transformed [formula omitted] metric for fluorescence molecular tomography

Background and Objective: Fluorescence molecular tomography (FMT) is a non-invasive molecular imaging modality that can be used to observe the three-dimensional distribution of fluorescent probes in vivo. FMT is a promising imaging technique in clinical and preclinical research that has attracted significant attention. Numerous regularization based reconstruction algorithms have been proposed. However, traditional algorithms that use the squared l2-norm distance usually exaggerate the influence of noise and measurement and calculation errors, and their robustness cannot be guaranteed.Methods: In this study, we propose a novel robust transformed l1 (TL1) metric that interpolates l0 and l1 norms through a nonnegative parameter α∈(0,+∞). The TL1 metric looks like the lp-norm with p∈(0,1). These are markedly different because TL1 metric has two properties, boundedness and Lipschitz-continuity, which make the TL1 criterion suitable distance metric, particularly for robustness, owing to its stronger noise suppression. Subsequently, we apply the proposed metric to FMT and build a robust model to reduce the influence of noise. The nonconvexity of the proposed model made direct optimization difficult, and a continuous optimization method was developed to solve the model. The problem was converted into a difference in convex programming problem for the TL1 metric (DCATL1), and the corresponding algorithm converged linearly.Results: Various numerical simulations and in vivo bead-implanted mouse experiments were conducted to verify the performance of the proposed method. The experimental results show that the DCATL1 algorithm is more robust than the state-of-the-art approaches and achieves better source localization and morphology recovery.Conclusions: The in vivo experiments showed that DCATL1 can be used to visualize the distribution of fluorescent probes inside biological tissues and promote preclinical application in small animals, demonstrating the feasibility and effectiveness of the proposed method.

In vivo active-targeting fluorescence molecular imaging with adaptive background fluorescence subtraction.

Using active tumor-targeting nanoparticles, fluorescence imaging can provide highly sensitive and specific tumor detection, and precisely guide radiation in translational radiotherapy study. However, the inevitable presence of non-specific nanoparticle uptake throughout the body can result in high levels of heterogeneous background fluorescence, which limits the detection sensitivity of fluorescence imaging and further complicates the early detection of small cancers. In this study, background fluorescence emanating from the baseline fluorophores was estimated from the distribution of excitation light transmitting through tissues, by using linear mean square error estimation. An adaptive masked-based background subtraction strategy was then implemented to selectively refine the background fluorescence subtraction. First, an in vivo experiment was performed on a mouse intratumorally injected with passively targeted fluorescent nanoparticles, to validate the reliability and robustness of the proposed method in a stringent situation wherein the target fluorescence was overlapped with the strong background. Then, we conducted in vivo studies on 10 mice which were inoculated with orthotopic breast tumors and intravenously injected with actively targeted fluorescent nanoparticles. Results demonstrated that active targeting combined with the proposed background subtraction method synergistically increased the accuracy of fluorescence molecular imaging, affording sensitive tumor detection.

Characterizing a photoacoustic and fluorescence imaging platform for preclinical murine longitudinal studies.

To effectively study preclinical animal models, medical imaging technology must be developed with a high enough resolution and sensitivity to perform anatomical, functional, and molecular assessments. Photoacoustic (PA) tomography provides high resolution and specificity, and fluorescence (FL) molecular tomography provides high sensitivity; the combination of these imaging modes will enable a wide range of research applications to be studied in small animals. We introduce and characterize a dual-modality PA and FL imaging platform using in vivo and phantom experiments. The imaging platform's detection limits were characterized through phantom studies that determined the PA spatial resolution, PA sensitivity, optical spatial resolution, and FL sensitivity. The system characterization yielded a PA spatial resolution of in the transverse plane and in the longitudinal axis, a PA sensitivity detection limit not less than that of a sample with absorption coefficient , an optical spatial resolution of in the vertical axis and in the horizontal axis, and a FL sensitivity detection limit not concentration of IR-800. The scanned animals displayed in three-dimensional renders showed high-resolution anatomical detail of organs. The combined PA and FL imaging system has been characterized and has demonstrated its ability to image mice in vivo, proving its suitability for biomedical imaging research applications.

NIR-II fluorescence imaging-guided colorectal cancer surgery targeting CEACAM5 by a nanobody.

Surgery is the cornerstone of colorectal cancer (CRC) treatment, yet complete removal of the tumour remains a challenge. The second near-infrared window (NIR-II, 1000-1700nm) fluorescent molecular imaging is a novel technique, which has broad application prospects in tumour surgical navigation. We aimed to evaluate the ability of CEACAM5-targeted probe for CRC recognition and the value of NIR-II imaging-guided CRC resection. We constructed the probe 2D5-IRDye800CW by conjugated anti-CEACAM5 nanobody (2D5) with near-infrared fluorescent dye IRDye800CW. The performance and benefits of 2D5-IRDye800CW at NIR-II were confirmed by imaging experiments in mouse vascular and capillary phantom. Then mouse colorectal cancer subcutaneous tumour model (n=15), orthotopic model (n=15), and peritoneal metastasis model (n=10) were constructed to investigate biodistribution of probe and imaging differences between NIR-I and NIR-II invivo, and then tumour resection was guided by NIR-II fluorescence. Fresh human colorectal cancer specimens were incubated with 2D5-IRDye800CW to verify its specific targeting ability. 2D5-IRDye800CW had an NIR-II fluorescence signal extending to 1600nm and bound specifically to CEACAM5 with an affinity of 2.29nM. Invivo imaging, 2D5-IRDye800CW accumulated rapidly in tumour (15 min) and could specifically identify orthotopic colorectal cancer and peritoneal metastases. All tumours were resected under NIR-II fluorescence guidance, even smaller than 2mm tumours were detected, and NIR-II had a higher tumour-to-background ratio than NIR-I (2.55±0.38, 1.94±0.20, respectively). 2D5-IRDye800CW could precisely identify CEACAM5-positive human colorectal cancer tissue. 2D5-IRDye800CW combined with NIR-II fluorescence has translational potential as an aid to improve R0 surgery of colorectal cancer. This study was supported by Beijing Natural Science Foundation(JQ19027), the National Key Research and Development Program of China (2017YFA0205200), National Natural Science Foundation of China (NSFC) (61971442, 62027901, 81930053, 92059207, 81227901, 82102236), Beijing Natural Science Foundation (L222054), CAS Youth Interdisciplinary Team (JCTD-2021-08), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16021200), the Zhuhai High-level Health Personnel Team Project (Zhuhai HLHPTP201703), the Fundamental Research Funds for the Central Universities (JKF-YG-22-B005) and Capital Clinical Characteristic Application Research (Z181100001718178). The authors would like to acknowledge the instrumental and technical support of the multi-modal biomedical imaging experimental platform, Institute of Automation, Chinese Academy of Sciences.

Visualization of cardiac uptake of bone marrow mesenchymal stem cell-derived extracellular vesicles after intramyocardial or intravenous injection in murine myocardial infarction.

In animal models, human bone marrow mesenchymal stem cell-derived extracellular vesicles (MSC-EV) have been found to have beneficial effects in cardiovascular disease, but only when administered via intramyocardial injection. The biodistribution of either intravenous or intramyocardial injection of MSC-EV in the presence of myocardial injury is uncharacterized at this time. We hypothesized that intramyocardial injection will ensure delivery of MSC-EV to the ischemic myocardium, while intravenous injection will not. Human bone marrow mesenchymal stem cells were cultured and the MSC-EV were isolated and characterized. The MSC-EVs were then labeled with DiD lipid dye. FVB mice with normal cardiac function underwent left coronary artery ligation followed by either peri-infarct intramyocardial or tail vein injection of 3*106 or 2*109 particles of DiD-labeled MSC-EV or a DiD-saline control. The heart, lungs, liver, spleen and kidneys were harvested 2h post-injection and were submitted for fluorescent molecular tomography imaging. Myocardial uptake of MSC-EV was only visualized after intramyocardial injection of 2*109 MSC-EV particles (p=0.01) compared to control, and there were no differences in cardiac fluorescence after tail vein injection of MSC-EV (p=0.5). There was no significantly detectable MSC-EV uptake in other organs after intramyocardial injection. After tail vein injection of 2*109 particles of MSC-EV, the liver (p=0.02) and spleen (p=0.04) appeared to have diffuse MSC-EV uptake compared to controls. Even in the presence of myocardial injury, only intramyocardial but not intravenous administration resulted in detectable levels of MSC-EV in the ischemic myocardium. This study confirms the role for intramyocardial injection in maximal and effective delivery of MSC-EV. Our ongoing studies aimed at developing bioengineered MSC-EV for targeted delivery to the heart may render MSC-EV clinically applicable for cardiovascular disease.

Activatable molecular fluorescence probes for the imaging and detection of ischemic stroke

The real-time, noninvasive, nonionizing, high spatiotemporal resolution, and flexibility characteristics of molecular fluorescence imaging provide a uniquely powerful approach to imaging and monitoring the physiology and pathophysiology of ischemic stroke. Currently, various fluorescence probes have been synthesized with the aim of improving quantitative and quantitative studies of the pathologic processes of ischemic stroke in living animals. In this review, we present an overview of current activatable fluorescence probes for the imaging and diagnosis of ischemic stroke in animal models. We categorize the probes based on their activatable signals from the biomarkers associated with ischemic stroke, and we present representative examples of their functional mechanisms. Finally, we briefly discuss future perspectives in this field.

Multi-target reconstruction strategy based on blind source separation of surface measurement signals in FMT.

Fluorescence molecular tomography (FMT) is a promising molecular imaging technique for tumor detection in the early stage. High-precision multi-target reconstructions are necessary for quantitative analysis in practical FMT applications. The existing reconstruction methods perform well in retrieving a single fluorescent target but may fail in reconstructing a multi-target, which remains an obstacle to the wider application of FMT. In this paper, a novel multi-target reconstruction strategy based on blind source separation (BSS) of surface measurement signals was proposed, which transformed the multi-target reconstruction problem into multiple single-target reconstruction problems. Firstly, by multiple points excitation, multiple groups of superimposed measurement signals conforming to the conditions of BSS were constructed. Secondly, an efficient nonnegative least-correlated component analysis with iterative volume maximization (nLCA-IVM) algorithm was applied to construct the separation matrix, and the superimposed measurement signals were separated into the measurements of each target. Thirdly, the least squares fitting method was combined with BSS to determine the number of fluorophores indirectly. Lastly, each target was reconstructed based on the extracted surface measurement signals. Numerical simulations and in vivo experiments proved that it has the ability of multi-target resolution for FMT. The encouraging results demonstrate the significant effectiveness and potential of our method for practical FMT applications.

Fluorescence molecular optomic signatures improve identification of tumors in head and neck specimens.

Fluorescence molecular imaging using ABY-029, an epidermal growth factor receptor (EGFR)-targeted, synthetic Affibody peptide labeled with a near-infrared fluorophore, is under investigation for surgical guidance during head and neck squamous cell carcinoma (HNSCC) resection. However, tumor-to-normal tissue contrast is confounded by intrinsic physiological limitations of heterogeneous EGFR expression and non-specific agent uptake. In this preliminary study, radiomic analysis was applied to optical ABY-029 fluorescence image data for HNSCC tissue classification through an approach termed "optomics." Optomics was employed to improve tumor identification by leveraging textural pattern differences in EGFR expression conveyed by fluorescence. The study objective was to compare the performance of conventional fluorescence intensity thresholding and optomics for binary classification of malignant vs. non-malignant HNSCC tissues. Fluorescence image data collected through a Phase 0 clinical trial of ABY-029 involved a total of 20,073 sub-image patches (size of 1.8 × 1.8 mm2) extracted from 24 bread-loafed slices of HNSCC surgical resections originating from 12 patients who were stratified into three dose groups (30, 90, and 171 nanomoles). Each dose group was randomly partitioned on the specimen-level 75%/25% into training/testing sets, then all training and testing sets were aggregated. A total of 1,472 standardized radiomic features were extracted from each patch and evaluated by minimum redundancy maximum relevance feature selection, and 25 top-ranked features were used to train a support vector machine (SVM) classifier. Predictive performance of the SVM classifier was compared to fluorescence intensity thresholding for classifying testing set image patches with histologically confirmed malignancy status. Optomics provided consistent improvement in prediction accuracy and false positive rate (FPR) and similar false negative rate (FNR) on all testing set slices, irrespective of dose, compared to fluorescence intensity thresholding (mean accuracies of 89% vs. 81%, P = 0.0072; mean FPRs of 12% vs. 21%, P = 0.0035; and mean FNRs of 13% vs. 17%, P = 0.35). Optomics outperformed conventional fluorescence intensity thresholding for tumor identification using sub-image patches as the unit of analysis. Optomics mitigate diagnostic uncertainties introduced through physiological variability, imaging agent dose, and inter-specimen biases of fluorescence molecular imaging by probing textural image information. This preliminary study provides a proof-of-concept that applying radiomics to fluorescence molecular imaging data offers a promising image analysis technique for cancer detection in fluorescence-guided surgery.

Robust reconstruction of fluorescence molecular tomography based on adaptive adversarial learning strategy

Objective. Fluorescence molecular tomography (FMT) is a promising molecular imaging modality for quantifying the three-dimensional (3D) distribution of tumor probes in small animals. However, traditional deep learning reconstruction methods that aim to minimize the mean squared error (MSE) and iterative regularization algorithms that rely on optimal parameters are typically influenced by strong noise, resulting in poor FMT reconstruction robustness. Approach. In this letter, we propose an adaptive adversarial learning strategy (3D-UR-WGAN) to achieve robust FMT reconstructions. Unlike the pixel-based MSE criterion in traditional CNNs or the regularization strategy in iterative solving schemes, the reconstruction strategy can greatly facilitate the performance of the network models through alternating loop training of the generator and the discriminator. Second, the reconstruction strategy combines the adversarial loss in GANs with the L1 loss to significantly enhance the robustness and preserve image details and textual information. Main results. Both numerical simulations and physical phantom experiments demonstrate that the 3D-UR-WGAN method can adaptively eliminate the effects of different noise levels on the reconstruction results, resulting in robust reconstructed images with reduced artifacts and enhanced image contrast. Compared with the state-of-the-art methods, the proposed method achieves better reconstruction performance in terms of target shape recovery and localization accuracy. Significance. This adaptive adversarial learning reconstruction strategy can provide a possible paradigm for robust reconstruction in complex environments, and also has great potential to provide an alternative solution for solving the problem of poor robustness encountered in other optical imaging modalities such as diffuse optical tomography, bioluminescence imaging, and Cherenkov luminescence imaging.

High-fidelity mesoscopic fluorescence molecular tomography based on SSB-Net.

The imaging fidelity of mesoscopic fluorescence molecular tomography (MFMT) in reflective geometry suffers from spatial nonuniformity of measurement sensitivity and ill-posed reconstruction. In this study, we present a spatially adaptive split Bregman network (SSB-Net) to simultaneously overcome the spatial nonuniformity of measurement sensitivity and promote reconstruction sparsity. The SSB-Net is derived by unfolding the split Bregman algorithm. In each layer of the SSB-Net, residual block and 3D convolution neural networks (3D-CNNs) can adaptively learn spatially nonuniform error compensation, the spatially dependent proximal operator, and sparsity transformation. Simulations and experiments show that the proposed SSB-Net enables high-fidelity MFMT reconstruction of multifluorophores at different positions within a depth of a few millimeters. Our method paves the way for a practical reflection-mode diffuse optical imaging technique.

Size-advantage of monovalent nanobodies against the macrophage mannose receptor for deep tumor penetration and tumor-associated macrophage targeting.

Rationale: Nanobodies (Nbs) have emerged as an elegant alternative to the use of conventional monoclonal antibodies in cancer therapy, but a detailed microscopic insight into the in vivo pharmacokinetics of different Nb formats in tumor-bearers is lacking. This is especially relevant for the recognition and targeting of pro-tumoral tumor-associated macrophages (TAMs), which may be located in less penetrable tumor regions. Methods: We employed anti-Macrophage Mannose Receptor (MMR) Nbs, in a monovalent (m) or bivalent (biv) format, to assess in vivo TAM targeting. Intravital and confocal microscopy were used to analyse the blood clearance rate and targeting kinetics of anti-MMR Nbs in tumor tissue, healthy muscle tissue and liver. Fluorescence Molecular Tomography was applied to confirm anti-MMR Nb accumulation in the primary tumor and in metastatic lesions. Results: Intravital microscopy demonstrated significant differences in the blood clearance rate and macrophage targeting kinetics of (m) and (biv)anti-MMR Nbs, both in tumoral and extra-tumoral tissue. Importantly, (m)anti-MMR Nbs are superior in reaching tissue macrophages, an advantage that is especially prominent in tumor tissue. The administration of a molar excess of unlabelled (biv)anti-MMR Nbs increased the (m)anti-MMR Nb bioavailability and impacted on its macrophage targeting kinetics, preventing their accumulation in extra-tumoral tissue (especially in the liver) but only partially influencing their interaction with TAMs. Finally, anti-MMR Nb administration not only allowed the visualization of TAMs in primary tumors, but also at a distant metastatic site. Conclusions: These data describe, for the first time, a microscopic analysis of (m) and (biv)anti-MMR Nb pharmacokinetics in tumor and healthy tissues. The concepts proposed in this study provide important knowledge for the future use of Nbs as diagnostic and therapeutic agents, especially for the targeting of tumor-infiltrating immune cells.

High-Resolution Reconstruction of FMT Based on Elastic Net Optimized by Relaxed ADMM.

Fluorescence Molecular Tomography (FMT), providing thethree-dimensional fluorescent distribution information of specific molecular probes in tumors, is widely applied to detect in vivo tumors. However, the ill-posedness of reconstruction greatly affects the resolution of FMT. Traditional methods have introduced different regularization terms to solve this problem, but there are still challenges for the high-resolution reconstruction of small tumors under complex conditions. In this paper, we proposed an elastic net method optimized by the relaxed Alternating Direction Method of Multipliers (EN-RADMM) to improve the reconstruction resolution for small tumors. The objective function consisted of the Least-Square term and elastic net regularization. Relaxation, equivalent deformation directing at ill-posed equations, and LU decomposition were applied to accelerate algorithm convergence and improve solution accuracy. Thereby, the light from small tumors can be precisely reconstructed. We designed a series of digital tumor models with different distances, sizes, and shapes to verify the performance of EN-RADMM, and utilized the real glioma-bearing mouse models to further verify its feasibility and accuracy. The simulation results demonstrated that EN-RADMM can achieve significantly higher resolution and reconstruction accuracy of morphology and position with less time compared with other advanced methods. Furthermore, in vivo experiments proved the broad prospect of EN-RADMM in pre-clinical application of FMT reconstruction.

Bioimaging of glutathione variation for early diagnosis of hepatocellular carcinoma using a liver-targeting ratiometric near-infrared fluorescent probe.

Reliable biomarkers are crucial for early diagnosis of diseases and precise therapy. Biological thiols (represented by glutathione, GSH) play vital roles in the antioxidant defense system for maintaining intracellular redox homeostasis in organisms. However, the aberrant variation in the cellular concentration of GSH correlates with diverse diseases including cancer. Here, a ratiometric near-infrared fluorescent probe CyO-Disu is constructed for the specific sensing of GSH variation in live cells and mice models of hepatic carcinoma (HCC). CyO-Disu features three key elements, a response moiety of bis(2-hydroxyethyl) disulfide, a near-infrared fluorescence signal transducer of heptamethine ketone cyanine, and a targeting moiety of D-galactose. By virtue of its liver-targeting capability, CyO-Disu was utilized for evaluating GSH fluctuations in primary and metastatic hepatoma living cells. To evaluate the efficacy of CyO-Disuin vivo, orthotopic HCC and pulmonary metastatic hepatoma mice models were employed for GSH imaging using two-dimensional and three-dimensional fluorescence molecular tomographic imaging systems. The bioimaging results offered direct evidence that GSH displayed varied concentrations during the progression of HCC. Therefore, the as-synthesized probe CyO-Disu could serve as a potential powerful tool for the early diagnosis and precise treatment of HCC using GSH as a reliable biomarker.

D2-RecST: Dual-domain joint reconstruction strategy for fluorescence molecular tomography based on image domain and perception domain

Background and ObjectiveFluorescence molecular tomography (FMT) is a promising molecular imaging modality for quantifying the three-dimensional (3D) distribution of fluorescent probes in small animals. Over the past few years, learning-based FMT reconstruction methods have achieved promising results. However, these methods typically attempt to minimize the mean-squared error (MSE) between the reconstructed image and the ground truth. Although signal-to-noise ratios (SNRs) are improved, they are susceptible to non-uniform artifacts and loss of structural detail, making it extremely challenging to obtain accurate and robust FMT reconstructions under noisy measurements. MethodsWe propose a novel dual-domain joint strategy based on the image domain and perception domain for accurate and robust FMT reconstruction. First, we formulate an explicit adversarial learning strategy in the image domain, which greatly facilitates training and optimization through two enhanced networks to improve anti-noise ability. Besides, we introduce a novel transfer learning strategy in the perceptual domain to optimize edge details by providing perceptual priors for fluorescent targets. Collectively, the proposed dual-domain joint reconstruction strategy can significantly eliminate the non-uniform artifacts and effectively preserve the structural edge details. ResultsBoth numerical simulations and in vivo mouse experiments demonstrate that the proposed method markedly outperforms traditional and cutting-edge methods in terms of positioning accuracy, image contrast, robustness, and target morphological recovery. ConclusionsThe proposed method achieves the best reconstruction performance and has great potential to facilitate precise localization and 3D visualization of tumors in in vivo animal experiments.

Excitation-based fully connected network for precise NIR-II fluorescence molecular tomography.

Fluorescence molecular tomography (FMT) is a novel imaging modality to obtain fluorescence biomarkers' three-dimensional (3D) distribution. However, the simplified mathematical model and complicated inverse problem limit it to achieving precise results. In this study, the second near-infrared (NIR-II) fluorescence imaging was adopted to mitigate tissue scattering and reduce noise interference. An excitation-based fully connected network was proposed to model the inverse process of NIR-II photon propagation and directly obtain the 3D distribution of the light source. An excitation block was embedded in the network allowing it to autonomously pay more attention to neurons related to the light source. The barycenter error was added to the loss function to improve the localization accuracy of the light source. Both numerical simulation and in vivo experiments showed the superiority of the novel NIR-II FMT reconstruction strategy over the baseline methods. This strategy was expected to facilitate the application of machine learning in biomedical research.