Mesoscopic Fluorescence Molecular Tomography Research Articles

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.

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.

Design and characterization of a time-domain optical tomography platform for mesoscopic lifetime imaging.

We report on the system design and instrumental characteristics of a novel time-domain mesoscopic fluorescence molecular tomography (TD-MFMT) system for multiplexed molecular imaging in turbid media. The system is equipped with a supercontinuum pulsed laser for broad spectral excitation, based on a high-density descanned raster scanning intensity-based acquisition for 2D and 3D imaging and augmented with a high-dynamical range linear time-resolved single-photon avalanche diode (SPAD) array for lifetime quantification. We report on the system's spatio-temporal and spectral characteristics and its sensitivity and specificity in controlled experimental settings. Also, a phantom study is undertaken to test the performance of the system to image deeply-seated fluorescence inclusions in tissue-like media. In addition, ex vivo tumor xenograft imaging is performed to validate the system's applicability to the biological sample. The characterization results manifest the capability to sense small fluorescence concentrations (on the order of nanomolar) while quantifying fluorescence lifetimes and lifetime-based parameters at high resolution. The phantom results demonstrate the system's potential to perform 3D multiplexed imaging thanks to spectral and lifetime contrast in the mesoscopic range (at millimeters depth). The ex vivo imaging exhibits the prospect of TD-MFMT to resolve intra-tumoral heterogeneity in a depth-dependent manner.

Intravital mesoscopic fluorescence molecular tomography allows non-invasive in vivo monitoring and quantification of breast cancer growth dynamics

Preclinical breast tumor models are an invaluable tool to systematically study tumor progression and treatment response, yet methods to non-invasively monitor the involved molecular and mechanistic properties under physiologically relevant conditions are limited. Here we present an intravital mesoscopic fluorescence molecular tomography (henceforth IFT) approach that is capable of tracking fluorescently labeled tumor cells in a quantitative manner inside the mammary gland of living mice. Our mesoscopic approach is entirely non-invasive and thus permits prolonged observational periods of several months. The relatively high sensitivity and spatial resolution further enable inferring the overall number of oncogene-expressing tumor cells as well as their tumor volume over the entire cycle from early tumor growth to residual disease following the treatment phase. Our IFT approach is a promising method for studying tumor growth dynamics in a quantitative and longitudinal fashion in-vivo.

System configuration optimization for mesoscopic fluorescence molecular tomography.

Tissue engineering applications demand 3D, non-invasive, and longitudinal assessment of bioprinted constructs. Current emphasis is on developing tissue constructs mimicking in vivo conditions; however, these are increasingly challenging to image as they are typically a few millimeters thick and turbid, limiting the usefulness of classical fluorescence microscopic techniques. For such applications, we developed a Mesoscopic Fluorescence Molecular Tomography methodology that collects high information content data to enable high-resolution tomographic reconstruction of fluorescence biomarkers at millimeters depths. This imaging approach is based on an inverse problem; hence, its imaging performances are dependent on critical technical considerations including optode sampling, forward model design and inverse solver parameters. Herein, we investigate the impact of the optical system configuration parameters, including detector layout, number of detectors, combination of detector and source numbers, and scanning mode with uncoupled or coupled source and detector array, on the 3D imaging performances. Our results establish that an MFMT system with a 2D detection chain implemented in a de-scanned mode provides the optimal imaging reconstruction performances.

Deep learning-based mesoscopic fluorescence molecular tomography: an in silico study.

Fluorescence molecular tomography (FMT), as well as mesoscopic FMT (MFMT) is widely employed to investigate molecular level processes ex vivo or in vivo. However, acquiring depth-localized and less blurry reconstruction still remains challenging, especially when fluorophore (dye) is located within large scattering coefficient media. Herein, a two-stage deep learning-based three-dimensional (3-D) reconstruction algorithm is proposed. The key point for the proposed algorithm is to employ a 3-D convolutional neural network to correctly predict the boundary of reconstructions, leading refined results. Compared with conventional algorithm, in silico experiments show that relative volume and absolute centroid error reduce over whereas intersection over union increases over 15% for most situations. These results preliminarily indicate the promising future of appropriately applying machine learning (deep learning)-based methods in MFMT.

Improving mesoscopic fluorescence molecular tomography via preconditioning and regularization.

Mesoscopic fluorescence molecular tomography (MFMT) is a novel imaging technique capable of obtaining 3-D distribution of molecular probes inside biological tissues at depths of a few millimeters with a resolution up to ~100 μm. However, the ill-conditioned nature of the MFMT inverse problem severely deteriorates its reconstruction performances. Furthermore, dense spatial sampling and fine discretization of the imaging volume required for high resolution reconstructions make the sensitivity matrix (Jacobian) highly correlated, which prevents even advanced algorithms from achieving optimal solutions. In this work, we propose two computational methods to respectively increase the incoherence of the sensitivity matrix and improve the convergence rate of the inverse solver. We first apply a compressed sensing (CS) based preconditioner on either the whole sensitivity matrix or sub sensitivity matrices to reduce the coherence between columns of the sensitivity matrix. Then we employed a regularization method based on the weight iterative improvement method (WIIM) to mitigate the ill-condition of the sensitivity matrix and to drive the iterative optimization process towards convergence at a faster rate. We performed numerical simulations and phantom experiments to validate the effectiveness of the proposed strategies. In both in silico and in vitro cases, we were able to improve the quality of MFMT reconstructions significantly.

Improving mesoscopic fluorescence molecular tomography through data reduction.

Mesoscopic fluorescence molecular tomography (MFMT) is a novel imaging technique that aims at obtaining the 3-D distribution of molecular probes inside biological tissues at depths of a few millimeters. To achieve high resolution, around 100-150μm scale in turbid samples, dense spatial sampling strategies are required. However, a large number of optodes leads to sizable forward and inverse problems that can be challenging to compute efficiently. In this work, we propose a two-step data reduction strategy to accelerate the inverse problem and improve robustness. First, data selection is performed via signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) criteria. Then principal component analysis (PCA) is applied to further reduce the size of the sensitivity matrix. We perform numerical simulations and phantom experiments to validate the effectiveness of the proposed strategy. In both in silico and in vitro cases, we are able to significantly improve the quality of MFMT reconstructions while reducing the computation times by close to a factor of two.

Mesoscopic Fluorescence Molecular Tomography for Evaluating Engineered Tissues.

Optimization of regenerative medicine strategies includes the design of biomaterials, development of cell-seeding methods, and control of cell-biomaterial interactions within the engineered tissues. Among these steps, one paramount challenge is to non-destructively image the engineered tissues in their entirety to assess structure, function, and molecular expression. It is especially important to be able to enable cell phenotyping and monitor the distribution and migration of cells throughout the bulk scaffold. Advanced fluorescence microscopic techniques are commonly employed to perform such tasks; however, they are limited to superficial examination of tissue constructs. Therefore, the field of tissue engineering and regenerative medicine would greatly benefit from the development of molecular imaging techniques which are capable of non-destructive imaging of three-dimensional cellular distribution and maturation within a tissue-engineered scaffold beyond the limited depth of current microscopic techniques. In this review, we focus on an emerging depth-resolved optical mesoscopic imaging technique, termed laminar optical tomography (LOT) or mesoscopic fluorescence molecular tomography (MFMT), which enables longitudinal imaging of cellular distribution in thick tissue engineering constructs at depths of a few millimeters and with relatively high resolution. The physical principle, image formation, and instrumentation of LOT/MFMT systems are introduced. Representative applications in tissue engineering include imaging the distribution of human mesenchymal stem cells embedded in hydrogels, imaging of bio-printed tissues, and in vivo applications.

Dental Imaging Using Mesoscopic Fluorescence Molecular Tomography: An ex Vivo Feasibility Study

Some dental lesions are difficult to detect with traditional anatomical imaging methods, such as, with visual observation, dental radiography and X-ray computed tomography (CT). Therefore, we investigated the viability of using an optical imaging technique, Mesoscopic Fluorescence Molecular Tomography (MFMT) to retrieve molecular contrast in dental samples. To establish feasibility of obtaining 3-D images in teeth using MFMT, molecular contrast was simulated using a dye-filled capillary that was placed in the lower half of human tooth ex vivo. The dye and excitation wavelength were chosen to be excited at 650–660 nm in order to simulate a carious lesion. The location of the capillary was varied by changing the depth from the surface at which the dye, at various concentrations, was introduced. MFMT reconstructions were benchmarked against micro-CT. Overall; MFMT exhibited a location accuracy of ~15% and a volume accuracy of ~15%, up to 2 mm depth with moderate dye concentrations. These results demonstrate the potential of MFMT to retrieve molecular contrast in 3-D in highly scattering tissues, such as teeth.

High-resolution mesoscopic fluorescence molecular tomography based on compressive sensing.

Mesoscopic fluorescence molecular tomography (MFMT) is new imaging modality aiming at 3-D imaging of molecular probes in a few millimeter thick biological samples with high-spatial resolution. In this paper, we develop a compressive sensing-based reconstruction method with l1-norm regularization for MFMT with the goal of improving spatial resolution and stability of the optical inverse problem. Three-dimensional numerical simulations of anatomically accurate microvasculature and real data obtained from phantom experiments are employed to evaluate the merits of the proposed method. Experimental results show that the proposed method can achieve 80 μm spatial resolution for a biological sample of 3 mm thickness and more accurate quantifications of concentrations and locations for the fluorophore distribution than those of the conventional methods.

Mesoscopic fluorescence molecular tomography of reporter genes in bioprinted thick tissue

Three-dimensional imaging of thick tissue constructs is one of the main challenges in the field of tissue engineering and regenerative medicine. Optical methods are the most promising as they offer noninvasive, fast, and inexpensive solutions. Herein, we report the use of mesoscopic fluorescence molecular tomography (MFMT) to image function and structure of thick bioprinted tissue hosted in a 3-mm-thick bioreactor. Collagen-based tissue assembled in this study contains two vascular channels formed by green fluorescent protein- and mCherry-expressing cells. Transfected live cell imaging enables us to image function, whereas Flash Red fluorescent bead perfusion into the vascular channel allows us to image structure. The MFMT optical reconstructions are benchmarked with classical microscopy techniques. MFMT and wide-field fluorescence microscopy data match within 92% in area and 84% in location, validating the accuracy of MFMT reconstructions. Our results demonstrate that MFMT is a well-suited imaging modality for fast, longitudinal, functional imaging of thick, and turbid tissue engineering constructs.

The integration of 3-D cell printing and mesoscopic fluorescence molecular tomography of vascular constructs within thick hydrogel scaffolds

Developing methods that provide adequate vascular perfusion is an important step toward engineering large functional tissues. Meanwhile, an imaging modality to assess the three-dimensional (3-D) structures and functions of the vascular channels is lacking for thick matrices (>2∼3 mm). Herein, we report on an original approach to construct and image 3-D dynamically perfused vascular structures in thick hydrogel scaffolds. In this work, we integrated a robotic 3-D cell printing technology with a mesoscopic fluorescence molecular tomography imaging system, and demonstrated the capability of the platform to construct perfused collagen scaffolds with endothelial lining and to image both the fluid flow and fluorescent-labeled living endothelial cells at high-frame rates, with high sensitivity and accuracy. These results establish the potential of integrating both 3-D cell printing and fluorescence mesoscopic imaging for functional and molecular studies in complex tissue-engineered tissues.