Fluorescence Diffuse Tomography Research Articles

Projected algebraic reconstruction technique-network for high-fidelity diffuse fluorescence tomography reconstruction

We propose a model-driven projected algebraic reconstruction technique (PART)-network (PART-Net) that leverages the advantages of the traditional model-based method and the neural network to improve the imaging quality of diffuse fluorescence tomography. In this algorithm, nonnegative prior information is incorporated into the ART iteration process to better guide the optimization process, and thereby improve imaging quality. On this basis, PART in conjunction with a residual convolutional neural network is further proposed to obtain high-fidelity image reconstruction. The numerical simulation results demonstrate that the PART-Net algorithm effectively improves noise robustness and reconstruction accuracy by at least 1–2 times and exhibits superiority in spatial resolution and quantification, especially for a small-sized target (r=2mm), compared with the traditional ART algorithm. Furthermore, the phantom and in vivo experiments verify the effectiveness of the PART-Net, suggesting strong generalization capability and a great potential for practical applications.

Performance enhancement of diffuse fluorescence tomography based on an extended Kalman filtering-long short term memory neural network correction model.

To alleviate the ill-posedness of diffuse fluorescence tomography (DFT) reconstruction and improve imaging quality and speed, a model-derived deep-learning method is proposed by combining extended Kalman filtering (EKF) with a long short term memory (LSTM) neural network, where the iterative process parameters acquired by implementing semi-iteration EKF (SEKF) served as inputs to the LSTM neural network correction model for predicting the optimal fluorescence distributions. To verify the effectiveness of the SEKF-LSTM algorithm, a series of numerical simulations, phantom and in vivo experiments are conducted, and the experimental results are quantitatively evaluated and compared with the traditional EKF algorithm. The simulation experimental results show that the proposed new algorithm can effectively improve the reconstructed image quality and reconstruction speed. Importantly, the LSTM correction model trained by the simulation data also obtains satisfactory results in the experimental data, suggesting that the SEKF-LSTM algorithm possesses strong generalization ability and great potential for practical applications.

IR780-based diffuse fluorescence tomography for cancer detection.

IR780 iodide is a commercially available targeted near-infrared contrast agent for in vivo imaging and cancer photodynamic or photothermal therapy, whereas the accumulation, dynamics, and retention of IR780 in biological tissue, especially in tumor is still under-explored. Diffuse fluorescence tomography (DFT) can be used for localization and quantification of the three-dimensional distribution of NIR fluorophores. Herein, a homemade DFT imaging system combined with tumor-targeted IR780 was utilized for cancer imaging and pharmacokinetic evaluation. The aim of this study is to comprehensively assess the biochemical and pharmacokinetic characteristics of IR780 with the aid of DFT imaging. The optimal IR780 concentration (20 μg/mL) was achieved first. Subsequently, the good biocompatibility and cellar uptake of IR780 was demonstrated through the mouse acute toxic test and cell assay. In vivo, DFT imaging effectively identified various subcutaneous tumors and revealed the long-term retention of IR780 in tumors and rapid metabolism in the liver. Ex vivo imaging indicated IR780 was mainly concentrated in tumor and lung with significantly different from the distribution in other organs. DFT imaging allowed sensitive tumor detection and pharmacokinetic rates analysis. Simultaneously, the kinetics of IR780 in tumors and liver provided more valuable information for application and development of IR780.

Special issue on enhanced photodynamic therapy: Part II

Special issue on enhanced photodynamic therapy: Part II

Three-dimensional quantification of protoporphyrin IX in photodynamic therapy using SFDI/DFT: A pilot experimental validation

Photodynamic therapy (PDT) dosimetry, including light dose, photosensitizer dose and tissue oxygen, has been a research focus in PDT. In this work, we present a three-dimensional (3D) quantification of protoporphyrin IX (PpIX) using combined spatial frequency domain imaging (SFDI) and diffuse fluorescence tomography (DFT). The SFDI maps both the distributions of tissue absorption and scattering properties at three wavelengths and accordingly provides the optical background for DFT and extracts the tissue oxygenation for assessing the therapeutic outcomes, while DFT dynamically monitors the 3D distribution of PpIX dose from measured fluorescence signals for the procedure optimization. A pilot in vivo application in tumor nude models showed that the proposed SFDI/DFT is able to dynamically trace changes in the PpIX concentration and tissue oxygen during the treatment, rendering it a potentially powerful tool for PDT to improve clinical efficacy.

Indirect and direct estimation of pharmacokinetic parameters in dynamic diffuse fluorescence tomography by adaptive extended Kalman filtering.

Pharmacokinetic parameter estimation with the support of dynamic diffuse fluorescence tomography (DFT) can provide helpful diagnostic information for tumor differentiation and monitoring. Adaptive extended Kalman filtering (AEKF) as a nonlinear filter method has the merits of high quantitativeness, noise robustness, and initialization independence. In this paper, indirect and direct AEKF schemes combining with a commonly used two-compartment model were studied to estimate the pharmacokinetic parameters based on our self-designed dynamic DFT system. To comprehensively compare the performances of both schemes, the selection of optimal noise covariance matrices affecting estimation results was first studied, then a series of numerical simulations with the metabolic time ranged from 4.16 min to 38 min was carried out and quantitatively evaluated. The comparison results show that the direct AEKF outperforms the indirect EKF in estimation accuracy at different metabolic velocity and demonstrates stronger stability at the large metabolic velocity. Furtherly, the in vivo experiment was conducted to achieve the indocyanine green pharmacokinetic-rate images in the mouse liver. The experimental results confirmed the capability of both schemes to estimate the pharmacokinetic-rate images and were in agreement with the theory predictions and the numerical simulation results.

High-sensitivity dynamic diffuse fluorescence tomography system for fluorescence pharmacokinetics.

.Significance: Dynamic diffuse fluorescence tomography (DFT) can recover the static distribution of fluorophores and track dynamic temporal events related to physiological and disease progression. Dynamic imaging indocyanine green (ICG) approved by the food and drug administration is still under-exploited because of its characteristics of low quantum yield and relatively rapid tissue metabolism.Aim: In order to acquire the ICG tomographic image sequences for pharmacokinetic analysis, a dynamic DFT system was proposed.Approach: A fiber-based dynamic DFT system adopts square-wave modulation lock-in photon-counting scheme and series-parallel measurement mode, which possesses high sensitivity, large dynamic range, high anti-ambient light ability in common knowledge, as well as good cost performance. In order to investigate the effectiveness of the proposed system, the measurement stability and the anti-crosstalk—a crucial factor affecting the system parallelization—were assessed firstly, then a series of static phantoms, dynamic phantoms and in vivo mice experiments were conducted to verify the imaging capability.Results: The system has the limited dynamic range of 100 dB, the fluctuation of photon counting within 3%, and channel-to-channel crosstalk ratio better than 1.35. Under the condition of a sufficient signal-to-noise ratio, a complete measurement time for one frame image was 10.08 s. The experimental results of static phantoms with a single target and three targets showed that this system can accurately obtain the positions, sizes, and shapes of the targets and the reconstructed images exhibited a high quantitativeness. Further, the self-designed dynamic phantom experiments demonstrated the capability of the system to capture fast changing fluorescence signals. Finally, the in vivo experiments validated the practical capability of the system to effectively track the ICG metabolism in living mice.Conclusions: These results demonstrate that our proposed system can be utilized for assessing ICG pharmacokinetics, which may provide a valuable tool for tumor detection, drug assessment, and liver function evaluation.

Reconstruction of fluorophore concentration distribution in diffuse fluorescence tomography based on Tikhonov regularisation and nonnegativity condition

We propose to solve the inverse problem of diffuse fluorescence tomography (DFT) – reconstruction of the spatial distribution of the fluorophore in biological tissues – by a method based on Tikhonov regularisation with the nonnegativity condition (TRNC) of the reconstructed components of the solution vector. Model experiments on a biotissue phantom demonstrate that the TRNC method allows for a more accurate reconstruction of the distribution of the fluorophore concentration, and is also more stable in comparison with the known algorithms used in DFT, such as ART, SMART, NNLS, etc.

Focused x-ray luminescence imaging system for small animals based on a rotary gantry.

.Significance: The ability to detect and localize specific molecules through tissue is important for elucidating the molecular basis of disease and treatment. Unfortunately, most current molecular imaging tools in tissue either lack high spatial resolution (e.g., diffuse optical fluorescence tomography or positron emission tomography) or lack molecular sensitivity (e.g., micro-computed tomography, ). X-ray luminescence imaging emerged about 10 years ago to address this issue by combining the molecular sensitivity of optical probes with the high spatial resolution of x-ray imaging through tissue. In particular, x-ray luminescence computed tomography (XLCT) has been demonstrated as a powerful technique for the high-resolution imaging of deeply embedded contrast agents in three dimensions (3D) for small-animal imaging.Aim: To facilitate the translation of XLCT for small-animal imaging, we have designed and built a small-animal dedicated focused x-ray luminescence tomography (FXLT) scanner with a scanner, synthesized bright and biocompatible nanophosphors as contrast agents, and have developed a deep-learning-based reconstruction algorithm.Approach: The proposed FXLT imaging system was designed using computer-aided design software and built according to specifications. nanophosphors doped with europium or terbium were synthesized with a silica shell for increased biocompatibility and functionalized with biotin. A deep-learning-based XLCT image reconstruction was also developed based on the residual neural network as a data synthesis method of projection views from few-view data to enhance the reconstructed image quality.Results: We have built the FXLT scanner for small-animal imaging based on a rotational gantry. With all major imaging components mounted, the motor controlling the gantry can be used to rotate the system with a high accuracy. The synthesized nanophosphors displayed distinct x-ray luminescence emission, which enables multi-color imaging, and has successfully been bound to streptavidin-coated substrates. Lastly, numerical simulations using the proposed deep-learning-based reconstruction algorithm has demonstrated a clear enhancement in the reconstructed image quality.Conclusions: The designed FXLT scanner, synthesized nanophosphors, and deep-learning-based reconstruction algorithm show great potential for the high-resolution molecular imaging of small animals.

In Vivo Pharmacokinetics Assessment of Indocyanine Green-Loaded Nanoparticles in Tumor Tissue with a Dynamic Diffuse Fluorescence Tomography System.

The purpose of this study was to show a systematic strategy for assessing the pharmacokinetics of indocyanine green (ICG)-loaded nanoparticles in the tumor tissue based on a dynamic diffuse fluorescence tomography (DFT) system. Twelve-seven-week-old male Balb/c nude mice bearing HepG2/ADR hepatocellular carcinoma were randomly divided into four groups (n= 3 per group). Four hundred microliters of three types of ICG-loaded nanoparticles (content of ICG: 50μg/ml) and free ICG (50μg/ml) was intravenously injected into the mice in each group, respectively. Afterwards, the real-time tomographic images on the spatial level were acquired at 2-11min, 30min, 1, 2, 3, 4, 6, 8, 10, 12, and 24h post-injection, and pharmacokinetic rates were derived for semi-quantitative assessment of the pharmacokinetics of nanoparticles at the tumor site using our proposed pharmacokinetic analysis method. The results obtained from our proposed dynamic DFT experiment demonstrated the distribution of different ICG formulations on the spatial level and enabled the semi-quantitative analysis of the pharmacokinetics of nanoparticles in the tumor tissue. The obtained pharmacokinetic rates effectively reflected the metabolic processes of nanoparticles in the tumor tissue, which proves to be beneficial for the development of tumor diagnosis and therapy.

In situ real-time tracing of hierarchical targeting nanostructures in drug resistant tumors using diffuse fluorescence tomography.

Nanoparticles that respond to specific endogenous or exogenous stimuli in tumor tissues are actively being developed to address multidrug resistance owing to multiple advantages, including a prolonged circulation time, enhanced permeability and retention effect, and superior cellular uptake. Although some exciting results have been obtained, existing nanoparticles have limited routes to overcome the drug resistance of tumor cells; this limitation results in a failure to ablate resistant tumors via intravenous administration. To resolve this dilemma, we developed a smart theranostic nanoplatform with programmable particle size, activatable target ligands and in vivo multimodal imaging. This nanoplatform, which includes stealth zwitterionic coating, was shown to be quickly trapped in tumor tissue from the blood circulation within 5 min. Subsequently, the targeting moieties were activated in response to the acidic tumor microenvironment by triggering the zwitterionic shell detachment, driving the peeled nanoparticles to penetrate into tumor cells. These smart nanoparticles completely inhibited drug-resistant tumor growth and did not cause any damage to normal organ tissues in live animals. The designed nanoplatforms simultaneously acted as a nanoprobe for fluorescence imaging. Moreover, we also used noninvasive pharmacokinetic diffuse fluorescence tomography (DFT) to dynamically monitor and in situ real-time trace the nanoplatforms' behavior throughout the entire tumor in live animals. The nanoplatforms enabled rapid drug accumulation and deep penetration throughout the entire tumor. The rate of drug accumulation after the administration of nanoplatforms was five-fold higher compared with that after the administration of the free drug, which resulted in increased drug delivery efficiency and improved antitumor efficacy. Collectively, this hierarchical vehicle design provides promising insights for the development of theragnosis for multidrug resistant tumors.

Assessing indocyanine green pharmacokinetics in mouse liver with a dynamic diffuse fluorescence tomography system.

Fluorescence pharmacokinetic rates in tissues can provide additional specific and quantitative physiological and pathological information for evaluating organ function. This modality requires a highly sensitive diffuse fluorescence tomography (DFT) working in dynamic way to finally extract the pharmacokinetic rates from the measured pharmacokinetics-associated temporally varying boundary intensity, normally with the support of a priori anatomy. This paper is devoted to study pharmacokinetics of indocyanine green (ICG) in mouse liver based on synergistic dynamic-DFT and X-ray computer tomography (XCT): A highly sensitive dynamic DFT system of CT-scanning mode working with parallel 4 photomultiplier-tube photon-counting channels generates informative and instantaneous sampling datasets; An XCT system provides priori information of the target localization for improvement of the reconstruction quality; An analysis procedure extracts the pharmacokinetic rates from the reconstructed ICG concentration-time curves, using the Gauss-Newton scheme for fitting to a 2-compartment model. The uptake and excretion rates of ICG which were obtained in livers of 10 healthy mice in the in vivo experiments can be used to quantitatively evaluate liver function. The results can validate the effectiveness of both the imaging measurements system and pharmacokinetic analysis method.

近赤外光を用いた次世代生体イメージング：拡散光・蛍光・光音響トモグラフィー

近赤外光を用いた次世代生体イメージング：拡散光・蛍光・光音響トモグラフィー

Direct reconstruction in CT-analogous pharmacokinetic diffuse fluorescence tomography: two-dimensional simulative and experimental validations.

We present a generalized strategy for direct reconstruction in pharmacokinetic diffuse fluorescence tomography (DFT) with CT-analogous scanning mode, which can accomplish one-step reconstruction of the indocyanine-green pharmacokinetic-rate images within in vivo small animals by incorporating the compartmental kinetic model into an adaptive extended Kalman filtering scheme and using an instantaneous sampling dataset. This scheme, compared with the established indirect and direct methods, eliminates the interim error of the DFT inversion and relaxes the expensive requirement of the instrument for obtaining highly time-resolved date-sets of complete 360 deg projections. The scheme is validated by two-dimensional simulations for the two-compartment model and pilot phantom experiments for the one-compartment model, suggesting that the proposed method can estimate the compartmental concentrations and the pharmacokinetic-rates simultaneously with a fair quantitative and localization accuracy, and is well suitable for cost-effective and dense-sampling instrumentation based on the highly-sensitive photon counting technique.

Small-Animal Imaging Using Diffuse Fluorescence Tomography.

Diffuse fluorescence tomography (DFT) has been developed to image the spatial distribution of fluorescence-tagged tracers in living tissue. This capability facilitates the recovery of any number of functional parameters, including enzymatic activity, receptor density, blood flow, and gene expression. However, deploying DFT effectively is complex and often requires years of know-how, especially for newer mutlimodal systems that combine DFT with conventional imaging systems. In this chapter, we step through the process of using MRI-DFT imaging of a receptor-targeted tracer in small animals.

Full time-resolved diffuse fluorescence tomography accelerated with parallelized Fourier-series truncated diffusion approximation.

Of the three measurement schemes established for diffuse fluorescence tomography (DFT), the time-domain scheme is well known to provide the richest information about the distribution of the targeting fluorophore in living tissues. However, the explicit use of the full time-resolved data usually leads to a considerably lengthy time for image reconstruction, limiting its applications to three-dimensional or small-volume imaging. To cope with the adversity, we propose herein a computationally efficient scheme for DFT image reconstruction where the time-dependent photon density is expanded to a Fourier-series and calculated by solving the independent frequency-domain diffusion equations at multiple sampling frequencies with the support of a combined multicore CPU-based coarse-grain and multithread GPU-based fine-grain parallelization strategy. With such a parallelized Fourier-series truncated diffusion approximation, both the time- and frequency-domain inversion procedures are developed and validated for their effectiveness and accuracy using simulative and phantom experiments. The results show that the proposed method can generate reconstructions comparable to the explicit time-domain scheme, with significantly reduced computational time.

Trans-illumination fluorescence imaging of deep-seated tumors in small animals

AbstractBackground:Fluorescence diffuse tomography (FDT) is the most accurate technique for the imaging of labeled tumors in the small animal body. However, the procedure for reconstruction of the spatial distribution of the fluorophore requires a high signal-to-noise ratio due to the ill-condition of the inverse problem. Therefore, the FDT technique is ineffective for imaging tumors of small size or with dim fluorophores because of the low intensity of their fluorescence compared with the high level of tissue autofluorescence. In these cases, the size and position of a marked tumor in the animal body can be estimated from two-dimensional fluorescence images obtained using trans- or epi-illumination techniques.Material and methods:A versatile system for small animal fluorescence imaging which combines planar epi- and trans-illumination geometries of the light source and of the fluorescence receiver was created and tested. For epi-illumination imaging, light-emitting diode sources were used to provide homogeneous and stable illumination of the experimental animal, in combination with a cooled CCD camera which covers the entire illuminated area. For trans-illumination imaging, mechanical raster-scanning devices modulated at a low frequency were used for the laser source, together with a cooled photomultiplier tube, which provided outstanding sensitivity.Results:Monitoring the orthotopic tumor growth in animal bodies has demonstrated the efficacy of trans-illumination imaging in comparison with the epi-illumination technique. The results obtained also showed that the effective use of the trans-illumination technique requires Born normalization of the fluorescence signal and the exclusion of lateral illumination by surrounding the animal with additional light absorption material using light-absorption pads on both sides of the body.

Performance Enhancement of Pharmacokinetic Diffuse Fluorescence Tomography by Use of Adaptive Extended Kalman Filtering.

Due to both the physiological and morphological differences in the vascularization between healthy and diseased tissues, pharmacokinetic diffuse fluorescence tomography (DFT) can provide contrast-enhanced and comprehensive information for tumor diagnosis and staging. In this regime, the extended Kalman filtering (EKF) based method shows numerous advantages including accurate modeling, online estimation of multiparameters, and universal applicability to any optical fluorophore. Nevertheless the performance of the conventional EKF highly hinges on the exact and inaccessible prior knowledge about the initial values. To address the above issues, an adaptive-EKF scheme is proposed based on a two-compartmental model for the enhancement, which utilizes a variable forgetting-factor to compensate the inaccuracy of the initial states and emphasize the effect of the current data. It is demonstrated using two-dimensional simulative investigations on a circular domain that the proposed adaptive-EKF can obtain preferable estimation of the pharmacokinetic-rates to the conventional-EKF and the enhanced-EKF in terms of quantitativeness, noise robustness, and initialization independence. Further three-dimensional numerical experiments on a digital mouse model validate the efficacy of the method as applied in realistic biological systems.

Overlap time-gating approach for improving time-domain diffuse fluorescence tomography based on the IRF-calibrated Born normalization

Diffuse fluorescence tomography (DFT) methods using the full time-resolved (TR) data have been demonstrated to substantially improve the spatial resolution and quantitative accuracy of reconstructed images. However, these methods usually suffer from low practical feasibility because of the influence of the system impulse response function (IRF) and the trade-off between the used data time-resolution and the required signal-to-noise ratio (SNR). We present a full TR approach that combines an IRF-calibrated full TR Born normalization and an overlap-delaying time-gate scheme for attaining high SNR without sacrificing the TR information content. The approach is validated with full TR data from phantom experiments for its better performances in the spatial resolution and reconstruction fidelity compared to the traditional DFT methods.

Fluorescence diffuse tomography technique with autofluorescence removal based on dispersion of biotissue optical properties

The dispersion of biotissue optical properties results in distortion of the spectrum of radiation during propagation through biotissues. This phenomenon can be used for solving the inverse problem in fluorescence diffuse tomography. We have developed the spectrally resolved fluorescence diffuse tomography (SFDT) technique, which allows reconstruction of the spatial distribution of the fluorophore in biotissue even in the presence of unknown autofluorescence. The experimental setup combining epi-illumination and trans-illumination imaging geometries with spectral resolution has been created. Experimental studies on tissue phantoms and small animals in vivo with the proposed SFDT technique have been conducted. The obtained results have shown high accuracy of the inverse problem solution for spatial distribution of fluorophore concentration.