KEYWORDS: Tumors, Fluorescence, Liver, Cancer detection, Imaging systems, In vivo imaging, Fluorescence imaging, Tissues, Fluorescence tomography, Near infrared
IR780 is widely used as a commercially available near infrared contrast agent due to superior optical properties and tumor targeting capacity, while is a photosensitizer for photothermal (PTT) and photodynamic therapy (PDT). However, few articles reported the accumulation, dynamics and retention of IR780 in tumor. In the work, we explored the accumulation and retention of IR780 in tumor by quantitatively recovering the three-dimensional distributions of IR780 using a home-made diffuse fluorescence tomography (DFT) prototype system. The results showed that DFT can effectively identified multiple tumor targets with a significant tumor-to-normal-tissue ratio simultaneously. The kinetics of fluorescent signals in tumors and liver showed that IR780 was quickly cleared from the liver, whereas exhibited much higher tumor retention over 7days. Ex vivo imaging of dissected organs and fluorescence signal analysis revealed that IR780 was mainly concentrated in tumor and lung with significantly different from the distribution in other organs, suggesting that IR780 had excellent tumor homing ability.
At present, the imaging of fluorescence pharmacokinetic parameters based on dynamic diffuse fluorescence tomography (D-DFT) technology have limitations in some aspects including the accuracy of physical model and the quantification of method. In this work, we propose a fluorescence pharmacokinetic parametric imaging method of tumor tissues based on D-DFT and deep learning. It mainly includes: a more realistic training and test simulation data set can be established by combining non-uniform tissue photon transport model and biological tissue fluorescence kinetics method. A fluorescence pharmacokinetic parametric reconstruction algorithm that involves an improved U-Net architecture based on the fully convolutional neural network is developed to break through the complexity bottleneck of imaging physical model. The numerical simulation results show that the method can realize image reconstruction of pharmacokinetic parameters with high spatial resolution and high quantitative accuracy.
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.
In-line X-ray phase contrast imaging (IL-PCI) is a promising technology for clinical diagnosis because of its great advantage in distinguishing low contrast tissues and simple structure to implement. In order to recover the phase projections from the phase contrast measurements, conventional phase retrieval methods were developed based on assumptions such as homogeneous material, weak attenuation, and thus suffered from limited generalizability, practicability and feasibility. Deep learning-based methods have been proposed for phase retrieval and great success has been achieved. While the practical physical model of phase contrast imaging hasn’t been fully considered including the non-ideal effects of finite size of the x-ray micro focal spot, finite pixel size of the detector and the system noise. In this paper, a convolutional network based on generative adversarial network is proposed to retrieve the phase projections with fully considering the non-ideal effects in IL-PCI. The network composed of a generating network from which the phase projections were retrieved and a discriminating network from which the difference between the output of generation network and the reference phase projection is processed and backpropagated to the input of the network. Phase contrast measurements of the microspheres phantom were simulated and retrieved by the conventional methods and the proposed network. Results show the superiority of the proposed network in spatial resolution and noise suppression compared with the conventional method.
Diffuse Optical Tomography (DOT) is a promising non-invasive optical imaging technology that can provide structural and functional information of biological tissues. Since the diffused light undergoes multiple scattering in biological tissues, and the boundary measurements are limited, the reverse problem of DOT is ill-posed and ill-conditioned. In order to overcome these limitations, two types of neural networks, back-propagation neural network (BPNN) and stacked autoencoder (SAE) were applied in DOT image reconstruction, which use the internal optical properties distribution and the boundary measurement of biological tissues as the input and output data sets respectively to adjust the neural network parameters, and directly establish a nonlinear mapping of the input and output. To verify the effectiveness of the methods, a series of numerical simulation experiments were conducted, and the experimental results were quantitatively assessed, which demonstrated that both methods can accurately predict the position and size of the inclusion, especially in the case of higher absorption contrast. As a whole, SAE can get better reconstructed image results than BPNN and the training time was only a quarter of BPNN.
Fluorescence pharmacokinetics can analyze the absorption, distribution, metabolism and other pharmacokinetic processes of fluorescence agents in biological tissues over time, which can provide more specific and quantitative physiological and pathological information for the evaluation of organ function. This paper is devoted to studying pharmacokinetics of indocyanine green (ICG) in healthy mice and mice with acute alcoholic liver injury based on a home-made dynamic diffuse fluorescence tomography system that possesses high sensitivity and large dynamic measurement range on account of digital lock-in-photon-counting technique. In this study, four-week-old Kunming mice were randomly divided into experimental and control groups. The time-varying distribution of ICG in mice was obtained by diffuse fluorescence tomography reconstruction, and the pharmacokinetic parameters were further extracted from the ICG concentration-time curve. The results showed that the dynamic diffuse fluorescence tomography system successfully captured the ICG metabolism process in mouse liver, and the ICG excretion rate demonstrated an obvious difference between healthy mice and the mice with acute alcoholic liver injury.
Pharmacokinetic diffuse fluorescence tomography (DFT) can provide helpful diagnostic information for tumor differentiation and monitoring. Among the methods of achieving pharmacokinetic parameters, adaptive extended Kalman filtering (AEKF) as a nonlinear filter method demonstrates the merits of quantitativeness, noise-robustness, and initialization independence. In this paper, indirect and direct AEKF schemes based on a commonly used two-compartment model were studied to extract pharmacokinetic parameters from simulation data. To assess the effect of metabolic rate on the reconstruction results, a series of numerical simulation experiments with the metabolic time range from 4.16 min to 38 min were carried out and the results obtained by the two schemes were compared. The results demonstrate that when the metabolic time is longer than 18 min, the pharmacokinetic-rate estimates of two schemes are similar; however, when the metabolic time is shorter than 5 min, the pharmacokinetic parameters obtained by the indirect scheme are far from the true value and even unavailable.
Diffuse optical tomography (DOT) is a novel functional imaging technique that has the vital clinical application. Aiming at the problems in DOT technology, we developed a three-wavelength continuous wave DOT system with high sensitivity and temporal resolution by adopting photo-multiple tube and photon counting detection, as well as lock-in technique. To assess the performance of the system, we conducted a series of cylindrical phantom experiments with optical properties that closely match those of human tissue, and obtained the reconstruction images by combining with our developed imaging scheme. The experimental results show that the position and size of the reconstructed targets are accurate, demonstrating the feasibility of the system. Additionally, the sensitivity, quantitativeness and spatial resolution of the imaging system were assessed by varying the target-to-background contrasting absorption contrast and target size. These preliminary results indicate that the system is scientifically capable of subcentimeter resolution imaging of low-contrast the lesion from the normal background.
Real-time and continuous monitoring of drug release in vivo is an important task in pharmaceutical development. Here, we devoted to explore a real-time continuous study of the pharmacokinetics of free indocyanine green (ICG) and ICG loaded in the shell-sheddable nanoparticles in tumor based on a dynamic diffuse fluorescence tomography (DFT) system: A highly-sensitive dynamic DFT system of CT-scanning mode generates informative and instantaneous sampling datasets; An analysis procedure extracts the pharmacokinetic parameters from the reconstructed time curves of the mean ICG concentration in tumor, using the Gauss-Newton scheme based on two-compartment model. Compared with the pharmacokinetic parameters of free ICG in tumor, the ICG loaded in the shell-sheddable nanoparticles shows efficient accumulation in tumor. The results demonstrate our proposed dynamic-DFT can provide an integrated and continuous view of the drug delivery of the injected agents in different formulations, which is helpful for the development of diagnosis and therapy for tumors.
Diffuse optical tomography (DOT) as a new functional imaging has important clinical applications in many aspects such as benign and malignant breast tumor detection, tumor staging and so on. For quantitative detection of breast tumor, a three-wavelength continuous-wave DOT prototype system combined the ultra-high sensitivity of the photon-counting detection and the measurement parallelism of the lock-in technique was developed to provide high temporal resolution, high sensitivity, large dynamic detection range and signal-to-noise ratio. Additionally, a CT-analogous scanning mode was proposed to cost-effectively increase the detection data. To evaluate the feasibility of the system, a series of assessments were conducted. The results demonstrate that the system can obtain high linearity, stability and negligible inter-wavelength crosstalk. The preliminary phantom experiments show the absorption coefficient is able to be successfully reconstructed, indicating that the system is one of the ideal platforms for optical breast tumor detection.
KEYWORDS: Modulation, Dynamical systems, Imaging systems, Signal detection, Fluorescence tomography, Field programmable gate arrays, Current controlled current source
Pharmacokinetic diffuse fluorescence tomography (DFT) can describe the metabolic processes of fluorescent agents in biomedical tissue and provide helpful information for tumor differentiation. In this paper, a dynamic DFT system was developed by employing digital lock-in-photon-counting with square wave modulation, which predominates in ultra-high sensitivity and measurement parallelism. In this system, 16 frequency-encoded laser diodes (LDs) driven by self-designed light source system were distributed evenly in the imaging plane and irradiated simultaneously. Meanwhile, 16 detection fibers collected emission light in parallel by the digital lock-in-photon-counting module. The fundamental performances of the proposed system were assessed with phantom experiments in terms of stability, linearity, anti-crosstalk as well as images reconstruction. The results validated the availability of the proposed dynamic DFT system.
The purpose of this work is to introduce and study a novel x-ray beam irradiation pattern for X-ray Luminescence Computed Tomography (XLCT), termed multiple intensity-weighted narrow-beam irradiation. The proposed XLCT imaging method is studied through simulations of x-ray and diffuse lights propagation. The emitted optical photons from X-ray excitable nanophosphors were collected by optical fiber bundles from the right-side surface of the phantom. The implementation of image reconstruction is based on the simulated measurements from 6 or 12 angular projections in terms of 3 or 5 x-ray beams scanning mode. The proposed XLCT imaging method is compared against the constant intensity weighted narrow-beam XLCT. From the reconstructed XLCT images, we found that the Dice similarity and quantitative ratio of targets have a certain degree of improvement. The results demonstrated that the proposed method can offer simultaneously high image quality and fast image acquisition.
Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.
Phase contrast x-ray imaging techniques have shown the ability to overcome the weakness of the low sensitivity of conventional x-ray imaging. Among them, in-line phase contrast imaging, blessed with simplicity of arrangement, is deemed to be a promising technique in clinical application. To obtain quantitative information from in-line phase contrast images, numerous phase-retrieval techniques have been developed. The theories of these phase-retrieval techniques are mostly proposed on the basis of the ideal detector and the noise-free environment. However, in practice, both detector resolution and system noise would have impacts on the performance of these phase-retrieval methods. To assess the impacts of above-mentioned factors, we include the effects of Gaussian shaped detectors varying in the full width at half maximum (FWHM) and system noise at different levels into numerical simulations. The performance of the phase-retrieval methods under such conditions is evaluated by the root mean square error. The results demonstrate that an increase in the detector FWHM or noise level degrades the effect of phase retrieval, especially for objects in small size.
X-ray phase contrast imaging (XPCI) is a novel method that exploits the phase shift for the incident X-ray to form an image. Various XPCI methods have been proposed, among which, in-line phase contrast imaging (IL-PCI) is regarded as one of the most promising clinical methods. The contrast of the interface is enhanced due to the introduction of the boundary fringes in XPCI, thus it is generally used to evaluate the image quality of XPCI. But the contrast is a comprehensive index and it does not reflect the information of image quality in the frequency range. The modulation transfer function (MTF), which is the Fourier transform of the system point spread function, is recognized as the metric to characterize the spatial response of conventional X-ray imaging system. In this work, MTF is introduced into the image quality evaluation of the IL-PCI system. Numerous simulations based on Fresnel - Kirchhoff diffraction theory are performed with varying system settings and the corresponding MTFs were calculated for comparison. The results show that MTF can provide more comprehensive information of image quality comparing to contrast in IL-PCI.
There is a direct evidence that the radiation doses associated with CT scans are associated with an increase in cancer risk. To reduce the radiation dose and simultaneously maintain the CT reconstruction quality, numerous algorithms have been proposed such as compressive sensing (CS) technique. CS theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional methods use. In this study, we mainly consider the relationship between the CT reconstruction quality and two undersampled scan types of CS technique, i.e., the sparse-view scan and limited-view scan. The results demonstrate that an appropriate selection of scan type of CS technique can effectively control the radiation dose.
CW radiance measurements examine the light intensity at a single source-detector location from different detection directions to recover absorption coefficient and reduced scattering coefficient of the turbid medium which is important in treatment planning of minimally invasive laser therapies. In this paper, P9 approximation for radiance is used as the forward model for fitting by considering the balance between computational time and the correctness of the forward model at low albedo and small source detector separation (SDS). By fitting P9 approximation for radiance to the angular radiance Monte Carlo (MC) simulations used as the angular radiance measurements, optical parameters are recovered over a wide range of reduced albedo between 0.69 and 0.99 at small SDS 2mm. The recovery errors of absorption coefficient and reduced scattering coefficient are less than 11.96% and 2.63%, respectively. The effects of the maximum angle used for fitting on optical parameter recovery have been further studied. The results show that the recovery errors of absorption coefficient and reduced scattering coefficient are less than 12% and 3% respectively when the maximum angle is greater than 70 degree.
In vivo tomographic imaging of the fluorescence pharmacokinetic parameters in tissues can provide additional specific and quantitative physiological and pathological information to that of fluorescence concentration. This modality normally requires a highly-sensitive diffuse fluorescence tomography (DFT) working in dynamic way to finally extract the pharmacokinetic parameters from the measured pharmacokinetics-associated temporally-varying boundary intensity. This paper is devoted to preliminary experimental validation of our proposed direct reconstruction scheme of instantaneous sampling based pharmacokinetic-DFT: A highly-sensitive DFT system of CT-scanning mode working with parallel four photomultiplier-tube photon-counting channels is developed to generate an instantaneous sampling dataset; A direct reconstruction scheme then extracts images of the pharmacokinetic parameters using the adaptive-EKF strategy. We design a dynamic phantom that can simulate the agent metabolism in living tissue. The results of the dynamic phantom experiments verify the validity of the experiment system and reconstruction algorithms, and demonstrate that system provides good resolution, high sensitivity and quantitativeness at different pump speed.
Coupling between transport theory and its diffusion approximation in subdomain-based hybrid models for enhanced description of near-field photon-migration can be computationally complex, or even physically inaccurate. We report on a physically consistent coupling method that links the transport and diffusion physics of the photons according to transient photon kinetics, where distribution of the fully diffusive photons at a transition time is provided by a computation-saving auxiliary time-domain diffusion solution. This serves as a complementary or complete isotropic source of the temporally integrated transport equation over the early stage and the diffusion equation over the late stage, respectively, from which the early and late photodensities can be acquired independently and summed up to achieve steady-state modeling of the whole transport process. The proposed scheme is validated with numerical simulations for a cubic geometry.
KEYWORDS: Fluorescence tomography, Data modeling, Tissues, Signal to noise ratio, Instrument modeling, Performance modeling, In vivo imaging, Digital filtering, Image filtering, Electronic filtering
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.
A novel optical accelerometer based on laser self-mixing effect is presented and experimentally demonstrated, which
consists of a mass-loaded elastic-beam assembly and laser self-mixing interferometer. Under external acceleration, an
inertial force is applied to the mass, flexible beams deflect from their equilibrium position. The deflection can be read
out by the self-mixing interferometer. In order to reduce the impact of higher harmonic, wavelet analysis is introduced to
remove singular points. Preliminary results indicate that the resolution is 0.19μg/Hz1/2 within a bandwidth of 100Hz. The
optical accelerometer has the potential to achieve high-precision, compact accelerometers.
In diffuse florescence tomography (DFT), the radiative transfer equation (RTE) and its P1 approximation, i.e. the diffuse equation (DE), have been used as the forward models. Since the assumptions of the diffusion approximation are not valid in particular regions of biological tissue which are close to the collimated light sources and boundaries, not scattering dominated or having void-like sub-domains, the RTE-based DFT methodology has become a focus of investigation. Therefore, we present a RTE-based featured-data scheme for time-domain DFT, which combines the discrete solidangle- element method and the finite element method to obtain numerical solutions of the Laplace-transformed 2D timedomain RTE, with the natural boundary condition and collimating light source model. The scheme is validated using the measurement data from phantom and in-vivo small-animal experiments compared to the DE-based scheme.
It is more complicated to write the analytical expression for the fluorescence simplified spherical harmonics (SPN) equations in a turbid medium, since both the processes of the excitation and emission light and the composite moments of the fluence rate are described by coupled equations. Based on an eigen-decomposition strategy and the well-developed analytical methods of diffusion approximation (DA), we derive the analytical solutions to the fluorescence SPN equations for regular geometries using the Green’s function approach. By means of comparisons with the results of fluorescence DA and Monte Carlo simulations, we have shown the effectiveness of our proposed method and the expected advantages of the SPN equations in the case of small source–detector separation and high absorption.
According to the morphological differences in the vascularization between healthy and diseased tissues, pharmacokinetic-rate images of fluorophore can provide diagnostic information for tumor differentiation, and especially have the potential for staging of tumors. In this paper, fluorescence diffuse optical tomography method is firstly used to acquire metabolism-related time-course images of the fluorophore concentration. Based on a two-compartment model comprised of plasma and extracelluar-extravascular space, we next propose an adaptive-EKF framework to estimate the pharmacokinetic-rate images. With the aid of a forgetting factor, the adaptive-EKF compensate the inaccuracy initial values and emphasize the effect of the current data in order to realize a better online estimation compared with the conventional EKF. We use simulate data to evaluate the performance of the proposed methodology. The results suggest that the adaptive-EKF can obtain preferable pharmacokinetic-rate images than the conventional EKF with higher quantitativeness and noise robustness.
Diffuse florescence tomography (DFT) as a high-sensitivity optical molecular imaging tool, can be applied to in vivo
visualize interior cellular and molecular events for small-animal disease model through quantitatively recovering
biodistributions of specific molecular probes. In DFT, the radiative transfer equation (RTE) and its approximation, such
as the diffuse equation (DE), have been used as the forward models. The RTE-based DFT methodology is more suitable
for biological tissue having void-like regions and the near-source area as in the situations of small animal imaging. We
present a RTE-based scheme for the steady state DFT, which combines the discrete solid angle method and the finite
difference method to obtain numerical solutions of the 2D steady RTE, with the natural boundary condition and
collimating light source model. The approach is validated using the forward data from the Monte Carlo simulation for its
better performances in the spatial resolution and reconstruction fidelity compared to the DE-based scheme.
A region-based approach of image reconstruction using the finite element method is developed for diffuse optical tomography (DOT). The method is based on the framework of the pixel-based DOT methodology and on an assumption that different anatomical regions have their respective sets of the homogeneous optical properties distributions. With this hypothesis, the region-based DOT solution greatly improves the ill-posedness of the inverse problem by reducing the number of unknowns to be reconstructed. The experimental validation of the methodology is performed on a solid phantom employing a multi-channel DOT system of lock-in photon-counting mode, as well as compared with the traditional pixel-based reconstruction results, demonstrate that the proposed DOT methodology presents a promising tool of in vivo reconstructing background optical structures with the aid of anatomical a priori.
Diffuse optical tomography was recognized as one of the most potential methods to in-vivo imaging due to its advantages of non-invasiveness, high sensitivity and excellent specificity etc. This modality aims at portraying the concentration distribution of oxy-hemoglobin and deoxy-hemoglobin statically or dynamically by resolving the optical properties at multiple wavelengths. To further improve the instantaneity and sensitivity of the method, we have developed a continuous-wave diffuse optical tomography system based on lock-in photon-counting technique, which can perform dual-wavelength measurement simultaneously at ultra-high sensitivity. The system was configured by modulating the laser sources at different wavelengths with different frequencies and adopting a single photon-counting block based on the digital lock-in detection for the data demodulation. Phantom experiments were conducted to evaluate the capability of the method. Results have shown that the absorption contrast can be commendably reconstructed, and the system we proposed provides a promising tool for in-vivo imaging.
We derive a modification method to simplify the SPN coupled partial differential equations into some independent equations. The modification leads to significant mathematical simplifications and can be used to calculate the Green’s function of the SPN equations for infinite and semi-infinite turbid medium. The obtained analytical solutions depend on eigenvectors and eigenvalues. Compared with the derived methods based on coupled equations, the derivation process of our proposed method is general, fast and simple. The derived analytical solutions are successfully verified by comparisons with Monte Carlo simulations.
Techniques of time-correlated single-photon counting (TCSPC) have been widely used in diffuse optical tomography (DOT) and diffuse fluorescence tomography (DFT). While a multi-channel TCSPC-based DOT/DFT system can be conveniently constructed using independent modules, the state-of-the-art TCSPC technique has extended its multidimensional function by facilitating a compact and cost-effective design of the multi-channel as well as multi-wavelength data-acquisition. We herein present a revised multi-channel TCSPC system that is based the multidimensional function of the TCSPC device. We also design a series of DOT and DFT experiments to validate effectiveness of the system.
At present, the most widely accepted forward model in diffuse optical tomography (DOT) is the diffusion equation,
which is derived from the radiative transfer equation by employing the P1 approximation. However, due to its validity
restricted to highly scattering regions, this model has several limitations for the whole-body imaging of small-animals,
where some cavity and low scattering areas exist. To overcome the difficulty, we presented a Graphic-Processing-
Unit(GPU) implementation of Monte-Carlo (MC) modeling for photon migration in arbitrarily heterogeneous turbid
medium, and, based on this GPU-accelerated MC forward calculation, developed a fast, universal DOT image
reconstruction algorithm. We experimentally validated the proposed method using a continuous-wave DOT system in the
photon-counting mode and a cylindrical phantom with a cavity inclusion.
To cope with the low quantification in the established optical topography that originates from the excessively simplified computation model based on the modified Lambert-Beer’s Law (MLBL), we propose a least-squares fitting scheme for time-domain optical topography that seeks for data matching between the time-resolved measurement and the model prediction calculated by analytically solving the time-domain diffusion equation in semi-infinite geometry. Our simulative and phantom experiments demonstrate that the proposed curve-fitting method is overall superior to the conventional MLBL-based one in quantitative performance.
The importance of cellular pH has been shown clearly in the study of cell activity, pathological feature, and drug metabolism. Monitoring pH changes of living cells and imaging the regions with abnormal pH-values, in vivo, could provide invaluable physiological and pathological information for the research of the cell biology, pharmacokinetics, diagnostics, and therapeutics of certain diseases such as cancer. Naturally, pH-sensitive fluorescence imaging of bulk tissues has been attracting great attentions from the realm of near infrared diffuse fluorescence tomography (DFT). Herein, the feasibility of quantifying pH-induced fluorescence changes in turbid medium is investigated using a continuous-wave difference-DFT technique that is based on the specifically designed computed tomography-analogous photon counting system and the Born normalized difference image reconstruction scheme. We have validated the methodology using two-dimensional imaging experiments on a small-animal-sized phantom, embedding an inclusion with varying pH-values. The results show that the proposed approach can accurately localize the target with a quantitative resolution to pH-sensitive variation of the fluorescent yield, and might provide a promising alternative method of pH-sensitive fluorescence imaging in addition to the fluorescence-lifetime imaging.
In vivo biomedical imaging using near-infrared light must overcome the effects of highly light scattering, which limit the
spatial resolution and affect image quality. The high-resolution, sensitive and quantitative fluorescence imaging tool is an
urgent need for the applications in small-animal imaging and clinical cancer research. A CT-analogous method for
fluorescence molecular tomography (FMT) on small-animal-sized models is presented to improve the spatial resolution
of FMT to a limit of several millimeters, depending on the size of the tissue region to be imaged. The method combines
FMT physics with the filtered back-projection scheme for image reconstruction of the fan-beam computed tomography,
based on the early-photon detection of time-resolved optical signals, and is suitable for two-dimensional (2D) imaging of
small size biological models. By use of a normalized Born formulation for the inversion, the algorithm is validated using
full time-resolved simulated data for 2D phantom that are generated from a hybrid finite-element and
finite-time-difference photon diffusion modeling, and its superiority in the improvement of the spatial resolution is
demonstrated by imaging different target-to-background contrast ratios.
A fiber-based non-contact scheme of the time-domain diffuse fluorescence yield and lifetime tomography is described
that combines the time-correlated single photon counting technique for high-sensitive, time-resolved detection and
CT-analogous configuration for high throughput data collection. A pilot validation of the methodology is performed for
two-dimensional scenarios using simulated and experimental data. The results demonstrated the potential of the proposed
scheme in improving the image quality.
The importance of cellular pH has been shown clearly in the study of cell activity, pathological feature, drug metabolism,
etc. Monitoring pH changes of living cells and imaging the regions with abnormal pH values in vivo could provide the
physiologic and pathologic information for the research of the cell biology, pharmacokinetics, diagnostics and
therapeutics of certain diseases such as cancer. Thus, pH-sensitive fluorescence imaging of bulk tissues has been
attracting great attention in the regime of near-infrared diffuse fluorescence tomography (DFT), an efficient small-animal
imaging tool. In this paper, the feasibility of quantifying pH-sensitive fluorescence targets in turbid medium is
investigated using both time-domain and steady-state DFT methods. By use of the specifically designed time-domain and
continuous-wave systems and the previously proposed image reconstruction scheme, we validate the method through
2-dimensional imaging experiments on a small-animal-sized phantom with multiply targets of distinct pH values. The
results show that the approach can localize the targets with reasonable accuracy and achieve quantitative reconstruction
of the pH-sensitive fluorescent yield.
A novel method for optical breast imaging was presented based on fluorescence guided diffusion optical tomography
(DOT). In this paper, the time-domain fluorescence parameters (yield and lifetime) were reconstructed based on discrete
wavelet transform at first, then the fluorescence images were used to guide and constrain the diffusion optical
tomography reconstruction, and the image segmentation strategy based on wavelet coefficient was applied to improve
the image quality in DOT. To validate the proposed method, the numerical simulation was performed to demonstrate its
computational efficacy. The results showed the feasibility of this method, and the spatial resolution, quantification and
computational efficiency in fluorescence diffusion optical tomography and DOT were enhanced evidently.
A prototype time-domain fluorescence diffusion optical tomography (FDOT) system using near-infrared light is
presented. The system employs two pulsed light sources, 32 source fibers and 32 detection channels, working separately
for acquiring the temporal distribution of the photon flux on the tissue surface. The light sources are provided by low
power picosecond pulsed diode lasers at wavelengths of 780 nm and 830 nm, and a 1×32-fiber-optic-switch sequentially
directs light sources to the object surface through 32 source fibers. The light signals re-emitted from the object are
collected by 32 detection fibers connected to four 8×1 fiber-optic-switch and then routed to four time-resolved
measuring channels, each of which consists of a collimator, a filter wheel, a photomultiplier tube (PMT)
photon-counting head and a time-correlated single photon counting (TCSPC) channel. The performance and efficacy of
the designed multi-channel PMT-TCSPC system are assessed by reconstructing the fluorescent yield and lifetime
images of a solid phantom.
Quantitative measurements of fluorescent parameters have merited great interest lately for near-infrared fluorescence
diffuse optical tomography - the efficient small animal imaging tool. We present a two-dimensional image reconstruction
method for time-domain fluorescence diffuse optical tomography, which employs the analytical solution to the
Laplace-transformed time-domain photon-diffusion equation to construct the inverse model and introduces a pair of
real-domain transform-factors to effectively separate the fluorescent yield and lifetime parameters from the algebraic
reconstruction technique solutions to the resultant linear inversions. By use of a specifically designed a multi-channel
time-correlated single photon counting system and a normalized Born formulation for the inversion, the proposed
scheme in a circular domain is experimentally validated using small-animal-sized cylindrical phantoms that embed
several fluorescent targets made from 1%-Intralipid solution and differently contrasting fluorescent agents, where the
time-resolved excitation and fluorescence signals are measured on the boundary. The results show that the approach
retrieves the positions and shapes of the targets with a reasonable accuracy and simultaneously achieve quantitative
reconstruction of the fluorescent yield and lifetime.
We present a scheme for fluorescence guided diffusion optical tomography to reconstruct the fluorescence parameters
(yield and lifetime) and optical parameters (absorption and reduced coefficients) based on time-resolved data. In this
paper, the fluorescence parameters were reconstructed at first, then the fluorescence images were used to guide and
constrain the diffusion optical tomography reconstruction, and the binary image segmentation strategy was applied to
improve the image quality in DOT. To validate the proposed method, the numerical simulation was performed to
demonstrate its computational efficacy. The results showed the feasibility of this method, and the spatial resolution,
quantification and computational efficiency in DOT were enhanced evidently.
Near-infrared fluorescence diffuse optical tomography has proven to be an efficient tool for visualizing the
bio-distributions of fluorescent markers in tissue. We present a two-dimensional image reconstruction method for
time-domain fluorescence diffuse optical tomography on a turbid medium of circular domain. The methodology is based
on a linear generalized pulse spectrum technique that employs the analytical solution to the Laplace-transformed
time-domain photon-diffusion equation to construct a Born normalized inverse model. A pair of real domain
transform-factors is introduced to simultaneously reconstruct the fluorescent yield and lifetime images and the resultant
linear inversions are solved using an algebraic reconstruction technique. The algorithm is validated using simulated data,
and the spatial resolution, noise-robustness and so on are assessed. The experimental validation is performed using a
multi-channel time-correlated single-photon-counting system and a cylinder phantom that embeds a fluorescent target
made from 1%-Intralipid solution and Cy5.5 agent. The results show that the approach retrieves the position and shape of
the target with a reasonable accuracy.
Fluorescence lifetime tomography (FLT) is an emerging imaging modality that seeks for recovering distributions of the
fluorescent yield and lifetime inside in vivo tissues. This technique, mainly based on time-domain instrumentation, has
found promising applications in small-animal imaging for studying tumor pathology and for drug development. As one
of the model-based imaging methods, FLT can be finalized with inverting an underdetermined, ill-posed linear system
with regard to both the parameters, for which several methods has been adopted. This paper concisely revises the main
facts of three commonly-used linear inversions: algebraic reconstruction technique, truncated singular value
decomposition and conjugate gradient descent, and presents a comparative investigation on these methods in terms of the
image quality and noise robustness.
Time-domain fluorescence diffuse optical tomography (FDOT) can provide information, not only concerning the
localization of specific fluorophores, but also about the local fluorophore environment. We present a method based on
linear inversion algorithm to reconstruct images of fluorescence yield and lifetime from time-resolved data. To provide
efficient solutions, we convert the data type by Laplace transform and adapt normalized Born ratio for its advantages in
fluorescence mode. The methodology is experimentally validated in reflection and transmittance measurements by use of
time-correlation single photon counting system. We experimentally validate that the proposed scheme can achieve
simultaneous three-dimensional reconstruction of the fluorescent yield and lifetime. The results show that for the
positions, sizes and shapes of the targets, there are some deviation in reflection measurement, the quality in transmittance
one is more satisfied.
Non-contact scheme is prevalent to diffuse fluorescence tomography (FDT) since it facilitates instrumentation as well as
simplifies experimental procedure. Although non-contact FDT generally uses CCD camera as detectors to achieve high
throughput of data collection, a fiber-based implementation can make full use of well-established high-sensitive and
time-resolved detection techniques. Therefore, a system that combines the fiber-based time-resolved detection and the
non-contact geometry of optodes would be significantly attractive, which also means a more complex modeling of
photon migration. This paper presents detailed computational aspects of the fiber-based non-contact DFT, including both
the forward and inverse models. A pilot validation of the method is performed using simulated data for a
two-dimensional case.
A full three-dimensional, featured-data algorithm for time-domain diffuse fluorescence tomography is presented, which
inverts the Laplace-transformed time-domain coupled diffusion equations and employs a pair of real-domain
transform-factors to effectively separate the fluorescent yield and lifetime parameters. By use of a multi-channel
time-correlation single photon counting system and a normalized Born formulation for the inversion, the proposed
scheme is experimentally validated to achieve simultaneous reconstruction of the fluorescent yield and lifetime
distributions with a reasonable accuracy.
KEYWORDS: Luminescence, Tomography, Fluorescence tomography, Diffusion, Data modeling, Atrial fibrillation, 3D modeling, Reconstruction algorithms, Finite element methods, Single photon
We propose a 3D scheme for time-domain fluorescence molecular tomography within the normalized Born-ratio
formulation. A finite element method solution to the Laplace transformed time-domain coupled diffusion equations is
employed as the forward model, and the resultant linear inversions at two distinct transform-factors are solved with an
algebraic reconstruction technique to separate fluorescent yield and lifetime images. By use of a multichannel
time-correlation single photon counting system, we experimentally validate that the proposed scheme can achieve
simultaneous reconstruction of the fluorescent yield and lifetime distributions with a reasonable accuracy.
A full time-resolved scheme that has been previously applied in diffuse optical tomography is extended to time-domain
fluorescence diffuse optical tomography regime, based on a finite-element-finite-time-difference photon diffusion
modeling and a Newton-Raphson inversion framework. The merits of using full time-resolved data are twofold: it helps
evaluate the intrinsic performance of time-domain mode for improvement of image quality and set up a 'gold standard'
for the development of computationally efficient featured-data-based algorithms, and provides a self-normalized
implementation to preclude the necessary for the scaling-factor calibration and spectroscopic-feature assessments of the
system as well as to overcome the adversity of system instability. We validate the proposed methodology using simulated
data, and evaluate its performances in simultaneously recovering the fluorescent yield and lifetime as well as its
superiority to the featured-data one in the fidelity of image reconstruction.
KEYWORDS: Luminescence, Monte Carlo methods, Sensors, Reconstruction algorithms, Signal to noise ratio, Atrial fibrillation, Diffuse optical tomography, Detection and tracking algorithms, Finite element methods, Photon transport
An image reconstruction scheme for time-domain fluorescence diffuse optical tomography is proposed using a
reflection-mode for a semi-infinite turbid geometry. The method is based on a generalized pulse spectrum technique that
employs analytic expressions of the Laplace-transformed time-domain photon-diffusion model to construct a Born
normalized inverse model, and a pair of real domain transform-factors to separate distributions of the fluorescent yield
and lifetime. The methodology is validated with a specifically-developed fluorescent Monte-Carlo simulator or
finite-element-based methods and its robustness to the background uncertainties is investigated.
A linear generalized pulse spectrum technique for image reconstruction of fluorescence molecular tomography is
proposed. The algorithm employs a finite element method solution to the Laplace-transformed coupled diffusion
equations and can simultaneously reconstruct both fluorescent yield and lifetime images of fluorophores. The proposed
algorithm was validated using simulated data for 3D phantoms. We investigated the ability of the algorithm to
reconstruct the fluorescent yield and lifetime at different region, contrasted the imaging quality of different target
lifetime and proved the noise-robustness by using noisy data with different signal-to-noise ratio. The results show that
the approach accurately retrieves the position and shape of the target and prove the effectiveness of the methodology.
Surface Acoustic Waves (SAW) propagating in a semi-infinite, anisotropic medium Lithium niobate(LiNbO3) are discussed. Integrated Acousto-Optical Tunable Filters (AOTF) have demonstrated wide application in various fields of laser technology, spectroscopy, optoelectronics and optical signal processing as well as wavelength division multiplexed (WDM) networks. We fabricated practical quasi-collinear integrated AOTF.
In an earlier approach, the 2-D acoustical field profiles on the substrate region are often calculated with BPM. In this
paper, we present a new approach based on the finite element - artificial transmitting boundary method and calculate the
2-D acoustical field on the substrate region.
HLA (High Level Architecture) is a new architecture of distributed interactive simulation developed from DIS. We put forward a technical scheme of a distributed interactive simulator based on HLA, and bring forward a concept about distributed oriented-object simulator's engine, as well as an in-depth study on its architecture. This provides a new theoretical and practical approach in order to turn simulator's architecture into HLA.
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