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.
We presented a novel dual-wavelength diffuse optical imaging system which can perform 2-D or 3-D imaging fast and high-sensitively for monitoring the dynamic change of optical parameters. A newly proposed lock-in photon-counting detection method was adopted for week optical signal collection, which brought in excellent property as well as simplified geometry. Fundamental principles of the lock-in photon-counting detection were elaborately demonstrated, and the feasibility was strictly verified by the linearity experiment. Systemic performance of the prototype set up was experimentally accessed, including stray light rejection and inherent interference. Results showed that the system possessed superior anti-interference capability (under 0.58% in darkroom) compared with traditional photon-counting detection, and the crosstalk between two wavelengths was lower than 2.28%. For comprehensive assessment, 2-D phantom experiments towards relatively large dimension model (diameter of 4cm) were conducted. Different absorption targets were imaged to investigate detection sensitivity. Reconstruction image under all conditions was exciting, with a desirable SNR. Study on image quality v.s. integration time put forward a new method for accessing higher SNR with the sacrifice of measuring speed. In summary, the newly developed system showed great potential in promoting detection sensitivity as well as measuring speed. This will make substantial progress in dynamically tracking the blood concentration distribution in many clinical areas, such as small animal disease modeling, human brain activity research and thick tissues (for example, breast) diagnosis.
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.
Radiance is sensitive to the variations of tissue optical parameters, such as absorption coefficient μa, scattering coefficient μs, and anisotropy factor g. Therefore, similar to fluence, radiance can be used for tissue characterization. Compared with fluence, radiance has the advantage of offering the direction information of light intensity. Taking such advantage, the optical parameters can be determined by rotating the detector through 360 deg with only a single optode pair. Instead of the translation mode used in the fluence-based technologies, the Rotation mode has less invasiveness in the clinical diagnosis. This paper explores a new method to obtain the optical properties by measuring the distribution of light intensity in liquid phantom with only a single optode pair and the detector rotation through 360 deg. The angular radiance and distance-dependent radiance are verified by comparing experimental measurement data with Monte Carlo (MC) simulation for the short source-detector separations and diffusion approximation for the large source-detector separations. Detecting angular radiance with only a single optode pair under a certain source-detection separation will present a way for prostate diagnose and light dose calculation during the photon dynamic therapy (PDT).
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.
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.
Near infrared (NIR) diffuse optical imaging (DOI) are increasingly used to detect hemodynamic changes in the cerebral cortex induced by brain activity. For the sake of capturing the dynamic changes in real-time imaging applications, such as brain imaging, digital lock-in detection technique could be applied. Using particular modulation and sampling constraints and averaging filters, one can achieve optimal noise reduction and discrimination between sources in different modulation frequencies. In this paper, we designed and developed a compact dual-wavelength continuous wave DOI system based on the single photon counting digital lock-in detection technique. According to the frequency division multiplexing light source coding technique, sine waves with different frequencies are generated so as to amplitude-modulate two laser sources with different wavelengths. The diffuse light is detected by photomultiplier tubes (PMTs) and the data is collected by the detection channels simultaneously. A digital lock-in detection circuit for photon counting measurement module and a DDS (Direct Digital Synthesizer) signal generation module were separately implemented in two FPGA development platforms. To validate the feasibility and functionality of the developed system, a series of experimental tests were performed. Preliminary results show that the system could be used to reconstruct the absorption coefficient and could separate the response of the dual wavelength sources which were modulated by sine signals of different frequencies effectively. In addition, several imaging experiments were performed on the semi-infinite solid phantom to find the “best imaging position” for a given source-detector placement.
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 biomedical optics, the Monte Carlo (MC) simulation is widely recognized as a gold standard for its high accuracy and
versatility. However, in fluorescence regime, due to the requirement for tracing a huge number of the consecutive events
of an excitation photon migration, the excitation-to-emission convention and the resultant fluorescent photon migration
in tissue, the MC method is prohibitively time-consuming, especially when the tissue has an optically heterogeneous
structure. To overcome the difficulty, we present a parallel implementation of MC modeling for fluorescence propagation
in tissue, on the basis of the Graphics Processing Units (GPU) and the Compute Unified Device Architecture (CUDA)
platform. By rationalizing the distribution of blocks and threads a certain number of photon migration procedures can be
processed synchronously and efficiently, with the single-instruction-multiple-thread execution mode of GPU. We have
evaluated the implementation for both homogeneous and heterogeneous scenarios by comparing with the conventional
CPU implementations, and shown that the GPU method can obtain significant acceleration of about 20-30 times for
fluorescence modeling in tissue, indicating that the GPU-based fluorescence MC simulation can be a practically effective
tool for methodological investigations of tissue fluorescence spectroscopy and imaging.
Traditionally, volume based finite element method (FEM) or finite difference method (FDM) are applied to the forward
problem of the time-domain diffuse fluorescence tomography (DFT), this paper presents a new numerical method for
solving the problem: the boundary element method (BEM). Using BEM forward solver is explored as an alternative to
the FEM or FDM solution methodology for the elliptic equations used to model the generation and transport of
fluorescent light in highly scattering media. In contrast to the FEM or FDM, the boundary integral method requires only
representation of the surface meshes, thus requires many fewer nodes and elements than the FEM and FDM. By using
BEM forward solver for time-domain DFT, we can simultaneously reconstruct both fluorescent yield and lifetime images.
The results have demonstrated that the BEM is suitable for solving the forward problem of time-domain DFT.
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.
Diffuse fluorescence tomography (DFT) provides spatial distributions of fluorescence parameters by measuring
fluorescence signals of probes or agents that are targeted to interior specific molecules or tissues. The potential
applications of DFT can be found in drug development and early tumor diagnosis. This work proposes a CT-analogous
mode of DFT, where the imaging chamber is impinged by collimated beam from a fiber-coupled laser diode and the
resultant fluorescence re-emissions on the opposite side, i.e., the so-called "projections", are collected by eight detection
fibers placed from 101.25º to 258.75º perspectives opposite to the incidence that are then successively filtered out into a
photon-counting channel for quantification. By rotating the imaging chamber or phantom at an angular, the system
acquires the "projections" of surface-emitted fluorescence under different perspectives as a CT system does. This ease of
acquiring a large data-set enables realization of high-quality imaging. Pilot experiments on phantoms with Cy5.5-target
embedded have validated the efficacy of the proposed method.
We obtain absorption and scattering reconstructed images by incorporating a priori information of target location
obtained from fluorescence diffuse optical tomography (FDOT) into the diffuse optical tomography (DOT). The main
disadvantage of DOT lies in the low spatial resolution resulting from highly scattering nature of tissue in the
near-infrared (NIR), but one can use it to monitor hemoglobin concentration and oxygen saturation simultaneously, as
well as several other cheomphores such as water, lipids, and cytochrome-c-oxidase. Up to date, extensive effort has been
made to integrate DOT with other imaging modalities such as MRI, CT, to obtain accurate optical property maps of the
tissue. However, the experimental apparatus is intricate. In this study, DOT image reconstruction algorithm that
incorporates a prior structural information provided by FDOT is investigated in an attempt to optimize recovery of a
simulated optical property distribution. By use of a specifically designed multi-channel time-correlated single photon
counting system, the proposed scheme in a transmission mode is experimentally validated to achieve simultaneous
reconstruction of the fluorescent yield, lifetime, absorption and scattering coefficient. The experimental results
demonstrate that the quantitative recovery of the tumor optical properties has doubled and the spatial resolution improves
as well by applying the new improved method.
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.
KEYWORDS: Diffusion, Monte Carlo methods, Radiative transfer, Scattering, Spherical lenses, Animal model studies, Absorption, Finite element methods, Tissues, Light scattering
In this article, we derive the two-dimensional spherical harmonics equations to three-order (P3) of Radiative Transfer
Equation for anisotropic scattering. We also solved this equations using Galerkin finite element method and compared
the solutions with the first-order diffusion equation and Monte Carlo simulation. the benchmark problems are tested,
and we found that the developed three-order model with high absorb coefficient is able to significantly improve the
diffusion solution in circle geometry, and the radiance distribution close to light source is more accurate. It is significant
for accurate modeling of light propagation in small tissue geometries in small animal imaging. Then, the inverse model
for the simultaneous reconstruction of the absorption images is proposed based on P3 equations, and the feasibility and
effectiveness of this method are proved by the simulation.
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