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.
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.
To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are associated with Ki67 expression of breast cancer. In this institutional review board approved retrospective study, we collected 377 cases Chinese women who were diagnosed with invasive breast cancer in 2015. This cohort included 53 low-Ki67 expression (Ki67 proliferation index less than 14%) and 324 cases with high-Ki67 expression (Ki67 proliferation index more than 14%). A binary-classification of low- vs. high- Ki67 expression was performed. A set of 52 quantitative radiomics features, including morphological, gray scale statistic, and texture features, were extracted from the segmented lesion area. Three most common machine learning classification methods, including Naive Bayes, k-Nearest Neighbor and support vector machine with Gaussian kernel, were employed for the classification and the least absolute shrink age and selection operator (LASSO) method was used to select most predictive features set for the classifiers. Classification performance was evaluated by the area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. The model that used Naive Bayes classification method achieved the best performance than the other two methods, yielding 0.773 AUC value, 0.757 accuracy, 0.777 sensitivity and 0.769 specificity. Our study showed that quantitative radiomics imaging features of breast tumor extracted from DCE-MRI are associated with breast cancer Ki67 expression. Future larger studies are needed in order to further evaluate the findings.
Endoscopic DOT has the potential to apply to cancer-related imaging in tubular organs. Although the DOT has relatively large tissue penetration depth, the endoscopic DOT is limited by the narrow space of the internal tubular tissue, so as to the relatively small penetration depth. Because some adenocarcinomas including cervical adenocarcinoma are located in deep canal, it is necessary to improve the imaging resolution under the limited measurement condition. To improve the resolution, a new FOCUSS algorithm along with the image reconstruction algorithm based on the effective detection range (EDR) is developed. This algorithm is based on the region of interest (ROI) to reduce the dimensions of the matrix. The shrinking method cuts down the computation burden. To reduce the computational complexity, double conjugate gradient method is used in the matrix inversion. For a typical inner size and optical properties of the cervix-like tubular tissue, reconstructed images from the simulation data demonstrate that the proposed method achieves equivalent image quality to that obtained from the method based on EDR when the target is close the inner boundary of the model, and with higher spatial resolution and quantitative ratio when the targets are far from the inner boundary of the model. The quantitative ratio of reconstructed absorption and reduced scattering coefficient can be up to 70% and 80% under 5mm depth, respectively. Furthermore, the two close targets with different depths can be separated from each other. The proposed method will be useful to the development of endoscopic DOT technologies in tubular organs.
In a typical laminar optical tomography (LOT) system, the dip-angle between the incident light (or the emitting light) and the normal of the detection plane randomly changes during raster-scanning. The inconstant dip-angle causes consistency between the measurement and the light transportation model where a fixed dip-angle of the incident light is generally required. To eliminate the effect from this dip angle, methods such as keeping the angle unchangeable by moving the phantom instead of scanning the light were investigated. In this paper, a LOT system with small dip-angle over the whole detection range is developed. Simulation and experimental evaluation show that the dip-angle of the modified system is much smaller than that of the traditional system. For example, the relative angle between the two incident light at (x=0mm, y=0mm) and (x=0mm, y=2.5mm) on the image plane is about 0.7° for the traditional system while that is only about 0.02° for the modified system. The main parameters of the system are also evaluated and an image reconstruction algorithm is developed based on Monte Carlo simulation. The reconstructed images show that the spatial resolution and quantitative ratio is improved by the modified system without loss of the scanning speed.
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.
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.
A combined time-domain diffuse fluorescence and optical tomographic system is proposed based on the multi-channel
time-correlated single-photon counting (TCSPC) technique, aiming at enhancing the reliability of breast diffuse optical
tomography. The system equipped with two pulsed laser diodes at wavelengths of 780 nm and 830 nm that are specific
to the maximal excitation and emission of the FDA-approved ICG dye, and works with a 4-channel TCSPC module to
acquire the temporal distributions of the light re-emissions 32 boundary sites of tissues in a tandem serial-to-parallel
mode. The performance and efficacy of the system are investigated with phantom experiments for diffuse optical
tomography (DOT), as well as fluorescence-guided DOT.
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.
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.
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.
We present a new algorithm for camera calibration using two concentric circles, which is a linear approach. In the calibration, a pinhole camera model is used. Different from previous methods, we take the projective equations of 3-D circles, which include the intrinsic parameter matrix of the camera, as the basis of our calibration approach. According to the special structure of the projective equations in algebra, we can get a linear equation system about the intrinsic parameters. After enough equations are constructed, the calibration can be easily finished. With at least three images of the two concentric circles, all five intrinsic parameters can be recovered. Experiments using computer simulated data and real data demonstrate the robustness and accuracy of our method.
In this paper, Image inpainting based on different displacement view images is proposed, which is the problem of filling
in the occluded or damaged regions of an image by the visible information from other different displacement view
images. The key problems are how to convert the visible information in different displacement view images to
consistence and to use available information to repair the target image. The first step of our method is to divide all
images into different scene planar regions and to transform all image regions into current view by projective
transformation computed from the matched points; thus the visible information can be directly used, then a new
inpainting algorithm based on image fusion with spatial frequency is applied. The experiment shows good and
harmonious results for the repaired image.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.