KEYWORDS: Raman spectroscopy, Tomography, Optical tomography, Imaging systems, Signal detection, 3D image processing, 3D image reconstruction, Projection systems
Volumetric imaging enables rapid, quantitative and global measurements of cells, tissues or organisms to obtain their biomolecular information and has become a powerful tool for studying cellular metabolism, brain function and developmental biology. Optical projection tomography (OPT) plays an important role in whole-body imaging of cells, organs, embryos and organisms because it enables three-dimensional (3D) imaging with high spatial and temporal resolution of samples at the millimeter level. However, the OPT technique relies on fluorescent labels for chemical targeting, which can perturb the biological function of living system. As a label-free molecular imaging technique, widefield Raman imaging enables high-resolution analysis of large field-of-view samples. Its combination with projection tomographic strategy enables high-resolution 3D imaging of large-scale samples in a label-free manner. However, this technique was failure to determine the tissue microstructure and specific spatial distribution. Here, we proposed a concept of new label free volumetric imaging, dual-modality of optical-Raman projection tomography. In this concept, Raman projection tomography was assigned to achieve volumetric imaging of chemical composition and distribution in a 3D volume, and the OPT was used to obtain structural information of the 3D volume with micron-level spatial resolution. We further homebuilt a dual-modality imaging system for optical-Raman projection tomography and the feasibility of the system was validated by imaging polystyrene microspheres and dimethyl sulfoxide. Finally, we demonstrated the application potential by a series of bio-sample experiments.
KEYWORDS: Raman spectroscopy, Remote sensing, Gaussian beams, Chemical analysis, Bessel beams, Analytical research, Tablets, Stomach, Skin, Signal to noise ratio
To meet the diversity needs of diagnosis, treatment or prevention of diseases, different pharmaceutical dosage forms are designed and manufactured. The main role of each dosage form is drug carrier. However, changing forms might have some other different effects in clinical usages. For example, the capsule and tablets are absorbed by the intestine and stomach respectively, solutions and patches can act directly on the surface of skin etc. The quantity and quality analysis of the main drug in different form is a key issue in quality control. Therefore, it is a meaningful research of developing a facility method to detect the drug in different dosage forms. The traditional drug detection methods principally analyze and evaluate the performance through chemical reactions, photo-electricity or electrophoresis. However, these methods will cause damage to the samples. Owing to the non-invasive, non-destructive and label-free characteristics, Raman spectroscopy (RS) technique plays an important role in different fields. The current RS setup uses Gaussian beam as the excitation light, which can provide higher signal-to-noise in the thin or transparent sample. However, the Gaussian beam dispersed rapidly in the scattering medium, it is not conducive to in vivo or deep imaging. The Bessel beam having long focusing characteristics and self-reconstructing properties may provide solution to this problem. We here presented a new scheme for RS, which used a Bessel beam as the excitation light. The feasibility and effectiveness of the proposed scheme for detecting the drug in different pharmaceutical dosage forms were verified by series experiments.
Multispectral Photoacoustic Tomography (MSPAT) is capable of visualizing the concentration distribution of various chromophores in biological tissues, where the unmixing process is usually performed with the spectral fitting method that requires the absorption spectral signatures of all chromophores in the tissue to be known. However, due to the changes of spectral signatures of some exogenous contrast agents in vitro and in vivo, the conventional fitting method will be hindered. Although the blind unmixing algorithms do not require the exact absorption spectrum of each chromophore in advance, it is often sensitive to noise, which may lead to low quantitative results. Considering that the non-negativity of concentration distribution and absorption spectra of the chromophores as well as the sparsity of concentration image of exogenous contrast agent in the gradient domain, we herein propose a modified MSPAT implementation that utilizes a non-negative matrix factorization iterative reconstruction framework with the support of a priori information of spectral signature of oxy-/deoxy-hemoglobin and valid sparsity regularization during the iteration. Consequently, the spectral signature of the exogenous contrast agent and the concentration distribution of each chromophore can be recovered simultaneously. The proposed approach has been validated by simulation and in vivo experiments, exhibiting promising performances in image fidelity even when the multi-wavelength photoacoustic tomographic images used for spectral unmixing are affected by noise or reconstruction artifacts.
Near infrared diffuse optical tomography (DOT) is a significant potential means of detecting breast cancer. Compared with other system structures, the parallel-plate scanning mode has such advantages like adapting to different breast size, as well as increasing the transmission of light by compressing. Traditional parallel-plate DOT systems utilized the fibers for photon transmission and photomultiplier tube (PMT) or CCD for photon detection, which resulted in the high complexity and cost. In this study, we propose a fiber-free parallel-plate continuous-wave DOT system for breast cancer detection based on Silicon photomultiplier (SiPM) and multi-wavelength light emitting diode (LED). 50 three-wavelength (660 nm, 750nm and 840nm) LEDs are arranged in a printed circuit board (PCB) array as the source plate. Parallel to this plate, the other plate with 56 silicon photomultipliers (SiPM) arranged is designed as the detection plate. The control of the light source excitation and the detection of the SiPMs output are implemented by a module based on a data acquisition card. The structure of proposed system is very simple, and the acquisition time is no more than 5 minutes. The feasibility of the system was verified by polyoxymethylene and agar phantom experiments, which indicated that the parallel-plate system can accurately reconstruct optical parameters.
The quad-head PET system has a compact structure which leads to the depth of interaction (DOI) blurring. The Monte Carlo (MC) simulation can eliminate the DOI effect significantly, and it has been utilized in the dual-head PET systems. For the quad-head PET system, the geometric symmetry is less, which makes the MC simulation difficult. The multi-ray method combined with the DOI model can also relieve the effect of the DOI blurring, but it is time-consumed. In this study, we focus on the rapid construction of the system response matrix (SRM) based on geometric symmetries for the multi-ray method. During the construction of the SRM, the SRM is divided into two parts: the SRM of the opposite detectors and the SRM of the adjacent detectors. The general processor unit (GPU) is utilized to improve the computation speed. The result shows that the computation time is largely decreased when the geometric symmetries are used. The simulation experiments indicate that the data of adjacent detector heads and the DOI model are helpful to improve the quality of the quad-head PET reconstruction.
Frequency domain diffuse optical tomography (FD-DOT) has been considered as a reliable method to quantify the absolute optical properties of tissues. In the conventional FD-DOT, PMTs coupled with optical fiber bundles were used as the detectors. Thus, the imaging system was expensive and complex in system structure. In this study, we propose to utilize the silicon photomultiplier (SiPM) to replace the PMT as the detectors in the FD-DOT system. SiPM can provide the similar level of gain as PMT. Meanwhile its price is much lower than PMT, and the use of optical fiber bundles can be avoided, which makes it possible to build a simple structure system. The feasibility of the SiPM based FD-DOT was studied in the experiment. A 660nm laser diode was utilized as the source to irradiate the phantom, and it was modulated from 10MHz to 40MHz with the step size 10MHz. The SiPM detectors with 1 mm2 detection area were used to collect the photons emitted from the phantom. We measured in several different source-detector distances for each modulation frequency, during which the bias voltage of SiPM remained constant. The results showed that we could restore the linear relationship between the phase lag and the transmission distance. We also obtained the expected linear curve of the logarithm of the product of the amplitude and distance versus transmission distance. In addition, the absorption and scattering coefficients of the phantom were calculated by the slope of the fitting curve, which showed a good consistency at different modulation frequencies. The experiments results illuminated that it is feasible to build a FD-DOT based on SiPM.
Bioluminescence tomography (BLT) is a promising optical imaging tool broadly used in preclinical research to observe and quantify the distribution of bioluminescent markers in small animal models. However, due to the highly scattering property of the biological tissues and the limited surface measurements, fast and precise reconstruction in BLT remains a challenging problem. Permissible source region is a cost-effective strategy to partially solve the problem. In this paper, we present a matched filtering based strategy to extract the permissible region (PSR) adaptively for bioluminescence tomography. First, a digital matched filter is formulated according to the forward weight matrix, then the surface measurements are filtered and the permissible source region is extracted according to the first several biggest outputs of the matched filter larger than a threshold value, and finally the bioluminescent source in the permissible source region is recovered. Numerical simulation experiments are performed to evaluate the performance of the proposed method. The results show that the number of unknowns can be significantly reduced even using a small threshold value and the BLT reconstruction quality can be improved with appropriate PSR.
Optical projection tomography(OPT) provides an approach to recreating three-dimensional images of small biological specimens. Light traverses through a straight line to achieve a homogeneous illumination of the specimen. As the specimens in the conventional OPT could not survive or the survival time was too short, this paper proposes a new type of sample fixation method for OPT imaging. The specimen was anaesthetized in a petri dish, and the dish was fixed under the rotational stage of our homemade OPT system for imaging. This method can reduce the damage to the specimen and be more conducive to the continuous observation for in vivo OPT. However, the sample fixation causes the problem of insufficient sampling. To obtain optical projection tomographic image with insufficient samples, this paper uses the iterative reconstruction algorithm combining with the prior information to solve the inverse reconstruction problem.
KEYWORDS: Reconstruction algorithms, Image quality, Tomography, Raman spectroscopy, 3D image processing, Head, 3D acquisition, Data modeling, Data acquisition, Sensors
As an emerging volumetric imaging technique, Stimulated Raman projection tomography (SRPT) can provide quantitative distribution of chemical components in a three-dimensional (3D) volume, with a label-free manner. Currently, the filtered back-projection (FBP) algorithm is used to reconstruct the 3D volume in SRPT. However, to obtain a satisfactory reconstruction result, the FBP algorithm requires a certain amount of projection data, usually, at least 180 projections in a half circle. This leads to a long data acquisition time and hence limits dynamic and longitudinal observation of living systems. Iterative reconstruction from sparsely sampled data may reduce the total data acquisition time by reducing the projections used in the reconstruction. In this work, two total variation regularization based iterative reconstruction algorithms were selected and used in SRPT, including the simultaneous algebra reconstruction technique (SART) and the two-step iterative shrinkage/thresholding algorithm (TwIST). The well-known distance-driven model was utilized as the forward and back-projectors. We evaluated these two algorithms with numerical simulations. Using the original image as the reference, we calculated the quality of the reconstructed images. Simulation results showed that both the SART and TwIST performed better than the FBP algorithm, with larger values of the structural similarity (SSIM). Furthermore, the number of projection images can be largely reduced when the iterative reconstruction algorithm was used. Especially when the SART was used, the projection number can be reduced to 15, providing a satisfactory reconstruction image (SSIM is larger than 0.9).
For early detection and targeted therapy, receptor expression profiling is instrumental to classifying breast cancer into
sub-groups. In particular, human epidermal growth factor receptor 2 (HER2) expression has been shown to have both
prognostic and predictive values. Recently, an increasingly more complex view of HER2 in breast cancer has emerged
from genome sequencing that highlights the role of inter- and intra-tumor heterogeneity in therapy resistance. Studies on
such heterogeneity demand high-content, high-resolution functional and molecular imaging in vivo, which cannot be
achieved using any single imaging tool. Clearly, there is a critical need to develop a multimodality approach for breast
cancer imaging. Since 2006, grating-based x-ray imaging has been developed for much-improved x-ray images. In 2014,
the demonstration of fluorescence molecular tomography (FMT) guided by x-ray grating-based micro-CT was reported
with encouraging results and major drawbacks. In this paper, we propose to integrate grating-based x-ray tomography
(GXT) and high-dimensional optical tomography (HOT) into the first-of-its-kind truly-fused GXT-HOT (pronounced as
“Get Hot”) system for imaging of breast tumor heterogeneity, HER2 expression and dimerization, and therapeutic
response. The primary innovation lies in developing a brand-new high-content, high-throughput x-ray optical imager
based on several contemporary techniques to have MRI-type soft tissue contrast, PET-like sensitivity and specificity, and
micro-CT-equivalent resolution. This system consists of two orthogonal x-ray Talbot-Lau interferometric imaging chains
and a hyperspectral time-resolved single-pixel optical imager. Both the system design and pilot results will be reported in
this paper, along with relevant issues under further investigation.
Laser sheet microscopy is a widely used imaging technique for imaging the three-dimensional distribution of a fluorescence signal in fixed tissue or small organisms. In laser sheet microscopy, the stripe artifacts caused by high absorption or high scattering structures are very common, greatly affecting image quality. To solve this problem, we report here a two-step procedure which consists of continuously acquiring laser sheet images while vertically displacing the sample, and then using the variational stationary noise remover (VSNR) method to further reduce the remaining stripes. Images from a cleared murine colon acquired with a vertical scan are compared with common stitching procedures demonstrating that vertically scanned light sheet microscopy greatly improves the performance of current light sheet microscopy approaches without the need for complex changes to the imaging setup and allows imaging of elongated samples, extending the field of view in the vertical direction.
Fluorescence molecular tomography (FMT) is an important imaging technique of optical imaging. The major challenge of the reconstruction method for FMT is the ill-posed and underdetermined nature of the inverse problem. In past years, various regularization methods have been employed for fluorescence target reconstruction. A comparative study between the reconstruction algorithms based on l 1 -norm and l 2 -norm for two imaging models of FMT is presented. The first imaging model is adopted by most researchers, where the fluorescent target is of small size to mimic small tissue with fluorescent substance, as demonstrated by the early detection of a tumor. The second model is the reconstruction of distribution of the fluorescent substance in organs, which is essential to drug pharmacokinetics. Apart from numerical experiments, in vivo experiments were conducted on a dual-modality FMT/micro-computed tomography imaging system. The experimental results indicated that l 1 -norm regularization is more suitable for reconstructing the small fluorescent target, while l 2 -norm regularization performs better for the reconstruction of the distribution of fluorescent substance.
As a high-sensitivity imaging modality, bioluminescence tomography can reconstruct the three-dimensional (3-D) location of an internal luminescent source based on the 3-D surface light distribution. However, we can only get the multi-orientation two-dimensional (2-D) bioluminescence distribution in the experiments. Therefore, developing an accurate universal registration method is essential for following bioluminescent source reconstruction. We can then map the multi-orientation 2-D bioluminescence distribution to the 3-D surface derived from anatomical information with it. We propose a 2-D -to-3-D registration method based on iterated optimal projection and applied it in a registration and reconstruction study of three transgenic mice. Compared with traditional registration methods based on the fixed points, our method was independent of the markers and the registration accuracy of the three experiments was improved by 0.3, 0.5, and 0.4 pixels, respectively. In addition, based on the above two registration results using the two registration methods, we reconstructed the 3-D location of the inner bioluminescent source in the three transgenic mice. The reconstruction results showed that the average error distance between the center of the reconstructed element and the center of the real element were reduced by 0.32, 0.48, and 0.39 mm, respectively.
As one of molecular imaging, bioluminescence tomography (BLT) aims to recover internal source from surface
measurement. Being an ill-posed inverse problem, BLT source reconstruction is usually converted to an optimization
problem through regularization. In this contribution, we build a bimodal hybrid imaging system consisting of BLT and
micro-CT, and then propose an improved source reconstruction method based on adjoint diffusion equations (ADEs).
Compared with conventional methods based on constrained minimization problem (CMP), ADEs-based method replaces
expensive iterative computation with solving a group of linear ADEs. Given surface flux density, internal source power
density and photon fluence rate can be efficiently determined in one step. Both numerical and physical experiments are
performed to evaluate the bimodal BLT/micro-CT imaging system and this novel reconstruction method. The relevant
results demonstrate the feasibility and potential of this source reconstruction method.
Gastric cancer is the second cause of cancer-related death in the world, and it remains difficult to cure because it has
been in late-stage once that is found. Early gastric cancer detection becomes an effective approach to decrease the gastric
cancer mortality. Bioluminescence tomography (BLT) has been applied to detect early liver cancer and prostate cancer
metastasis. However, the gastric cancer commonly originates from the gastric mucosa and grows outwards. The
bioluminescent light will pass through a non-scattering region constructed by gastric pouch when it transports in tissues.
Thus, the current BLT reconstruction algorithms based on the approximation model of radiative transfer equation are not
optimal to handle this problem. To address the gastric cancer specific problem, this paper presents a novel reconstruction
algorithm that uses a hybrid light transport model to describe the bioluminescent light propagation in tissues. The
radiosity theory integrated with the diffusion equation to form the hybrid light transport model is utilized to describe
light propagation in the non-scattering region. After the finite element discretization, the hybrid light transport model is
converted into a minimization problem which fuses an l1 norm based regularization term to reveal the sparsity of
bioluminescent source distribution. The performance of the reconstruction algorithm is first demonstrated with a digital
mouse based simulation with the reconstruction error less than 1mm. An in situ gastric cancer-bearing nude mouse based
experiment is then conducted. The primary result reveals the ability of the novel BLT reconstruction algorithm in early
gastric cancer detection.
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.