Photodynamic therapy (PDT) has shown superiorities of noninvasiveness and high-efficiency in the treatment of early-stage skin cancer. Rapid and accurate determination of spatially distributed photon fluence in turbid tissue is essential for the dosimetry evaluation of PDT. It is generally known that photon fluence can be accurately obtained by Monte Carlo (MC) methods, while too much time would be consumed especially for complex light source mode or online real-time dosimetry evaluation of PDT. In this work, a method to rapidly calculate spatially distributed photon fluence in turbid medium is proposed implementing a classical perturbation and iteration theory on mesh Monte Carlo (MMC). In the proposed method, photon fluence can be obtained by superposing a perturbed and iterative solution caused by the defects in turbid medium to an unperturbed solution for the background medium and therefore repetitive MMC simulations can be avoided. To validate the method, a non-melanoma skin cancer model is carried out. The simulation results show the solution of photon fluence can be obtained quickly and correctly by perturbation algorithm.
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.
Two-layered slab is a rational simplified sample to the near-infrared functional brain imaging using diffuse optical
tomography (DOT).The quality of reconstructed images is substantially affected by the accuracy of the background optical
properties. In this paper, region step wise reconstruction method is proposed for reconstructing the background optical
properties of the two-layered slab sample with the known geometric information based on continuous wave (CW) DOT. The optical properties of the top and bottom layers are respectively reconstructed utilizing the different
source-detector-separation groups according to the depth of maximum brain sensitivity of the source-detector-separation. We demonstrate the feasibility of the proposed method and investigate the application range of the
source-detector-separation groups by the numerical simulations. The numerical simulation results indicate the proposed
method can effectively reconstruct the background optical properties of two-layered slab sample. The relative
reconstruction errors are less than 10% when the thickness of the top layer is approximate 10mm. The reconstruction of target caused by brain activation is investigated with the reconstructed optical properties as well. The quantitativeness ratio
of the ROI is about 80% which is higher than that of the conventional method. The spatial resolution of the reconstructions (R) with two targets is investigated, and it demonstrates R with the proposed method is better than that with the
conventional method as well.
In this paper, frequency-domain endoscopic diffuse optical tomography image reconstruction algorithm based on dual-modulation-frequency and dual-points source diffuse equation is investigated for the reconstruction of the optical parameters including the absorption and reducing scattering coefficients. The forward problem is solved by the finite element method based on the frequency domain diffuse equation (FD-DE) for dual-points source approximation and multi-modulation-frequency. In the image reconstruction, a multi-modulation-frequency Newton-Raphson algorithm is applied to obtain the solution. To further improve the image accuracy and quality, a method based on the region of interest (ROI) is applied on the above procedures. The simulation is performed in the tubular model to verify the validity of the algorithm. Results show that the FD-DE with dual-points source approximate is more accuracy at shorter source-detector separation. The reconstruction with dual-modulation-frequency improves the image accuracy and quality compared to the results with single-modulation-frequency and triple-modulation-frequency method. The peak optical coefficients in ROI (ROI_max) are almost equivalent to the true optical coefficients with the relative error less than 6.67%. The full width at half maximum (FWHM) achieves 82% of the true radius. The contrast-to-noise ratio (CNR) and image coefficient(IC) is 5.678 and 26.962, respectively. Additionally, the results with the method based on ROI show that the ROI_max is equivalent to the true value. The FWHM can improve by 88% of the true radius. The CNR and IC is improved over 7.782 and 45.335, respectively.
In the non-invasive brain imaging with near-infrared light, precise head model is of great significance to the forward model and the image reconstruction. To deal with the individual difference of human head tissues and the problem of the irregular curvature, in this paper, we extracted head structure with Mimics software from the MRI image of a volunteer. This scheme makes it possible to assign the optical parameters to every layer of the head tissues reasonably and solve the diffusion equation with the finite-element analysis. During the solution of the inverse problem, a semi-3D reconstruction algorithm is adopted to trade off the computation cost and accuracy between the full 3-D and the 2-D reconstructions. In this scheme, the changes in the optical properties of the inclusions are assumed either axially invariable or confined to the imaging plane, while the 3-D nature of the photon migration is still retained. This therefore leads to a 2-D inverse issue with the matched 3-D forward model. Simulation results show that comparing to the 3-D reconstruction algorithm, the Semi-3D reconstruction algorithm cut 27% the calculation time consumption.
To acquire the optical diffuse tomographic image of the cervix, a novel endoscopic rotary probe is designed and the
frequency domain measurement system is developed. The finite element method and Gauss-Newton method are
proposed to reconstruct the image of the phantom.
In the optical diffuse tomographic imaging of the cervix, an endoscopic probe is needed and the detection of light at
different separation to the irradiation spot is necessary. To simplify the system, only two optical fibers are adopted for
light irradiation and collection, respectively. Two small stepper motors are employed to control the rotation of the
incident fiber and the detection fiber, respectively. For one position of source fiber, the position of the detection fiber is
changed from -61.875° to -50.625° and 50.625° to 61.875° to the source fiber, respectively. Then, the position of the source fiber is changed to another preconcerted position, which deviates the precious source position in an angle of
11.25°, and the detection fiber rotates within the above angles. To acquire the efficient irradiation and collection of the
light, a gradient-index (GRIN) lens is connected at the head of the optical fiber. The other end of the GRIN lens is cut to
45°. With this design, light from optical fiber is reflected to the cervix wall, which is perpendicular to the optical fiber or
vice versa. Considering the cervical size, the external diameter of the endoscopic probe is made to 20mm.
A frequency domain (FD) near-infrared diffuse system is developed aiming at the detection of early cervical cancer,
which modulates the light intensity in radio frequency and measures the amplitude attenuation and the phase delay of the
diffused light using heterodyne detection.
Phantom experiment results demonstrate that the endoscopic rotary scan probe and the system perform well in the
endoscopic measurement.
To reduce the cost of near-infrared endoscopic image equipment and the reconstruction time, a measurement method
based on the effective detection area is proposed and the corresponding algorithm which simultaneously reconstructs the
absorption coefficient and the reduced scattering coefficient is developed. First, the effective detection area is
investigated with the Monte Carlo simulation. Secondly, the image reconstruction algorithm based on the effective
detection area is studied. The Jacobin matrix is built by combining the adjoint method with the modified Generalized
Pulse Spectrum Technique and calibrated by the maximum of its absolute value. The Generalized Minimal Residual
Krylov method is used to obtain the iterative update factor. Finally, the impact of the number of measured points in the
effective detection area on the reconstructed results is discussed, and the robustness of the algorithm to noise and
cross-talk are verified by the simulated test data. The results show that the reconstructed algorithm based on the effective
detection area has equivalent accuracy to the traditional ones. The fidelity of reconstructed absorption and reduced
scattering coefficients can be 80%, respectively. The scales and positions of the reconstructed lesions are both correspond
to the true and the reconstruction time is reduced by half. The optimal number of sources and detectors is 16 depending
on the scale of the simulation model. The detection using the effective detection area and the developed reconstruction
algorithm will promote the development of diffuse optical tomography which is applied to cervical and other tubular
organs.
This article aims at the optical property (absorption coefficient and scatter coefficient) reconstruction from the
frequency-domain (FD) near-infrared diffuse measurement on small tissues, such as a cervix, for which inverse Monte
Carlo (MC) simulation is the suitable choice. To achieve the fast and accurate reconstruction based on the inverse Monte
Carlo simulation, following techniques were adopted. First, in the forward calculation, a database, which include the
frequency-domain information calculated from MC simulation for a series of optical parameters of tissue, were
established with fast methods. Then, in the reconstruction procedure, Levenberg-Marquardt (L-M) optimization was
adopted and Multiple Polynomial Regression (MPR) method was used to rapidly get the FD information at any optical
properties by best fitting the curved surface formed by the above database. At Last, in the reconstruction, to eliminate the
influence of the initial guess of optical properties on the reconstruction accuracy, cluster analysis method was introduced
into L-M reconstruction algorithm to determine the region of the initial guess. The reconstruction algorithm was
demonstrated with simulation data. The results showed that it takes less than 0.5s to reconstruction one set of optical
properties. The average relative error from the reconstruction algorithm joined with cluster analysis is 10% lower than
that without cluster analysis.
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