Positron emission tomography (PET) has been used forin vivotreatment verification, mainly for range verification, in proton therapy. Evaluating the direct dose from PET measurements remains challenging;however, it is ...
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Positron emission tomography (PET) has been used forin vivotreatment verification, mainly for range verification, in proton therapy. Evaluating the direct dose from PET measurements remains challenging;however, it is highly desirable from a clinical perspective. In this study, a method for estimating the dose distribution from the positron emitter distributions was developed using the maximum likelihood expectation maximization algorithm. The 1D spatial relationship between positron emitter distributions and a dose distribution in an inhomogeneous target was inputted into the system matrix based on a filter framework. In contrast, spatial resolution of the PET system and total variation regularization (as prior knowledge for dose distribution) were considered in the 3D image-space. The dose estimation was demonstrated using Monte Carlo simulated PET activity distributions with substantial noise in a head and neck phantom. This mimicked the single field irradiation of the spread-out Bragg peak beams at clinical dose levels. Besides the simple implementation of the algorithm, this strategy achieved a high-speed calculation (30 s for a 3D dose estimation) and accurate dose and range estimations (less than 10% and 2 mm errors at 1-sigma values, respectively). The proposed method could be key for using PET forin vivodose monitoring.
Positron emission tomography (PET) has been extensively studied and clinically investigated for dose verification in proton therapy. However, the production distributions of positron emitters are not proportional to t...
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Positron emission tomography (PET) has been extensively studied and clinically investigated for dose verification in proton therapy. However, the production distributions of positron emitters are not proportional to the dose distribution. Thus, direct dose evaluation is limited when using the conventional PET-based approach. We propose a method for estimating the dose distribution from the positron emitter distributions using the maximum likelihood (ml) expectation maximization (em) algorithm combined with filtering. In experiments to verify the effectiveness of the proposed method, mono-energetic and spread-out Bragg-peak proton beams were delivered by a synchrotron, and a water target was irradiated at clinical dose levels. Planar PET measurements were performed during beam pauses and after irradiation over a total period of 200 s. In addition, we conducted a Monte Carlo simulation to obtain the required filter functions and analyze the influence of the number of algorithm iterations on estimation. We successfully estimated the 2D dose distributions even under statistical noise in the PET images. The accuracy of the 2D dose estimation was about 10% for both beams at the 1-sigma values of relative error. This value is comparable to the deviations in the measured PET activity distributions. For the laterally integrated profile along the beam direction, a low error within 5% was obtained per irradiation value. Moreover, the difference of estimated proton ranges was within 1 mm, and 2D estimation from the PET images was completed in 21 ms. Hence, the proposed algorithm may be applied to real-time dose monitoring. Although this is the first attempt to use the ml-em algorithm for dose estimation, the proposed method showed high accuracy and speed in the estimation of proton dose distribution from PET data. The proposed method is thus a step forward to exploit the full potential of PET for in vivo dose verification.
The iterative maximum-likelihood expectation-maximization (ml-em) algorithm is an excellent algorithm for image reconstruction and usually provides better images than the filtered backprojection (FBP) algorithm. Howev...
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The iterative maximum-likelihood expectation-maximization (ml-em) algorithm is an excellent algorithm for image reconstruction and usually provides better images than the filtered backprojection (FBP) algorithm. However, a windowed FBP algorithm can outperform the ml-em in certain occasions, when the least-squared difference from the true image, that is, the least-squared error (LSE), is used as the comparison criterion. Computer simulations were carried out for the two algorithms. For a given data set the best reconstruction (compared to the true image) from each algorithm was first obtained, and the two reconstructions are compared. The stopping iteration number of the ml-em algorithm and the parameters of the windowed FBP algorithm were determined, so that they produced an image that was closest to the true image. However, to use the LSE criterion to compare algorithms, one must know the true image. How to select the optimal parameters when the true image is unknown is a practical open problem. For noisy Poisson projections, computer simulation results indicate that the ml-em images are better than the regular FBP images, and the windowed FBP algorithm images are better than the ml-em images. For the noiseless projections, the FBP algorithms outperform the ml-em algorithm. The computer simulations reveal that the windowed FBP algorithm can provide a reconstruction that is closer to the true image than the ml-em algorithm. (C) 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 114120, 2012
We develop a method to diagnose two-dimensional distribution of positron-emitting radioactivity in a rotating object through gamma-ray coincidence measurements with two detectors. The principle of this method is same ...
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We develop a method to diagnose two-dimensional distribution of positron-emitting radioactivity in a rotating object through gamma-ray coincidence measurements with two detectors. The principle of this method is same as PET but the measurement system is much simpler. We have constructed a prototype and performed tests with point-like and plate-shaped radioactive sources. The image reconstruction with ml-em algorithm reproduced the distribution. It can be useful for radiotracer measurements of slow transport processes of materials in a closed system and can find applications in mechanical engineering. (C) 2015 Elsevier B.V. All rights reserved.
We proposed a new concept of TOF-PET (Time-of-Flight Positron emission Tomography) using Cherenkov radiation. Basic experiments revealed a timing resolution of 170 ps, but the detection efficiency was less than those ...
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We proposed a new concept of TOF-PET (Time-of-Flight Positron emission Tomography) using Cherenkov radiation. Basic experiments revealed a timing resolution of 170 ps, but the detection efficiency was less than those of the conventional BaF2 scintillators. Through simulation studies, we confirmed that the spatial resolution and the S/N ratio of the images reconstructed with TOF information were 1.5 and 3 times better, respectively, than they were without TOF information, when we adopted the FP (Forward Projection) method combined with the ml-em (Maximum Likelihood Expectation Maximization) algorithm as an image reconstruction algorithm. Consequently, we concluded that TOF-PET using Cherenkov radiation is a promising candidate for next-generation PET. We concluded that PWO (PbWO4) is the best Cherenkov radiator from the viewpoint of detection efficiency. Additionally, we found that the Monte Carlo algorithm was able to generate images having error bars and thus to make quantitative diagnoses possible.
Recently new technologies for detecting biomolecules have been developed and are opening a new era of medical imaging. Chemiluminescence and fluorescence are emerging as promising tools for these tasks. These molecule...
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ISBN:
(纸本)081944006X
Recently new technologies for detecting biomolecules have been developed and are opening a new era of medical imaging. Chemiluminescence and fluorescence are emerging as promising tools for these tasks. These molecules emit optical photons that can be observed outside the body. Unfortunately, they are heavily scattered and absorbed in biological tissue. This is an obstacle for determining a way of mapping an original source distribution. In order to overcome this obstacle, we suggest a new concept, Optical emission Computed Tomography(OpECT) and test its feasibility with computer simulation.
We have studied three-dimensional reconstruction methods to estimate the cell volume of astroglial cells in primary culture. The studies are based on fluorescence imaging and optical sectioning. An automated image-acq...
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ISBN:
(纸本)0819430757
We have studied three-dimensional reconstruction methods to estimate the cell volume of astroglial cells in primary culture. The studies are based on fluorescence imaging and optical sectioning. An automated image-acquisition system was developed to collect two-dimensional microscopic images. Images were reconstructed by the Linear Maximum a Posteriori method and the non-linear Maximum Likelihood Expectation Maximization (ml-em) method. In addition, because of the high computational demand of the ml-em algorithm, we have developed a fast variant of this method. 1) Advanced image analysis techniques were applied for accurate and automated cell volume determination. 2) The sensitivity and accuracy of the reconstruction methods were evaluated by using fluorescent micro-beads with known diameter. The algorithms were applied to fura-2-labeled astroglial cells in primary culture exposed to hypo- or hyper-osmotic stress. The results showed that the ml-em reconstructed images are adequate for the determination of volume changes in cells or parts thereof.
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