Search

Small extracellular vesicles (sEVs) provide major promise for advances in cancer diagnostics, prognostics, and therapeutics, ascribed to their distinctive cargo reflective of pathophysiological status, active involvement in intercellular communication, as well as their ubiquity and stability in bodily fluids. As a result, the field of sEV research has expanded exponentially. Nevertheless, there is a lack of standardisation in methods for sEV isolation from cells grown in serum-containing media. The majority of researchers use serum-containing media for sEV harvest and employ ultracentrifugation as the primary isolation method. Ultracentrifugation is inefficient as it is devoid of the capacity to isolate high sEV yields without contamination of non-sEV materials or disruption of sEV integrity. We comprehensively evaluated a protocol using tangential flow filtration and size exclusion chromatography to isolate sEVs from a variety of human and murine cancer cell lines, including HeLa, MDA-MB-231, EO771 and B16F10. We directly compared the performance of traditional ultracentrifugation and tangential flow filtration methods, that had undergone further purification by size exclusion chromatography, in their capacity to separate sEVs, and rigorously characterised sEV properties using multiple quantification devices, protein analyses and both image and nano-flow cytometry. Ultracentrifugation and tangential flow filtration both enrich consistent sEV populations, with similar size distributions of particles ranging up to 200 nm. However, tangential flow filtration exceeds ultracentrifugation in isolating significantly higher yields of sEVs, making it more suitable for large-scale research applications. Our results demonstrate that tangential flow filtration is a reliable and robust sEV isolation approach that surpasses ultracentrifugation in yield, reproducibility, time, costs and scalability. These advantages allow for implementation in comprehensive research applications and downstream investigations.

With the rapid increase of on-site monitoring objects and technological development, the power on-site image monitoring data has increased geometrically. For security managers, it is necessary to efficiently and quickly identify valid data and conduct intelligent early warning. Therefore, this paper proposes an intelligent analysis method of power field surveillance video data based on convolutional neural network. Firstly, the original surveillance video material is extracted. Secondly, the video cloud storage platform is used for storage and data cleaning. At the same time, the hidden danger behaviors are classified and analyzed and marked. Finally, the proposed method is used for feature extraction, model training and field verification to realize intelligent early warning analysis of video big data. The field application effect shows that the method proposed in this paper can realize the functions of video image data feature extraction, model training, and improve the effect of image processing. Eventually, it can meet the needs of on-site video data intelligent analysis and has a certain promotion prospect.

Due to the complex site conditions of power infrastructure projects and the similar structural features of various danger sources, it is difficult to extract salient features suitable for classification. Although the neural networks with large numbers of available improved loss functions have good application effects in feature recognition, the single depth feature does not make full use of the complementarity between the multiple features of the field environment. In response to these problems, this paper proposes a method for classification and identification of danger sources at infrastructure construction sites based on neural network multi-layer feature information. It completes the image recognition of the infrastructure site by selecting the sparse self-encoding technology, extracts the multi-layer features in the neural network, and then sends the multi-layer features to the softmax classifier to solve the multi-classification problem of dangerous sources, and can extract more suitable based on the analysis of the characteristics of the danger sources on the infrastructure construction site. Through data analysis, the method illustrated in this paper effectively improves the identification rate of the danger sources and shows great significance to ensure the safety of infrastructure construction site.

With the development of energy Internet technology, the types and number of terminals in substations have shown an explosive growth trend, which puts forward higher requirements for image compression and image processing capabilities. Therefore, this paper proposes a method to improve the quality of power image transmission. Firstly, the eigenvalues and special vectors of the image are obtained, and then the wavelet transform method is used to encode the image, and finally the compressed image after decoding is obtained. Based on a typical field case, the comparison of experimental data under various algorithms is carried out. The results show that the improved method proposed in this paper has better image compression quality and higher peak signal-to-noise ratio, and improves the transmission quality of substation field monitoring images. It provides new technical ideas for the development of big data processing of electric power images.

To master the real-time security status of the infrastructure construction site, an intelligent monitoring system for the recognition of the danger sources at infrastructure construction site, which is based on the theory of depth learning, is proposed. The monitoring system mainly includes signal acquisition equipment, internal optical network, server control center and display terminal. The intelligent identification algorithm of the danger sources is the core of the entire system. The characteristics from the image signal are extracted by the sparse self-coding, which is used to train the neural network. Then, the convolution is proposed to reduce the dimensionality of the features. The experiments confirm that the identification algorithm based on deep learning illustrates high accuracy in hazard identification. In terms of feedback, the identification results will be transmitted to the display terminal, and the safety status of the entire infrastructure construction site can be fully controlled to ensure the safety of both the infrastructure site and the power system.

At present, massive amounts of image data have been generated at the power construction site. Due to the limitation of power communication transmission bandwidth, it is necessary to improve the low bit rate, high compression ratio, and anti-interference of the image, which is very necessary for on-site management personnel under the premise of ensuring efficient information transmission. Aiming at the above problems, this paper proposes an improved algorithm based on Set Partitioning in Hierarchical Trees (SPIHT). Firstly, the feature value of the image is extracted, and then the wavelet encoding is performed to obtain the compressed image. Compared with the traditional multi-level tree ensemble splitting algorithm, experimental data show that the image compressed by this algorithm has better visual effects and higher peak signal-to-noise ratio. Therefore, the method can effectively improve the transmission performance of the on-site image of the infrastructure construction, and ultimately improve the efficiency of the on-site inspection for violations.

In order to reveal the influence of gas pressure on the gas adsorption law of middle-rank coals, four groups of typical middle-rank coals in China were used as the research objects, using saturated, centrifugal, drying equipment and Low-field Nuclear Magnetic Resonance (LNMR) system to carry out coal samples. The pore structure characterization test and the isotherm adsorption test under different gas pressure were carried out. First, the coal sample's pore size distribution, pore roar distribution, porosity and permeability and other parameters were analyzed. Then, the gas adsorption isotherm process was quantitatively studied based on the established relaxation time (T2) spectrum area conversion model. Finally, the relationship between gas pressure and gas adsorption in coal reservoir was discussed. The experimental results show that the pore structure of middle-rank coal is mainly composed of small pores, and a small number of large pores are distributed. Middle-rank coal has low permeability and good gas storage capacity. Under the same gas pressure, with the increase of adsorption time, the gas adsorption amount gradually increased, and the gas adsorption increment gradually decreased. After 7 h, the adsorption equilibrium is reached. Under different gas pressure, the gas pressure has a proportional relationship with the initial gas adsorption speed, which conforms to the Langmuir adsorption theory with the amount of adsorbed gas, and has a quadratic function relationship with the amount of non-adsorbed gas. When the gas pressure is higher than 2.4 MPa, the time required to reach adsorption equilibrium is shortened to 5 h. Gas pressure has no obvious effect on the micropore structure of middle-rank coal, but it will promote the expansion of middle-large pore structure, and its expansion effect is enhanced with the increase of gas pressure.

To develop a multi-radionuclide imaging system with a flexible and compact structure that has a potential for breast and other applications, and to evaluate its performances under both positron emission tomography and single photon emission imaging conditions. The plane detector was composed of 5 × 6 blocks with an effective detection area of 168.6 mm × 202.4 mm. Each block consisted of a 16 × 16 LYSO array. The pixel size is 1.9 mm × 1.9 mm × 15 mm. An 8 × 8 silicon photomultiplier (SiPM) array with SensL’s C-30035 sensors was coupled to the LYSO array, separated by a 1.5-mm-thick glass. To minimize the influence of temperature on the detector, the active part of the front-end electronics was kept away from SiPMs. Self-designed data acquisition system and reconstruction software were utilized to evaluate the performances of the whole system. All the blocks had excellent pixels identification. An average energy resolution of 11.39% for 511 keV and 21.37% for 140 keV was obtained. In the PET mode, the best spatial resolution was better than 2 mm and the system sensitivity reached up to 11.05% at 60 mm distance. In the single photon emission imaging mode, a spatial resolution better than 3 mm was obtained. The results indicated that the system has a good overall performance and can be used in breast imaging and other general PET applications. It also has the potential to be used for single photon emission imaging. In pursuit of a better spatial resolution of cross-plane, PSF and DOI technology will be developed in the next work. For specific applications, further improvement of the detector system such as performance evaluation with phantoms will be carried out.

The Eplus-260 primate PET is an animal PET imaging system developed by the Institute of High Energy Physics, Chinese Academy of Sciences, which is designed to image non-human primates, especially the brain of large non-human primates. The system consists of 48 block detectors arranged in two 24-sided rings with a ring diameter of 263 mm and an axial extent of 64 mm. Each block detector is composed of a 16 × 16 cerium-doped lutetium-yttrium orthosilicate crystal array with a pixel size of 1.9 × 1.9 × 10 mm3. This article presents a performance evaluation of the PET scanner according to the National Electrical Manufacturers Association NU-4 2008 standards. All measurements were made for an energy window of 360-660 keV and a coincidence timing window of 2 ns. In terms of the FWHM, the FBP reconstructed spatial resolution results in all three directions at the radial position of 5 mm were better than or approached to 2 mm, and remained below 3.0 mm within the central 5 cm diameter of the FOV. The peak absolute sensitivity of the scanner was measured 1.80%. For a monkey-sized phantom, the scatter fraction was 34.2% and the peak noise equivalent count rate (NECR) was 26.5 kcps at 64.3 kBq/cc. The overall imaging capabilities of the scanner were also assessed using in vivo imaging study of a rhesus macaque. The performance measurements demonstrate that the Eplus-260 primate PET scanner has the potential ability to obtain good quality and high-contrast images for non-human primates, especially the brain of large non-human primates and could be considered as one technologically advanced dedicated non-human primate PET scanner available today.

This paper presents a coded aperture method to remotely estimate the radioactivity of a source. The activity is estimated from the detected counts and the estimated source location, which is extracted by factoring the effect of aperture magnification. A 6mm thick tungsten-copper alloy coded aperture mask is used to modulate the incoming gamma-rays. The location of point and line sources in all three dimensions was estimated with an accuracy of less than 10% when the source-camera distance was about 4 m. The estimated activities were 17.6% smaller and 50.4% larger than the actual activities for the point and line sources, respectively.

A new polygon positron emission mammography imaging system (PEMi) was developed in 2009 by the Institute of High Energy Physics, Chinese Academy of Sciences. PEMi is constructed in a polygon structure with lutetium yttrium orthosilicate crystal arrays mounted on a position-sensitive photomultiplier. The system consists of 64 blocks and each block is arranged in $16 \times 16$ crystal arrays with a pixel size of $1.9~\times 1.9~ \times 15$ mm. The diameter of the detector ring is 166 mm, and the axial length is 128 mm. The transaxial field of view of PEMi is 110 mm. The goal of the initial study was to test PEMi’s performance and the clinical imaging ability with a small group of selected subjects. The detectors have a measured intrinsic spatial resolution averaging 1.67 mm. The axial and tangential resolution remained under 2.5-mm full width at half maximum within the central 5-cm diameter of the field of view. The hot rods with a diameter of 1.7 mm can be clearly identified, and the structure of the region containing 1.35-mm diameter rods can also be observed. Using a 6-ns coincidence timing window and a ${\hbox {360}} \sim {\hbox {660}}$ -keV energy window, the peak sensitivity of the tomograph is 6.88%. The noise-equivalent count rate peak is 110 $\thinspace$ 766 cps for a breast-like cylindrical phantom of 100 mm in diameter at an activity concentration of $0.03~\hbox{MBq}/{\rm cc}$ . The recovery coefficients ranged from 0.21 to 0.85 for rods between 1 mm and 5 mm in the image-quality phantom. The reconstructed image resolution achieved an improvement compared with whole-body positron emission tomography (PET), which might reduce the lower threshold on detectable lesion size. Example patient images demonstrate that PEMi is clinically feasible. And more detailed structure information was obtained with PEMi than with the whole-body PET imaging.

Purpose Positron emission tomography (PET) is a non-invasive imaging tool for the evaluation of brain function and neuronal activity in normal and diseased conditions with high sensitivity. The macaque monkey serves as a valuable model system in the field of translational medicine, for its phylogenetic proximity to man. To translation of non-human primate neuro-PET studies, an effective and objective data analysis platform for neuro-PET studies is needed. Materials and methods A set of stereotaxic templates of macaque brain, namely the Institute of High Energy Physics & Jinan University Macaque Template (HJT), was constructed by iteratively registration and averaging, based on 30 healthy rhesus monkeys. A brain atlas image was created in HJT space by combining sub-anatomical regions and defining new 88 bilateral functional regions, in which a unique integer was assigned for each sub-anatomical region. Results The HJT comprised a structural MRI T1 weighted image (T1WI) template image, a functional FDG-PET template image, intracranial tissue segmentations accompanied with a digital macaque brain atlas image. It is compatible with various commercially available software tools, such as SPM and PMOD. Data analysis was performed on a stroke model compared with a group of healthy controls to demonstrate the usage of HJT. Conclusion We have constructed a stereotaxic template set of macaque brain named HJT, which standardizes macaque neuroimaging data analysis, supports novel radiotracer development and facilitates translational neuro-disorders research.

X-ray Computed Tomography (CT) method is an integral part of hydraulic-fracture imaging, but its application to micro-fractures in cores is limited. This paper documents the visualization of fractured cores via an accessorial PET-CT approach to improve both spatial resolution and image contrast. PET-CT approach combines X-ray Computed Tomography (CT) and positron emission tomography (PET) method. CT technique provides information of core structure and accurate location of fractures based on density variations. PET is a nuclear imaging technique through inducing radionuclide into fractures, offering the potential to overcome CT limitations by providing information of micro-fractures. Combined PET-CT approach has been demonstrated as a technical advancement for imaging fractured cores better than simply CT or PET method. Comprehensive information of core structure, micro-fractures and connected fractures could be provided by PET-CT method. The applicability of each visualization technique was evaluated, the favorable implementation of combined PET-CT for laboratory core analysis was discussed.

Respiratory motion is a major factor that affects the quality of PET images of the thoracic area. The diaphragm moves about 15–20 mm due to respiratory motion, which substantially degrades the effective spatial resolution of PET. In this paper, a gated acquisition method is used to correct the motion effects. In this method, an improved demons algorithm is proposed to align the gated images. The experimental results show that the quality of PET images is significantly improved when using our improved method and the proposed method has a faster convergence rate than the original demons algorithm.

Geometric calibration is critical to the accurate SPECT reconstruction. In this paper, a geometric calibration method was developed for a dedicated breast SPECT system with a tilted parallel beam (TPB) orbit. The acquisition geometry of the breast SPECT was firstly characterized. And then its projection model was established based on the acquisition geometry. Finally, the calibration results were obtained using a nonlinear optimization method that fitted the measured projections to the model. Monte Carlo data of the breast SPECT were used to verify the calibration method. Simulation results showed that the geometric parameters with reasonable accuracy could be obtained by the proposed method.

Positional single photon incidence response (P-SPIR) theory is researched in this paper to generate more accurate PSF-contained system matrix simply and quickly. The method has been proved highly effective to improve the spatial resolution by applying to the Eplus-260 primate PET designed by the Institute of High Energy Physics of the Chinese Academy of Sciences(IHEP). Simultaneously, to meet the clinical needs, GPU acceleration is put to use. Basically, P-SPIR theory takes both incidence angle and incidence position by crystal subdivision instead of only incidence angle into consideration based on Geant4 Application for Emission Tomography (GATE). The simulation conforms to the actual response distribution and can be completed rapidly within less than 1s. Furthermore,two-block penetration and normalization of the response probability are raised to fit the reality. With PSF obtained, the homogenization model is analyzed to calculate the spread distribution of bins within a few minutes for system matrix generation. As a reult, The images reconstructed indicate that the P-SPIR method can effectively inhibit the depth of interaction (DOI) effect especially in the field close to the edge of the field of view (FOV). What is more, the method can be promoted to any other PET and the list-mode organization structure high-speedily and efficiently, which substantially reduces the computing cost and ensures the accuracy of system matrix for PET reconstruction., Comment: 6 pages,12 figures

A PET module that comprises a pair of compact, high-resolution and large-area detectors based on silicon photomultipliers (SiPM) was developed and evaluated. The detector's effective area was 24 mm x 24 mm. LYSO crystals measuring 1.9 mm x 1.9 mm x 10 mm and charge division circuit were employed to obtain high spatial resolution with relatively concise Front-end electronics (FEE). Initial results showed the detector to be compatible with 1.5 T magnetic fields. The system's intrinsic FWHM spatial resolution is 1.50 mm. The average energy resolution is 18.5% and the coincidence timing resolution is 2.6 ns. (C) 2011 Elsevier B.V. All rights reserved.

In fully three-dimensional (3D) positron emission tomography (PET) imaging, the scatter fraction (SF) is about 40%-60%, which may degrade the imaging quality severely. Scatter correction is important for high quality image reconstruction. Model-based scatter correction has been proved to be accurate and available in clinical PET. However, it does not correct the scatter from out of the field of view (OFOV) and multiple scatters. In this study, we demonstrate the radial and axial distribution of scatters from OFOV when the source is located in different radial positions. In order to apply the above conclusions to different PET systems, we characterize the scatters from OFOV as a function of the ratio of the scanner diameter to the length of the axial field of view (AFOV) by modeling several typical whole-body and micro PET systems. The proportions of true events (S0–0), single scatter of one photon (S1–0), single scatter of both photons (S1–1), double scatter of one photon (S2–0) and multiple scatter (Sm) are also calculated and compared. Here the 3D-PET Monte Carlo simulations are performed with the Geant4 Application for Tomography Emission (GATE). In summary, the scatters from OFOV tend to be recorded on the lines of response (LOR) far away from the source. They have a much more serious impact on whole-body PET than micro PET depending on the ratio of scanner diameter to the length of AFOV. In whole-body PET, twice scatters including single scatter of both photons (S1–1) and double scatter of one photon (S2–0) add up to about 12% so that twice scatter correction must be taken into account to acquire a high quality reconstruction image.

Structural brain abnormalities have been widely reported in major depressive disorder (MDD). However, many previous results cannot exclude the interferences of medication or multiple recurrent episodes. In this study, we examined structural brain abnormalities by comparing 68 drug-naïve first-episode adult-onset MDD and 68 healthy controls (HCs). Structural magnetic resonance imaging (MRI) and voxel-based morphometry (VBM) methods were used. The mean values of grey matter volume/white matter volume (GMV/WMV) were calculated, then the differences between MDD and HCs were analyzed, and the associations of the differences with clinical characteristics of depression were discussed. The whole brain GMV/WMV did not differ between MDD patients and HCs; however, the regional GMV of the right pre-supplementary motor area (pre-SMA) was smaller in MDD patients. The GMV of both hippocampi was positively correlated with symptom severity and lower in patients with long durations. These results indicate the GMV reduction of the pre-SMA at an early stage of depression, whereas the GMV of the hippocampus is associated with depressive characteristics. Moreover, the whole brain GMV/WMV was negatively related to the duration of depression, supporting that volume loss could become progressive during the development of disease. These results may suggest the importance of identifying and intervening depression at an early stage, especially the first year after onset, to prevent volume loss in the brain.

A method has been developed to establish the crystal position look-up table for positron emission tomography with block detectors. It is based on the principle that the counts in crystal position histogram obey the Gaussian mixture model (GMM). This method has taken full consideration of the characteristics of the GMM and the detector itself. The experimental results have proved that it is simple, reliable, and universal.

PET/MR is a new multi-modality imaging system which provide both structural and functional information with good soft tissue imaging ability and no ionizing radiation. In recent years, PET/MR is under major progress because of the development of silicon photomultipliers (SiPM). The goal of this study is to develop a MRI compatible PET insert based on SiPM and LYSO scintillator. The PET system was constituted by the detector ring, electronics and software. The detector ring consists of 16 detector module. The inner diameter of the ring was 151 mm, the external diameter was 216 mm, which was big enough for small animal research, e.g. rat, rabbit and tupaia. The sensor of each module was 2*2 SensL SPMArraySL, coupled with an array of 14 x 14 LYSO crystals, each crystal measuring 2 mm x 2 mm 10 mm. The detector was encapsulated in a copper box for light and magnetic shielding. Resister charge multiplexing circuit was used in the front end electronics. Each detector output 8X and 8Y position signals. One summed timing signal was extracted from the common cathode of all 64 channels. All these signals were transmitted to digital electronic board by a 3 m long coaxial cable from inside of the MR to the outside. Each digital electronic board handled 8 detector modules based on FPGA to obtain the timing, position and energy information of a single event. And then these single events were sent to the coincidence processing board to produce coincidence packets which are prepared for further processing. A 0.2mCi 68Ge line source was used to do the preliminary imaging test. The image was reconstructed by 3D-OSEM algorithm. The initial result proved the system to be feasible as a PET. FDG phantom imaging and simultaneous PET/MR imaging are in progress.

An instrument used for measuring multiple scintillators' light output and energy resolution was developed. The instrument consisted of a light sensor array which was composed of 64 discrete SiPMs (Silicon Photomultipliers), a corresponding individual channel readout electronics system, and a data processing algorithm. A Teflon grid and a large interval between adjacent SiPMs were employed to eliminate the optical cross talk among scintillators. The scintillators' light output was obtained by comparing with a reference sample with known light output. Given the SiPM temperature dependency and the difference among each SiPM, a temperature offset correction algorithm and a non-uniformity correction algorithm were added to the instrument. A positioning algorithm, based on nine points, was designed to evaluate the performance of a scintillator array. Tests were performed to evaluate the instrument's performance. The uniformity of 64 channels for light output measurement was better than 98%, the stability was better than 98% when temperature varied from 15 °C to 40 °C, and the nonlinearity under 511 keV was better than 2%. This instrument was capable of selecting scintillators and evaluating the packaging technology of scintillator arrays with high efficiency and accuracy.

A depth discrimination method is devised based on a multirow linear array detector for push-broom Compton scatter imaging. Two or more rows of detector modules are placed at different positions towards a sample. An improved parallel-hole collimator is fixed in front of the modules to restrict their fields of view. The depth information could be indicated by comparing the signal differences. In addition, an available detector and several related simulations using GEANT4 are given to support the method well.

Positron emission tomography (PET) is a radiotracer imaging technique, which permits the in vivo quantitative measurement of biological processes non-invasively. The science and technology behind PET involves radiotracing and tomography. In the process of PET imaging, the compound labeled with a positron-emitting isotope is injected into body. The isotope-labeled compound joins a biological process in the body. Meanwhile, the positron-emitting isotope decays and emits a positron. The positron will lose energy through interactions with the surrounding tissue and then annihilate it with an electron. The annihilated positron and electron will transform into two gamma photons with an energy of 511 keV, which will travel apart in opposite directions. PET detects these gamma photon pairs in the coincidence mode and reconstructs them in the tomographic image which reflects the original distribution of the radio-isotope in the body. From the distribution of the radio-isotope, we can infer the distribution of the radio-isotope labeled compound in the body and obtain the related biological information in the body.

Positron Emission Mammography imaging system (PEMi) is a nuclear medicine diagnosis method dedicated for breast imaging. It provides a better resolution in detection of millimeter-sized breast tumors than whole-body PET. To address the requirement of semi-quantitative analysis with the radiotracer concentration map of the breast, a new attenuation correction method based on three-dimensional seeded region growing image segmentation (3DSRG-AC) solution was developed. The method gives a 3D connected region as the segmentation result instead of image slices. The continuously segmentation property makes this new method free of activity variation of breast tissues. Threshold value chosen is the key point for the segmentation process. The first valley of the grey level histogram of the reconstruction image is set as the lower threshold, which works fine in clinical application. Results show that attenuation correction for PEMi improves the image quality and the quantitative accuracy of radioactivity distribution determination. Attenuation correction also improves the probabilities to detect small and early breast tumors.

Purpose To automatically extract regions of interest (ROIs) and simultaneously preserve the anatomical characteristics of each individual, we developed a new atlas-based method utilizing a pair of coregistered brain template and digital atlas. Materials and Methods Unlike the previous atlas-based method, this method treats each individual as the target image, and the template and atlas are each transformed to register with the individual. To evaluate the accuracy of this method we implemented it in extracting the hippocampus from two groups of T2-weighted structural images with different spatial resolutions and a group of T2*-weighted functional images. Furthermore, the results were compared against a manually segmented hippocampus and an atlas-derived hippocampus. Results Jaccard similarity (JS) reached 84.7%–90.5%, and relative error in volume (RV) was 4.8%–12.7%. The consistency observed between the results of the proposed method and manual drawing was therefore considerable. Conclusion We developed a new atlas-based method for ROI extraction that can automatically extract ROI and simultaneously preserve each individual's unique anatomical characteristics. J. Magn. Reson. Imaging 2010;32:830–835. © 2010 Wiley-Liss, Inc.

Objective.The central nervous system (CNS) is often affected by systemic lupus erythematosus (SLE), but assessment of CNS outcomes using noninvasive cerebral structural measures remains in its infancy. Magnetic resonance imaging (MRI) with expert visual interpretation is critical to diagnosis, but does not permit quantitative measurements. Our pilot study investigated whether quantitative brain volumetric analyses could be used to detect white-matter (WM) abnormalities and responses to treatment in SLE (ClinicalTrials.gov: NCT00703742).Methods.Forty-two pairs of SLE patients and healthy controls underwent high-resolution 3-dimensional structural MRI scans. Combining voxel-based morphometry and region of interest analyses, subtle WM volume abnormalities in whole brains from SLE patients were identified, and regional WM volume was calculated. Associations between WM volume and symptom severity, as well as the effects of immunosuppressive therapy, were then investigated.Results.The WM volume of the SLE group was significantly decreased in the bilateral posterior and anterior crus of the internal capsule (PIC and AIC, respectively), the subgyral right frontal lobe, and left temporal lobe (p < 0.001). Regional WM volume (left PIC and right AIC) was correlated with SLEDAI scores. The WM volume of patients treated with immunosuppressive therapy was greater than that of patients who were never treated with immunosuppressive therapy.Conclusion.Quantitative brain volumetric analyses detect brain injuries in WM for SLE that are not obvious by conventional MRI, and may be adequately sensitive and quantitative to measure the effect of therapeutic interventions in preventing brain injury and outcomes in SLE.

A point spread function (PSF) for the blurring component in positron emission tomography (PET) is studied. The PSF matrix is derived from the single photon incidence response function. A statistical iterative reconstruction (IR) method based on the system matrix containing the PSF is developed. More specifically, the gamma photon incidence upon a crystal array is simulated by Monte Carlo (MC) simulation, and then the single photon incidence response functions are calculated. Subsequently, the single photon incidence response functions are used to compute the coincidence blurring factor according to the physical process of PET coincidence detection. Through weighting the ordinary system matrix response by the coincidence blurring factors, the IR system matrix containing the PSF is finally established. By using this system matrix, the image is reconstructed by an ordered subset expectation maximization (OSEM) algorithm. The experimental results show that the proposed system matrix can substantially improve the image radial resolution, contrast, and noise property. Furthermore, the simulated single gamma-ray incidence response function depends only on the crystal configuration, so the method could be extended to any PET scanner with the same detector crystal configuration.

Accurate attenuation correction is required in dedicated breast PET imaging systems for image artifact removal and quantitative studies. In this study, a method using only emission data based on consistency conditions is proposed for attenuation correction in breast PET imaging systems. The consistency conditions are exploited to evaluate the accuracy of the estimated attenuation distribution and find the appropriate parameters that yield the most consistent attenuation distribution with the measured emission data. We have proved the validity of the method with experimental investigations and single-patient studies using a dedicated breast PET. The results show that the method is capable of accurately estimating the attenuation distribution of a uniform attenuator from the experimental data with various relatively low activities. The results also show that in single-patient studies, the method is robust for the irregular boundary of breast tissue and provides a distinct improvement in image quality.

A linear relationship between the MTF degradation and the wavefront variance has been developed for small wavefront error perturbation. A sensitivity coefficient can then be defined to aid both the design and error budgeting process. For error budgeting, this coefficient is applied to predict change in performance of a nearly diffraction-limited optical imaging system due to manufacture and assembly errors. This leads to a fast and accurate way to create an error budget and explore ideal distribution of individual terms. A CODE V verification model will be presented to show the range of wavefront error that this MTF linear degradation model applied. Further, an example of an error budget spread sheet will illustrate how this model is used to determine the best distribution of error allocations.

Using the linear MTF degradation model, a convenient tool has been developed that enables a design to be toleranced for MTF performance as a function of wavefront error perturbation. By integrating this computation model with conventional designing tools, end-of-life MTF performance can be quickly and accurately predicted. The HRMSI optical performance requirements will be presented and examples discussed that show how the MTF degradation model was used for optimization and design trades.

We present a read/write/erase all-optical memory that fully utilizes local photoinduced birefringence in a synthetic dye-polymer. Memory reading is based on an optical vector-matrix inner product. The intrinsic chromatic characteristics of the proposed memory storage medium is the key to a novel form of nonmechanical parallel memory storage. Green light at 514.5 nm writes a spatial pattern and read light at 632 nm reads it. The dynamic memory material is an improved polyvinyl-alcohol (PVA) polymer film doped with Azo dye. Unique to this material is low optical power, no significant memory degradation after the recording process, and local information erasure or rewrite at any time. The material operates at room temperature with no sealing requirements.

The search for proper materials for all-optical data storage has become a critical issue in the development of a practical system that would provide high capacity and high accessing speed operation. In order to characterize a material to determine whether it is a candidate for optical information storage, three basic properties that deal with the material's light/matter interaction response (its ability to retain information, the driving power requirements for light/matter interaction, and the material's response speed) must be considered as a whole, balancing one property against another. Recent developments have shown certain materials that utilize photochromic two-photon absorption phenomena[1] and time-domain frequency selective storage (TDFSS) methods[2,3] are superb in performing three-dimensional, ultra-high capacity, and ultra-high speed data storage. Nevertheless, the two-photon materials need always be driven by a very powerful laser source due to the inherent low absorption cross-section of the two-photon process and the fact that TDFSS is constrained by the required cryogenic cooling operation. In this paper, we present a novel erasable and nonvolatile optical memory based on the application of high-efficiency polymeric material with reversible photoinduced birefringence. All the disadvantages of the two-photon absorption and TDFSS mechanisms are invisible to the synthetic polymer because its storage does not rely on quantum mechanic state excitation but on fast photoinduced electric dipole rotation.