Journal of X-Ray Science and Technology - Volume 26, issue 6
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Journal of X-Ray Science and Technology is an international journal designed for the diverse community (biomedical, industrial and academic) of users and developers of novel x-ray imaging techniques. The purpose of the journal is to provide clear and full coverage of new developments and applications in the field.
Areas such as x-ray microlithography, x-ray astronomy and medical x-ray imaging as well as new technologies arising from fields traditionally considered unrelated to x rays (semiconductor processing, accelerator technology, ionizing and non-ionizing medical diagnostic and therapeutic modalities, etc.) present opportunities for research that can meet new challenges as they arise.
Abstract: Soft X-ray spectromicroscopy was applied to study the distribution of DNA and RNA in a mammalian cell at the spatial resolution of 400 nm. The relative distribution of DNA and RNA was examined by the SVD (singular value decomposition) method in aXis2000 program using combined full spectra of DNA and RNA at the absorption edge regions of carbon, nitrogen and oxygen. The absorption of nucleic acid was evaluated using 1s-π * transitions in the NEXAFS spectra at the nitrogen K absorption edge and distributed to DNA and RNA according to the relative level obtained above. The present results revealed the usefulness…of the SVD method to discriminate closely related molecules such as DNA and RNA.
Keywords: STXM, DNA and RNA mapping, quantitative study, cultured mammalian cell
Abstract: BACKGROUND: Low-quality medical images may influence the accuracy of the machine learning process. OBJECTIVE: This study was undertaken to compare accuracy of medical image classification among machine learning methods, as classification is a basic aspect of clinical image inspection. METHODS: Three types of machine learning methods were used, which include Support Vector Machine (SVM), Artificial Neural Network (ANN), and Convolution Neural Network (CNN). To investigate changes in accuracy related to image quality, we constructed a single dataset using two different file formats of DICOM (Digital Imaging and Communications in Medicine) and JPEG (Joint Photographic Experts Group).…RESULTS: The JPEG format contains less color information and data capacity than the DICOM format. CNN classification was accurate for both datasets, whereas SVM and ANN accuracy decreased with the loss of data from DICOM to JPEG formats. CONCLUSIONS: CNN is more accurate than conventional machine learning methods that utilize the manual feature extraction.
Abstract: OBJECTIVE: To perform quantitative measurement based on the standardized uptake value (SUV) of Tc-99m methylene diphosphonate (MDP) in the normal pelvis using a single-photon emission tomography (SPECT)/computed tomography (CT) scanner. MATERIAL AND METHODS: This retrospective study was performed on 31 patients with cancer undergoing bone SPECT/CT scans with 99m Tc-MDP. SUVmax and SUVmean of the normal pelvis were calculated based on the body weight. SUVmax and SUVmean of the bilateral anterior superior iliac spine, posterior superior iliac spine, facies auricularis ossis ilii, ischial tuberosity, and sacrum were also calculated. Furthermore, the correlation of SUVmax…and SUVmean of all parts of pelvis with weight, height, and CT was assessed. RESULTS: The data for 31 patients (20 women and 11 men; mean age 58.97±9.12 years; age range 37–87 years) were collected. SUVmax and SUVmean changed from 1.65±0.40 to 3.8±1.0 and from 1.15±0.25 to 2.07±0.58, respectively. The coefficient of variation of SUVmax and SUVmean ranged from 0.22 to 0.31. SUVmax and SUVmean had no statistically significant difference between men and women. SUVmax and SUVmean also showed no significant correlation with weight and height. However, part of SUVmax and SUVmean showed a significant correlation with CT. In addition, SUVmax and SUVmean of the bilateral ischial tuberosity showed a significant correlation with CT values. CONCLUSIONS: Determination of the SUV value of the normal pelvis with 99m Tc-MDP SPECT/CT is feasible and highly reproducible. SUVs of the normal pelvis showed a relatively large variability. As a quantitative imaging biomarker, SUVs might require standardization with adequate reference data for the participant to minimize variability.
Abstract: BACKGROUND: The Accreditation Council for Lung Cancer CT Screening of Japan established guidelines for the certification of Radiological Technologists in 2009. OBJECTIVE: To analyze the trends in examination pass rates of the Radiological Technologists and discuss the reasons. METHODS: The cohort comprised 1593 Radiological Technologists (as examinees) based on 10-year of data (with a total of 17 examination runs). First, the examinees’ written test results were analyzed. Second, an abnormal finding detection test was conducted using >100 client PCs connected to a dedicated server containing low-dose lung cancer CT screening images of 60 cases. The passing…scores were correct answer rate >60% and sensitivity (TP) of >90%, respectively. RESULTS: Overall, 1243 examinees passed with an overall rate of 78%. The average pass rate for the written test was 91%, whereas that for the abnormal findings detection test was 85%. There was a moderate correlation between the test pass rate and average years of clinical experience of the examinees for the abnormal findings detection test (R = 0.558), whereas no such correlation existed for the written test (R = 0.105). CONCLUSIONS: In order for accredited Radiological Technologists to serve as primary screeners of low-dose computed tomography, it is important to revise the educational system according to current standard practices.
Keywords: Lung, radiological technologist, computed tomography, education, training
Abstract: Material discrimination is an important application of dual-energy computed tomography (CT) techniques. Projection decomposition is a key problem for pre-reconstruction material discrimination. In this study, we focused on the pre-reconstruction space based on the photoelectric and Compton effect decomposition model to characterize different material components, and proposed an efficient method to calculate the projection decomposition coefficient. We converted the complex projection integral into a linear equation by calculating the equivalent monochromatic energy from the high and low energy spectrum. Meanwhile, we constructed a dual-energy CT system based on a photon-counting detector to take small animal scan and material discrimination analysis.…Finally, the results of simulation and experimental study demonstrated the feasibility of our proposed new method, and explained the characteristics of photoelectric absorption and Compton scattering reconstruction images.
Keywords: Keywords: Dual-energy CT, photon-counting detector, material discrimination, projection
Abstract: Influence of x-ray pulse generated from gamma spectrometers should be eliminated in applications, which typically uses pulse shape techniques between gamma and x-ray pulses. In this study, we proposed and tested several algorithms aiming to eliminate this influence. The algorithms are based on curve fitting (CF), artificial neural network (ANN), system identification, peak shape, amplitude search with curve fitting and pulse tracking methods. Gamma pulses and X-ray pulses are detected by NaI(TI) scintillator detector and Silicon lithium Si(Li) detector, respectively. The developed algorithms are tested using 32,000 total instantaneous detector events of acquired gamma pulses and 65,536 total instantaneous detector…events of x-ray source. An algorithm using the least square curve fitting method is applied for differentiation between gamma and x-ray pulses. ANN is employed as a classifier for identification of extracted spectrum and Bispectrum features of gamma and x-ray pulses. A comparison between identification results due to extracted spectrum and Bispectrum features is established. System identification algorithm is then built to determine the detection system response of each radiation pulse, which includes various models to attain best fitting. These models are Auto-regressive model with external input (ARX), the linear parametric model (IV) and process models (P1D). The peak shape algorithm is also tried, which depends on the individual classification of pulse width. The amplitude search with curve fitting algorithm is implemented. Moreover, the pulse tracking algorithm is investigated for PSD between gamma and x-ray pulses. The maximum peak of contaminated pulse is tracked using a suggested peak search method. Then, pulse position is estimated using matrix method. Comparison between these algorithms is conducted based on the evaluation of light of residuals, fitting error and processing time. The results confirm that peak shape algorithm is the best one from computational speed point of view, while ANN algorithm using Bispectrum feature extraction method is the most appropriate one that yields 100% accuracy over noisy environment with longer processing time. In addition, the system identification algorithm is the optimal algorithm that achieves zero fitting error under clean environment. These proposed algorithms for PSD between gamma and x-ray pulses lead to design efficient spectrometers with optimal applicability in various environments.
Keywords: Spectrometers, medical imaging, FPGA, digital signal processing
Abstract: Inspired by the compressed sensing (CS) theory, introducing priori information of sparse image into sparse-view reconstruction algorithm of computed tomography (CT) can improve image quality. In recent years, as a special case of CS, total variation (TV) reconstruction algorithm that uses both image sparsity and prior information of edge direction have attracted much research interest in sparse-view image reconstruction due to its ability to preserve image edges. In this paper, we propose a new adaptive-weighted total variation (NAWTV) algorithm for CT image reconstruction, which is derived by considering local gradient direction continuity and the anisotropic edge property. The anisotropic edge…property is used to consolidate the image sparsity, where the associated weights are expressed as a combination of exponential and cosine function. The weights can also be adjusted adaptively according the local image intensity gradient. The NAWTV algorithm is numerically implemented with gradient descent method. The typical Shepp-Logan phantom and FORBILD head phantom are employed to perform image reconstruction simulation. To evaluate performance of NAWTV algorithm, we compared it with TV and AwTV reconstruction algorithms in experiments. Numerical experimental results verified the effectiveness and feasibility of the proposed algorithm. Comparison results also showed that the NAWTV algorithm achieved a satisfactory performance in suppressing artifacts and preserving the edge structure details information of the reconstructed image.
Keywords: Compressed sensing, computed tomography, sparse-view reconstruction, total variation
Abstract: PURPOSE: To explore the hemodynamic characteristics of variously differentiated breast ductal carcinoma (BDC) using the dynamic contrast-enhanced CT (DCE-CT) based CT perfusion imaging (CTPI), including the specific perfusion parameter values, and to identify potential clinical applications in the cell differentiation degree of BDC. MATERIALS AND METHODS: Forty patients with breast ductal carcinoma confirmed by needle puncture biopsy were studied prospectively using CTPI on a 64-slice spiral CT scanner. The acquired volume data were used for calculations, mapping, and analysis by using a tumor perfusion protocol in the CT perfusion software package to measure 4 parameters namely, blood flow…(BF), blood volume (BV), mean transit time (MTT), and the permeability surface (PS) area product. The different differentiated BDC with CT perfusion parameters were divided into 3 groups of high, moderate and poor differentiation. The comparison among these groups were then made using statistical data analysis software. RESULTS: The patients were categorized into three groups of 12, 13, and 15 highly, moderately and poorly differentiated ductal carcinoma cases, respectively. Comparing the perfusion parameters values of the three groups, BF, BV, and PS values increased from highly to poorly differentiated BDC cases. Differences between the highly and moderately or poorly differentiated groups were all statistically significant for BF, BV, and PS values (p < 0.05), while MTT value showed no statistical difference among the three groups (p > 0.05). CONCLUSION: CTPI is a functional imaging technology from the perspective of hemodynamics with potential clinical applications. Three parameters of BF, BV and PS values have potential to serve as indicators of the cell differentiation degree of the breast ductal carcinoma.
Keywords: Breast cancer, tumor differentiation, dynamic contrast-enhanced CT, cancer prognosis
Abstract: OBJECTIVE: Correlation between myocardial infarction (MI) scar by cardiac magnetic resonance and the Lown’s classification of ventricular premature beats (VPBs) is poorly understood. This study aims to investigate the correlation between the MI scar characteristics by delayed-enhancement magnetic resonance imaging (DE-MRI) and the Lown’s classification of VPBs. METHODS: Sixty-five patients, in the convalescence stage and consolidation phase of MI, were included in this retrospective study. All patient were divided into VPBs group (n = 39) and non-VPBs group (n = 26 patients) according to the clinical diagnostic criteria of Universal Definition of MI scar. VPBs patients were assigned to Lown’s…I-II group and Lown’s III-IV subgroup in accordance with the Lown classification criteria. Cardiac function parameters and MI scar characteristics were detected by cardiac magnetic resonance (CMR) and DE-MRI, respectively. RESULTS: Lown’s classification was negatively correlated with left ventricular ejection fraction (LVEF), peak ejection rate (PER) and peak filling rate (PFR) (–0.724, –0.628, –0.559), and positively correlated with MI area, MI integral, MI segments number and left ventricular end systolic volume (LVESV) (0.673, 0.655, 0.586, and 0.514), respectively. CONCLUSIONS The study indicated that MI area and MI integral were strongly associated with Lown’s classification.
Abstract: BACKGROUND: Anesthesia may alter the cellular components contributing to the magnetic resonance imaging (MRI) signal intensities. Developing awake animal models to evaluate cerebral function has grown in importance. OBJECTIVE: To investigate a noninvasive strategy for dynamic MRI (dMRI) of awake rabbits during carbogen challenge. METHODS: A nonmetallic assistive device with a self-adhering wrap secure procedure was developed for the head fixation of awake rabbits. Multi-shot gradient echo echo-planar imaging sequence was applied for the dMRI on a 1.5 T clinical MRI scanner with a quadrature head coil. The carbogen challenge pattern was applied in…a sequence of air - carbogen - air - carbogen - air. Twelve scans were performed for each block of carbogen challenge. T2 -weighted fast-spin echo and T1 -weighted gradient echo sequences were performed before and after dMRI to evaluate the head position shifts. The whole dMRI scan time was about 30 minutes. RESULTS: The position shift of 8 rabbits in the x-and y-direction was less than 3%. The average MRI signal intensities (SI) from the 8 rabbits during carbogen challenge was fitted well using exponential growth and decay functions. The average MRI SI increase due to carbogen inhaling was 1.51%. CONCLUSIONS: The proposed strategy for head dMRI on an awake rabbit during carbogen challenge is feasible.