Numerical study on the hydrodynamic performance and internal flow of an axial-flow pump with various inlet flow angles.

In this study, numerical simulation was employed to predict the performance and internal flow characteristics of the inlet of an axial-flow pump by assigning an absolute flow angle to the inlet guide vane (IGV) trailing-edge flow. Further, the finite volume method based on the three-dimensional Reynolds-averaged Navier-Stokes equations was employed to discretize the governing equations. The shear stress transport model was used as the turbulence model, and an appropriate number of nodes were selected for the hexahedral grid system through a grid-dependency test. The performance curve and changes in the internal flow field were investigated based on the variation in the flow angle at the inlet of the axial-flow pump. These results can be used to establish an efficient operational plan by adjusting the IGV angle of IGV when installing a variable IGV for an axial-flow pump.

Numerical investigation on functional limitations of the anti-stall fin for an axial fan: one-factor analyses.

The stall in an axial fan is directly related to detrimental phenomena such as performance degradation, vibration, noise, and flow instability at low flow rates. As a kind of passive control method to handle the stall, two-dimensional plates so-named anti-stall fin (ASF) were suggested by ourselves and were attached inside the casing. In this study, the ASF's effect on the internal flow pattern was visually investigated in the flow passage, and its tendency was discussed with the performance curve. Subsequently, the ASF's functional limitations for various design parameters, which the ASF can derive aerodynamically, were presented as the primary focus of this study. Each one-factor analysis was performed, and the internal flow pattern was observed in parallel at the point where the ASF lost its function. For the radial length, axial length, number of fins, and positive-tangential angle, the ASF almost retained its function up to the limitation to prevent instability but radically lost its function at a certain flow rate. For the axial gap and negative-tangential angle, the ASF gradually lost its function. Mostly, this study was based on numerical analysis, and the performance was validated through experimental tests.

In silico design and fabrication of an SFI chip-based microspheroid culture system.

The emergence of microfluidic devices and computational fluid dynamics (CFD) has propelled the need for next-generation biomimetic cell culture platforms that are flexible for monitoring and regulation. Therefore, this study evaluated a CFD application in an in silico-designed and spheroid-based flow integration 3D cell culture chip (SFI chip) to illustrate cell culture, drug screening, cytokine delivery, and differentiation of cells in a platform that partially recapitulates the natural environment. Our results show that a flow rate of 0.05 mL h-1 or less induced no physical stress in the SFI chip (15 mm), and uniform cell spheroids (approximately 200 µm) were formed across the platform. The cultured cells were tested in several experimental contexts (co-culture, drug screening, cytokine delivery, and differentiation), demonstrating the usefulness of computational simulation in expediting discovery and simple and effective means to scale the production of standardized cell spheroids cultured under dynamic and natural conditions. Advanced cell culture technologies can be used to accelerate research and discovery and the preclinical and clinical development of cell and cell-free therapies for urgent medical needs.

Feasibility study of portable multi-energy computed tomography with photon-counting detector for preclinical and clinical applications.

In this study, preclinical experiments were performed with an in-house developed prototypal photon-counting detector computed tomography (PCD CT) system. The performance of the system was compared with the conventional energy-integrating detector (EID)-based CT, concerning the basic image quality biomarkers and the respective capacities for material separation. The pre- and the post-contrast axial images of a canine brain captured by the PCD CT and EID CT systems were found to be visually similar. Multi-energy images were acquired using the PCD CT system, and machine learning-based material decomposition was performed to segment the white and gray matters for the first time in soft tissue segmentation. Furthermore, to accommodate clinical applications that require high resolution acquisitions, a small, native, high-resolution (HR) detector was implemented on the PCD CT system, and its performance was evaluated based on animal experiments. The HR acquisition mode improved the spatial resolution and delineation of the fine structures in the canine's nasal turbinates compared to the standard mode. Clinical applications that rely on high-spatial resolution expectedly will also benefit from this resolution-enhancing function. The results demonstrate the potential impact on the brain tissue segmentation, improved detection of the liver tumors, and capacity to reconstruct high-resolution images both preclinically and clinically.

Metal artifact reduction and tumor detection using photon-counting multi-energy computed tomography.

Metal artifacts are considered a major challenge in computed tomography (CT) as these adversely affect the diagnosis and treatment of patients. Several approaches have been developed to address this problem. The present study explored the clinical potential of a novel photon-counting detector (PCD) CT system in reducing metal artifacts in head CT scans. In particular, we studied the recovery of an oral tumor region located under metal artifacts after correction. Three energy thresholds were used to group data into three bins (bin 1: low-energy, bin 2: middle-energy, and bin 3: high-energy) in the prototype PCD CT system. Three types of physical phantoms were scanned on the prototype PCD CT system. First, we assessed the accuracy of iodine quantification using iodine phantoms at varying concentrations. Second, we evaluated the performance of material decomposition (MD) and virtual monochromatic images (VMIs) using a multi-energy CT phantom. Third, we designed an ATOM phantom with metal insertions to verify the effect of the proposed metal artifact reduction. In particular, we placed an insertion-mimicking an iodine-enhanced oral tumor in the beam path of metallic objects. Normalized metal artifact reduction (NMAR) was performed for each energy bin image, followed by an image-based MD and VMI reconstruction. Image quality was analyzed quantitatively by contrast-to-noise ratio (CNR) measurements. The results of iodine quantification showed a good match between the true and measured iodine concentrations. Furthermore, as expected, the contrast between iodine and the surrounding material was higher in bin 1 image than in bin 3 image. On the other hand, the bin 3 image of the ATOM phantom showed fewer metal artifacts than the bin 1 image because of the higher photon energy. The result of quantitative assessment demonstrated that the 40-keV VMI (CNR: 20.6 ± 1.2) with NMAR and MD remarkably increased the contrast of the iodine-enhanced region compared with that of the conventional images (CNR: 10.4 ± 0.5) having 30 to 140 keV energy levels. The PCD-based multi-energy CT imaging has immense potential to maximize the contrast of the target tissue and reduce metal artifacts simultaneously. We believe that it would open the door to novel applications for the diagnosis and treatment of several diseases.

CLIMAR: classified linear interpolation based metal artifact reduction for severe metal artifact reduction in x-ray CT imaging.

In x-ray CT imaging, the existence of metal in the imaging field of view deteriorates the quality of the reconstructed image. This is because rays penetrating dense metal implants are highly corrupted, causing huge inconsistency between projection data. The result appears as strong artifacts such as black and white streaks on the reconstructed image disturbing correct diagnosis. For several decades, there have been various trials to reduce metal artifacts for better image quality. As the computing power of computer processors became more powerful, more complex algorithms with improved performance have been introduced. For instance, the initially developed metal artifact reduction (MAR) algorithms based on simple sinogram interpolation were combined with computationally expensive iterative reconstruction techniques to pursue better image quality. Recently, even machine learning based techniques have been introduced, which require huge amounts of computations for training. In this paper, we introduce an image based novel MAR algorithm in which severe metal artifacts such as black shadings are detected by the proposed method in a straightforward manner based on a linear interpolation. To do that, a new concept of metal artifact classification is devised using linear interpolation in the virtual projection domain. The proposed method reduces severe artifacts very quickly and effectively and has good performance to keep the detailed body structure preserved. Results of qualitative and quantitative comparisons with other representative algorithms such as LIMAR and NMAR support the excellence of the proposed algorithm. Thanks to the nature of reducing artifacts in the image itself and its low computational cost, the proposed algorithm can function as an initial image generator for other MAR algorithms, as well as being integrated in the modalities under limited computation power such as mobile CT scanners.

Motion correction for routine X-ray lung CT imaging.

A novel motion correction algorithm for X-ray lung CT imaging has been developed recently. It was designed to perform for routine chest or thorax CT scans without gating, namely axial or helical scans with pitch around 1.0. The algorithm makes use of two conjugate partial angle reconstruction images for motion estimation via non-rigid registration which is followed by a motion compensated reconstruction. Differently from other conventional approaches, no segmentation is adopted in motion estimation. This makes motion estimation of various fine lung structures possible. The aim of this study is to explore the performance of the proposed method in correcting the lung motion artifacts which arise even under routine CT scans with breath-hold. The artifacts are known to mimic various lung diseases, so it is of great interest to address the problem. For that purpose, a moving phantom experiment and clinical study (seven cases) were conducted. We selected the entropy and positivity as figure of merits to compare the reconstructed images before and after the motion correction. Results of both phantom and clinical studies showed a statistically significant improvement by the proposed method, namely up to 53.6% (p < 0.05) and up to 35.5% (p < 0.05) improvement by means of the positivity measure, respectively. Images of the proposed method show significantly reduced motion artifacts of various lung structures such as lung parenchyma, pulmonary vessels, and airways which are prominent in FBP images. Results of two exemplary cases also showed great potential of the proposed method in correcting motion artifacts of the aorta which is known to mimic aortic dissection. Compared to other approaches, the proposed method provides an excellent performance and a fully automatic workflow. In addition, it has a great potential to handle motions in wide range of organs such as lung structures and the aorta. We expect that this would pave a way toward innovations in chest and thorax CT imaging.

Validation of a novel cardiac motion correction algorithm for x-ray computed tomography: From phantom experiments to initial clinical experience.

A novel cardiac motion correction algorithm has been introduced recently. Unlike other segmentation-based approaches it is fully automatic and capable of correcting motion artifacts of myocardial wall and other moving structures as well as coronary arteries of the heart. In addition, it requires raw data of only less than a single rotation for motion estimation and correction, which is a significant advantage from the perspective of x-ray exposure and workflow. The aim of this study is to explore the capability of the proposed method through phantoms and in-vivo experiments. Motion correction of coronary arteries and other heart structures including myocardial wall is the main focus of the evaluation. First, we provide a brief introduction to the concept of the motion correction algorithm. Next we address the procedure of our studies using an XCAT phantom and commercially available physical phantoms. Results of XCAT phantom demonstrate that our solution significantly improves the structural similarity of coronary arteries compared to FBP (proposed: 0.94, FBP: 0.77, p<0.001). Besides, it provides significantly lower root mean square error (proposed: 20.27, FBP: 25.33, p = 0.01) of the whole heart image. Mocomo phantom study shows that the proposed method improves the visualization of coronary arteries estimated based on motion score (1: worst, 5: best) from two experienced radiologists (proposed: 3.5, FBP: 2.1, p<0.001). The results of these phantom studies reveal that the proposed has a great potential in handling motion artifacts of other heart structures as well as coronary arteries. Finally, we provide the results of in-vivo animal and human studies. The 3D and 4D heart images show a consistently superior performance in the visualization of coronary arteries along with myocardial wall and other cardiothoracic structures. Based on these findings of our studies, we are of the opinion that our solution has a considerable potential to improve temporal resolution of cardiac CT imaging. This would open the door to innovations in structural or functional diagnosis of the heart.

Relationships between Obesity, Nutrient Supply and Primary Open Angle Glaucoma in Koreans.

To investigate the association between nutrient intake and primary open angle glaucoma (POAG) in Koreans, a population-based, cross-sectional survey, the Korean National Health and Nutrition Examination Survey, was analyzed. Glaucoma diagnosis was based on criteria established by the International Society of Geographic and Epidemiologic Ophthalmology. Multivariate regression analysis was used to assess the correlation between dietary intake and the prevalence of POAG in all enrolled subjects. In the low Body mass index(BMI) group (BMI <18.5), females with POAG had significantly lower intakes of energy, protein, fat, carbohydrate, ash, calcium, phosphorus, sodium, potassium, vitamin A, B-carotene, thiamin, riboflavin, and vitamin C than their non-glaucoma counterparts, based on a multivariate logistic regression analysis (all p < 0.05). In females with a medium BMI (18.5 ≤ BMI < 23), POAG showed a significant association with lower food intake, energy, protein, calcium, phosphorus, potassium, thiamin and niacin. (all p < 0.05). Lower protein thiamine intake in medium BMI males was related to POAG. Low dietary intake of several nutrients showed an association with glaucoma in low BMI female subjects. An insufficient intake of certain nutrients may be associated with an increased risk of glaucoma in Koreans. Further large-scale cohort studies are needed to determine how specific nutrients alter the risk of glaucoma.

Head Motion Correction Based on Filtered Backprojection in Helical CT Scanning.

Head motion may unexpectedly occur during a CT scan. It thereby results in motion artifacts in a reconstructed image and may lead to a false diagnosis or a failure of diagnosis. To alleviate this motion problem, as a hardware approach, increasing the gantry rotation speed or using an immobilization device is usually considered. These approaches, however, cannot completely resolve the motion problem. Hence, motion estimation (ME) and compensation for it have been explored as a software approach instead. In this paper, adopting the latter approach, we propose a head motion correction algorithm in helical CT scanning, based on filtered backprojection (FBP). For the motion correction, we first introduce a new motion-compensated (MC) reconstruction scheme based on FBP, which is applicable to helical scanning. We then estimate the head motion parameters by using an iterative nonlinear optimization algorithm, or the L-BFGS. Note here that an objective function for the optimization is defined on reconstructed images in each iteration, which are obtained by using the proposed MC reconstruction scheme. Using the estimated motion parameters, we then obtain the final MC reconstructed image. Using numerical and physical phantom datasets along with simulated head motions, we demonstrate that the proposed algorithm can provide significantly improved quality to MC reconstructed images by alleviating motion artifacts.

Predictors of mortality in autoimmune disease patients with concurrent cytomegalovirus infections detected by quantitative real-time PCR.

OBJECTIVE: Cytomegaloviruses (CMV) can have a significant impact on the prognosis of immunocompromised patients. Unlike in the transplantation and AIDS fields, only a few studies on CMV infections have been published in the field of autoimmunity. In this study, we examined the clinical outcomes of CMV infections in patients with autoimmune diseases at a single tertiary medical institution. METHODS: A retrospective study was performed to identify the mortality risk factors associated with CMV infections in patients with autoimmune diseases. We reviewed the medical records of patients with autoimmune diseases who were diagnosed with CMV infections using real-time quantitative polymerase chain reaction between December 2005 and March 2016. Clinical and laboratory parameters as well as treatment outcomes were analyzed. RESULTS: Seventy-three CMV infected patients were separated into survivors and non-survivors. Non-survivors had significantly higher median CMV-DNA copy numbers than survivors (95,500 vs 6,700 copies/mL, p = 0.005) and demonstrated significantly more frequent incidents of CMV pneumonitis (69.2 vs 36.2%, p = 0.007). After adjusting for multiple confounding covariates, the log CMV-DNA copies/mL (hazard ratio, 1.48; 95% confidence interval, 1.14-1.92; p = 0.003) and the presence of concurrent infections (hazard ratio, 22.00; 95% confidence interval, 2.75-175.97, p = 0.004) were identified as independent mortality risk factors. Furthermore, patients with high CMV copy numbers (> 60,000 copies/mL) had higher in-hospital mortality than those with low CMV copy numbers (p < 0.05). CONCLUSIONS: CMV-DNA copy numbers and concurrent infections are predictors of in-hospital mortality in CMV-infected patients with autoimmune diseases. Therefore, serial measurements of CMV-DNA copy numbers and close observation for signs of other infections are recommended for patients with autoimmune diseases who have concurrent CMV infection.

Delayed Severe Hemobilia after Endoscopic Biliary Plastic Stent Insertion.

Hemobilia is a rare gastrointestinal bleeding, usually caused by injury to the bile duct. Hemobilia after endoscopic retrograde cholangiopancreatography (ERCP) is generally self-limiting and patients will spontaneously recover, but some severe and fatal hemorrhages have been reported. ERCP-related bowel or bile duct perforation should be managed promptly, according to the type of injury and the status of the patient. We recently experienced a case of late-onset severe hemobilia in which the patient recovered after endoscopic biliary stent insertion. The problem was attributable to ERCP-related bile duct perforation during stone removal, approximately 5 weeks prior to the hemorrhagic episode. The removal of the stent was performed 10 days before the onset of hemobilia. The bleeding was successfully treated by two sessions of transarterial coil embolization.

Implementation of hospital examination reservation system using data mining technique.

OBJECTIVES: New methods for obtaining appropriate information for users have been attempted with the development of information technology and the Internet. Among such methods, the demand for systems and services that can improve patient satisfaction has increased in hospital care environments. METHODS: In this paper, we proposed the Hospital Exam Reservation System (HERS), which uses the data mining method. First, we focused on carrying clinical exam data and finding the optimal schedule for generating rules using the multi-examination pattern-mining algorithm. Then, HERS was applied by a rule master and recommending system with an exam log. Finally, HERS was designed as a user-friendly interface. RESULTS: HERS has been applied at the National Cancer Center in Korea since June 2014. As the number of scheduled exams increased, the time required to schedule more than a single condition decreased (from 398.67% to 168.67% and from 448.49% to 188.49%; p < 0.0001). As the number of tests increased, the difference between HERS and non-HERS increased (from 0.18 days to 0.81 days). CONCLUSIONS: It was possible to expand the efficiency of HERS studies using mining technology in not only exam reservations, but also the medical environment. The proposed system based on doctor prescription removes exams that were not executed in order to improve recommendation accuracy. In addition, we expect HERS to become an effective system in various medical environments.