Search results for: chest imaging

Authors: Priyal Chikhaliwala, Sudeshna Chandra

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Liver cancer is one of the most common malignant tumors with poor prognosis. This is because liver cancer does not exhibit any symptoms in early stage of disease. Increased serum level of AFP is clinically considered as a diagnostic marker for liver malignancy. The present diagnostic modalities include various types of immunoassays, radiological studies, and biopsy. However, these tests undergo slow response times, require significant sample volumes, achieve limited sensitivity and ultimately become expensive and burdensome to patients. Considering all these aspects, electrochemical biosensors based on dendrimer-magnetic nanoparticles (MNPs) was designed. Dendrimers are novel nano-sized, three-dimensional molecules with monodispersed structures. Poly-amidoamine (PAMAM) dendrimers with eight –NH₂ groups using ethylenediamine as a core molecule were synthesized using Michael addition reaction. Dendrimers provide added the advantage of not only stabilizing Fe₃O₄ NPs but also displays capability of performing multiple electron redox events and binding multiple biological ligands to its dendritic end-surface. Fe₃O₄ NPs due to its superparamagnetic behavior can be exploited for magneto-separation process. Fe₃O₄ NPs were stabilized with PAMAM dendrimer by in situ co-precipitation method. The surface coating was examined by FT-IR, XRD, VSM, and TGA analysis. Electrochemical behavior and kinetic studies were evaluated using CV which revealed that the dendrimer-Fe₃O₄ NPs can be looked upon as electrochemically active materials. Electrochemical immunosensor was designed by immobilizing anti-AFP onto dendrimer-MNPs by gluteraldehyde conjugation reaction. The bioconjugates were then incubated with AFP antigen. The immunosensor was characterized electrochemically indicating successful immuno-binding events. The binding events were also further studied using magnetic particle imaging (MPI) which is a novel imaging modality in which Fe₃O₄ NPs are used as tracer molecules with positive contrast. Multicolor MPI was able to clearly localize AFP antigen and antibody and its binding successfully. Results demonstrate immense potential in terms of biosensing and enabling MPI of AFP in clinical diagnosis.

Keywords: alpha-fetoprotein, dendrimers, electrochemical biosensors, magnetic nanoparticles

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Authors: Jui-Chien Hsieh

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Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

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Authors: Hosam Abdelhady

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Filming the behaviors of individual DNA molecules in their environment when they interact with individual medicinal nano-polymers in a molecular scale has opened the door to understand the effect of the molecular shape, size, and incubation time with nanocarriers on optimizing the design of robust genetic Nano molecules able to resist the enzymatic degradation, enter the cell, reach to the nucleus and kill individual cancer cells in their environment. To this end, we will show how we applied the 4D AFM as a guide to finetune the design of genetic nanoparticles and to film the effects of these nanoparticles on the nanomechanical and morphological profiles of individual cancer cells.

Keywords: AFM, dendrimers, nanoparticles, DNA, gene therapy, imaging

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Authors: A.R. Eskandari, M.R. Eskandari

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A 2D complete identification algorithm for dielectric and multiple objects immersed in air is presented. The employed technique consists of initially retrieving the shape and position of the scattering object using a linear sampling method and then determining the electric permittivity and conductivity of the scatterer using adjoint sensitivity analysis. This inversion algorithm results in high computational speed and efficiency, and it can be generalized for any scatterer structure. Also, this method is robust with respect to noise. The numerical results clearly show that this hybrid approach provides accurate reconstructions of various objects.

Keywords: inverse scattering, microwave imaging, two-dimensional objects, Linear Sampling Method (LSM)

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Authors: Juan C. Gutierrez-Estrada, Inmaculada Pulido-Calvo, Ignacio De La Rosa, Antonio Peregrin, Fernando Gomez-Bravo, Samuel Lopez-Dominguez, Alejandro Garrocho-Cruz, Jairo Castro-Gutierrez

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The semi-intensive aquaculture in traditional earth ponds is the main rearing system in Southern Spain. These fish rearing systems are approximately two thirds of aquatic production in this area which has made a significant contribution to the regional economy in recent years. In this type of rearing system, a crucial aspect is the correct quantification and control of the fish abundance in the ponds because the fish farmer knows how many fishes he puts in the ponds but doesn’t know how many fishes will harvest at the end of the rear period. This is a consequence of the mortality induced by different causes as pathogen agents as parasites, viruses and bacteria and other factors as predation of fish-eating birds and poaching. Track the fish abundance in these installations is very difficult because usually the ponds take up a large area of land and the management of the water flow is not automatized. Therefore, there is a very high degree of uncertainty on the abundance fishes which strongly hinders the management and planning of the sales. A novel and non-invasive procedure to count fishes in the ponds is by the means of imaging sonars, particularly fixed systems and/or linked to aquatic vehicles as Remotely Operated Vehicles (ROVs). In this work, a method based on census stations procedures is proposed to evaluate the fish abundance estimation accuracy using images obtained of multibeam sonars. The results indicate that it is possible to obtain a realistic approach about the number of fishes, sizes and therefore the biomass contained in the ponds. This research is included in the framework of the KTTSeaDrones Project (‘Conocimiento y transferencia de tecnología sobre vehículos aéreos y acuáticos para el desarrollo transfronterizo de ciencias marinas y pesqueras 0622-KTTSEADRONES-5-E’) financed by the European Regional Development Fund (ERDF) through the Interreg V-A Spain-Portugal Programme (POCTEP) 2014-2020.

Keywords: census station procedure, fish biomass, semi-intensive aquaculture, multibeam sonars

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Authors: Tuğçe Arslan

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In the dark and gloomy times of the Middle Ages, high, majestic, and frightening structures were revealed in the architectural field. Thus, gothic architecture began to find a place for itself in different areas and spread its influence. Gothic has found its place in almost every literary genre and manages to show itself as the dominant genre in the works it enters. It has exploited many concepts, such as a chest full of bad feelings, and creates a gloomy, scary, frightening, and pessimistic mood in the story with these concepts. One of the essential concepts it uses while creating these feelings is the concept of “Doppelganger.” With this concept, the authors make sense of the uncanny; at this point, they allow the spaces to act like characters, just like the uncanny feeling Edgar Allan Poe creates in his story “The Fall of the House of the Usher.” In this story by Edgar Allan Poe, attention should be paid to the symbolic link between the two, as “House of Usher” refers to the family and the building. And indeed, it is possible to see this minor rift as representative of a breakdown in family unity, specifically between Madeline and Roderick. Because although the home is not alive, it has some supernatural features that make it look like a living, breathing being. Therefore, the remainder of this paper will argue that apart from the apparent twins, the house should also qualify as a Doppelganger in the story. This study will first explore the physical and mental disorders of the twins and their journey to complement each other; next, in an attempt to demonstrate how the house as a non-living needs to be considered as a Doppelganger of the twins, a close reading on the house depictions will be scrutinized.

Keywords: Edgar Allan Poe, doppelganger, uncanny, gothic, space, home

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Janet Fernandez

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Reading is both for aesthetic and efferent purposes. In order for reading comprehension to take place, the reader needs to be able to make meaningful connections and enjoy the reading process. The notion of reading comprehension is discussed along with the plausible causes of poor reading comprehension abilities among primary school children. Among the major contributing causes are imaging, lack of schemata, selection of reading materials, and habits of the readers. Instruction methods are an integral part of making reading comprehension a meaningful experience, hence several models are presented for the classroom practitioner. Suggestions on how primary school children can improve their reading comprehension skills are offered.

Keywords: children, improve, reading comprehension, meaningful strategies

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Authors: Suehyun Cho, Darrell Harrington, Florent Cros, Olin Palmer, John Caputo, Michael Kardosh, Eran Oren, William Loudon, Alex Kiselyov, Michael Shpigelmacher

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Bionaut Labs, LLC is developing a minimally invasive robotic microdevice designed to treat non-communicating hydrocephalus in both adult and pediatric patients. The device utilizes biocompatible microsurgical particles (Bionaut™) that are specifically designed to safely and reliably perform accurate fenestration(s) in the 3rd ventricle, aqueduct of Sylvius, and/or trapped intraventricular cysts of the brain in order to re-establish normal cerebrospinal fluid flow dynamics and thereby balance and/or normalize intra/intercompartmental pressure. The Bionaut™ is navigated to the target via CSF or brain tissue in a minimally invasive fashion with precise control using real-time imaging. Upon reaching the pre-defined anatomical target, the external driver allows for directing the specific microsurgical action defined to achieve the surgical goal. Notable features of the proposed protocol are i) Bionaut™ access to the intraventricular target follows a clinically validated endoscopy trajectory which may not be feasible via ‘traditional’ rigid endoscopy: ii) the treatment is microsurgical, there are no foreign materials left behind post-procedure; iii) Bionaut™ is an untethered device that is navigated through the subarachnoid and intraventricular compartments of the brain, following pre-designated non-linear trajectories as determined by the safest anatomical and physiological path; iv) Overall protocol involves minimally invasive delivery and post-operational retrieval of the surgical Bionaut™. The approach is expected to be suitable to treat pediatric patients 0-12 months old as well as adult patients with obstructive hydrocephalus who fail traditional shunts or are eligible for endoscopy. Current progress, including platform optimization, Bionaut™ control, and real-time imaging and in vivo safety studies of the Bionauts™ in large animals, specifically the spine and the brain of ovine models, will be discussed.

Keywords: Bionaut™, cerebrospinal fluid, CSF, fenestration, hydrocephalus, micro-robot, microsurgery

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Authors: Evgenia Iakovleva, Juha Koivisto, Pasi Karppinen, J. Inkinen, Mikko Alava

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Preventing the spread of infectious diseases throughout the worldwide is one of the most important tasks of modern health care. Infectious diseases not only account for one fifth of the deaths in the world, but also cause many pathological complications for the human health. Touch surfaces pose an important vector for the spread of infections by varying microorganisms, including antimicrobial resistant organisms. Further, antimicrobial resistance is reply of bacteria to the overused or inappropriate used of antibiotics everywhere. The biggest challenges in bacterial detection by existing methods are non-direct determination, long time of analysis, the sample preparation, use of chemicals and expensive equipment, and availability of qualified specialists. Therefore, a high-performance, rapid, real-time detection is demanded in rapid practical bacterial detection and to control the epidemiological hazard. Among the known methods for determining bacteria on the surfaces, Hyperspectral methods can be used as direct and rapid methods for microorganism detection on different kind of surfaces based on fluorescence without sampling, sample preparation and chemicals. The aim of this study was to assess the relevance of such systems to remote sensing of surfaces for microorganisms detection to prevent a global spread of infectious diseases. Bacillus subtilis and Escherichia coli with different concentrations (from 0 to 10x8 cell/100µL) were detected with hyperspectral camera using different filters as visible visualization of bacteria and background spots on the steel plate. A method of internal standards was applied for monitoring the correctness of the analysis results. Distances from sample to hyperspectral camera and light source are 25 cm and 40 cm, respectively. Each sample is optically imaged from the surface by hyperspectral imaging system, utilizing a JAI CM-140GE-UV camera. Light source is BeamZ FLATPAR DMX Tri-light, 3W tri-colour LEDs (red, blue and green). Light colors are changed through DMX USB Pro interface. The developed system was calibrated following a standard procedure of setting exposure and focused for light with λ=525 nm. The filter is ThorLabs KuriousTM hyperspectral filter controller with wavelengths from 420 to 720 nm. All data collection, pro-processing and multivariate analysis was performed using LabVIEW and Python software. The studied human eye visible and invisible bacterial stains clustered apart from a reference steel material by clustering analysis using different light sources and filter wavelengths. The calculation of random and systematic errors of the analysis results proved the applicability of the method in real conditions. Validation experiments have been carried out with photometry and ATP swab-test. The lower detection limit of developed method is several orders of magnitude lower than for both validation methods. All parameters of the experiments were the same, except for the light. Hyperspectral imaging method allows to separate not only bacteria and surfaces, but also different types of bacteria, such as Gram-negative Escherichia coli and Gram-positive Bacillus subtilis. Developed method allows skipping the sample preparation and the use of chemicals, unlike all other microbiological methods. The time of analysis with novel hyperspectral system is a few seconds, which is innovative in the field of microbiological tests.

Keywords: Escherichia coli, Bacillus subtilis, hyperspectral imaging, microorganisms detection

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Authors: Aadil Khan, Yasser Chomayil, P. P. Venugopalan

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Background: Budd-Chiari syndrome is caused by thrombosis of the hepatic veins and/or the thrombosis of the intrahepatic or suprahepatic IVC. The etiology remains idiopathic in 16% -35% of cases. Malignancy, rheumatological disorder, myeloproliferative disease, inheritable coagulopathy, infection or hyperestrogen state can be identified in many cases. Methodology: Review of case records of the patient presented to Aster Medcity, Emergency Department, Cochin. Introduction:17 years old female was presented to ED with fever, jaundice and abdominal distention since 1 week. O/E: Pallor+, icterus+. Abdomen- gross distension+, shifting dullness+, generalized anasarca+. USG abdomen showed hepatomegaly with mild coarse echotexture and moderate to gross ascites. CT abdomen and chest showed hepatomegaly with thrombosis of all three hepatic vein and moderate ascites suggestive of Budd-Chiari syndrome. Patient was taken for catheter vein thrombolysis. Venogram done the next day revealed almost > 50% opening of the right hepatic vein. Concurrent doppler showed colour and doppler signals in middle hepatic veins. She gradually improved and was discharged home on anticoagulant and adviced regular follow up. Conclusion: Being a rare disease in this young population, high suspicion is required when evaluating young patients with abdominal pain and jaundice.

Keywords: Budd-Chiari syndrome, rare disease, abdominal pain, India

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Authors: Sarai Guerrero, Lijia Liu

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Zinc gallogermanate (ZGGO) is a persistent phosphor that can emit in the near infrared (NIR) range once dopped with Cr³⁺ enabling its use for in-vivo deep-tissue bio-imaging. Such a property also allows for its application in cancer diagnosis and therapy. Given this, work into developing a synthetic procedure that can be done using common laboratory instruments and equipment as well as understanding ZGGO overall, is in demand. However, the ZGGO nanoparticles must have a size compatible for cell intake to occur while still maintaining sufficient photoluminescence. The nanoparticle must also be made biocompatible by functionalizing the surface for hydrophilic solubility and for high particle uniformity in the final product. Additionally, most research is completed on doped ZGGO, leaving a gap in understanding the base form of ZGGO. It also leaves a gap in understanding how doping affects the synthesis of ZGGO. In this work, the first step of optimizing the particle size via the crystalline size of ZGGO was done with undoped ZGGO using the organic acid, oleic acid (OA) for organic ligand-assisted biphasic hydrothermal synthesis. The effects of this synthesis procedure on ZGGO’s crystallinity were evaluated using Powder X-Ray Diffraction (PXRD). OA was selected as the capping ligand as experiments have shown it beneficial in synthesizing sub-10 nm zinc gallate (ZGO) nanoparticles as well as palladium nanocrystals and magnetite (Fe₃O₄) nanoparticles. Later it is possible to substitute OA with a different ligand allowing for hydrophilic solubility. Attenuated Total Reflection Fourier-Transform Infrared (ATR-FTIR) was used to investigate the surface of the nanoparticle to investigate and verify that OA had capped the nanoparticle. PXRD results showed that using this procedure led to improved crystallinity, comparable to the high-purity reagents used on the ZGGO nanoparticles. There was also a change in the crystalline size of the ZGGO nanoparticles. ATR-FTIR showed that once capped ZGGO cannot be annealed as doing so will affect the OA. These results point to this new procedure positively affecting the crystallinity of ZGGO nanoparticles. There are also repeatable implying the procedure is a reliable source of highly crystalline ZGGO nanoparticles. With this completed, the next step will be working on substituting the OA with a hydrophilic ligand. As these ligands effect the solubility of the nanoparticle as well as the pH that the nanoparticles can dissolve in, further research is needed to verify which ligand is best suited for preparing ZGGO for bio-imaging.

Keywords: biphasic hydrothermal synthesis, crystallinity, oleic acid, zinc gallogermanate

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Dalia El Hadi, Alaa Bou Ghannam, Hala Mostafa, Hana Mansour, Ibrahim Hashim, Soubhi Tahhan, Tharwat El Zahran

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Introduction: Neuro-ophthalmological emergencies require prompt assessment and management to avoid vision or life-threatening sequelae. Some would require neuroimaging. Most commonly used are the CT and MRI of the Brain. They can be over-used when not indicated. Their yield remains dependent on multiple factors relating to the clinical scenario. Methods: A retrospective cross-sectional study was conducted by reviewing the electronic medical records of patients presenting to the Emergency Department (ED) with isolated neuro-ophthalmologic complaints. For each patient, data were collected on the clinical presentation, whether neuroimaging was performed (and which type), and the result of neuroimaging. Analysis of the performed neuroimaging was made, and its yield was determined. Results: A total of 211 patients were reviewed. The complaints or symptoms at presentation were: blurry vision, change in the visual field, transient vision loss, floaters, double vision, eye pain, eyelid droop, headache, dizziness and others such as nausea or vomiting. In the ED, a total of 126 neuroimaging procedures were performed. Ninety-four imagings (74.6%) were normal, while 32 (25.4%) had relevant abnormal findings. Only 2 symptoms were significant for abnormal imaging: blurry vision (p-value= 0.038) and visual field change (p-value= 0.014). While 4 physical exam findings had significant abnormal imaging: visual field defect (p-value= 0.016), abnormal pupil reactivity (p-value= 0.028), afferent pupillary defect (p-value= 0.018), and abnormal optic disc exam (p-value= 0.009). Conclusion: Risk indicators for abnormal neuroimaging in the setting of neuro-ophthalmological emergencies are blurred vision or changes in the visual field on history taking. While visual field irregularities, abnormal pupil reactivity with or without afferent pupillary defect, or abnormal optic discs, are risk factors related to physical testing. These findings, when present, should sway the ED physician towards neuroimaging but still individualizing each case is of utmost importance to prevent time-consuming, resource-draining, and sometimes unnecessary workup. In the end, it suggests a well-structured patient-centered algorithm to be followed by ED physicians.

Keywords: emergency department, neuro-ophthalmology, neuroimaging, risk indicators

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Authors: D. Sankara Reddy, T. Kranthi Kumar, K. Sreevani

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This paper investigates the impact of carrier frequency offset (CFO) on the performance of different MIMO-OFDM schemes with high spectral efficiency for next generation of terrestrial digital TV. We show that all studied MIMO-OFDM schemes are sensitive to CFO when it is greater than 1% of intercarrier spacing. We show also that the Alamouti scheme is the most sensitive MIMO scheme to CFO.

Keywords: modulation and multiplexing (MIMO-OFDM), signal processing for transmission carrier frequency offset, future digital TV, imaging and signal processing

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Authors: Nitu Chhikaraa, S. B. Tyagia, Kiran Jainb, Mamta Kharkwala

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The I–III–VI2 semiconductor Nanocrystals such as AgInS2 have great interest for various applications such as optical devices (solar cell and LED), cellular Imaging and bio tagging etc. we synthesized the phase and shape controlled chalcopyrite AgInS2 (AIS) colloidal nanoparticles by thermal decomposition of metal xanthate at low temperature in an organic solvent’s containing surfactant molecules. Here we are focusing on enhancements of photoluminescence of AgInS2 Nps by coating of ZnS at low temperature for application of optical devices. The size of core shell Nps was less than 50nm.by increasing the time and temperature the emission of the wavelength of the Zn coated AgInS2 Nps could be adjusted from visible region to IR the QY of the AgInS2 Nps could be increased by coating of ZnS from 20 to 80% which was reasonably good as compared to those of the previously reported. The synthesized NPs were characterized by PL, UV, XRD and TEM.

Keywords: PL, UV, XRD, TEM

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Authors: Hossein Barri Ghazani

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Transfusion-related acute lung injury is the main reason of transfusion-related death, and it’s assigned to white blood cell reactive antibodies present in the blood product (anti-HLA class I and class II or anti granulocyte antibodies). TRALI may occur in the COVID-19 patients who are treated by convalescent plasma. The rate of TRALI’s reactions is the same in both males and females and can happen in all age groups. TRALI’s occurrence is higher for people who receive plasma from female donors because the parous female donors have multiple HLA antibodies in their plasma. Patients with chronic liver disease have an augmented risk of transfusion-related acute lung injuries from plasma containing blood products like FFP and PRP. The condition of TRALI suddenly starts with a non‐cardiogenic pulmonary Edema, often accompanied by marked systemic hypovolemic and hypotension. The conditions occur during or within a few hours of transfusion. Chest X-ray shows a nodular penetration or bats’ wing pattern of Edema which can be seen in acute respiratory distress syndrome as well. TRALI can occur with any type of blood products and can occur with as little as one unit. The blood donor center should be informed of the suspected TRALI reactions when the symptoms of TRALI are observed. After a review of the clinical data, the donors must be screened for granulocyte and HLA antibodies. The diagnosis and management of TRALI is not simple and is best done with a professional team and a specialty skilled nurse experienced with the upkeep of these patients.

Keywords: TRALI, transfusion-related death, anti-granulocyte antibodies, anti-HLA antibodies, COVID-19

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Authors: A. Manallah, C. Meier

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Confocal spectral interferometry (CSI) is an innovative optical method for determining microtopography of surfaces and thickness of transparent layers, based on the combination of two optical principles: confocal imaging, and spectral interferometry. Confocal optical system images at each instant a single point of the sample. The whole surface is reconstructed by plan scanning. The interference signal generated by mixing two white-light beams is analyzed using a spectrometer. In this work, five ‘rugotests’ of known standard roughnesses are investigated. The topography is then measured and illustrated, and the equivalent roughness is determined and compared with the standard values.

Keywords: confocal spectral interferometry, nondestructive testing, optical metrology, surface topography, roughness

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Authors: Leila Keshavarz Afshar, Hedieh Sajedi

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Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

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Authors: Wan Azuati Wan Omar, Selva Rani John Jasudass, Siti Rohaiza Md. Saad

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Introduction & objective: The objectives of this study were to assess patient’s knowledge of appropriate sublingual glyceryl trinitrate (GTN) use as well as to investigate how patients commonly store and carry their sublingual GTN tablets. Methodology: This was a cross-sectional survey, using a validated researcher-administered questionnaire. The study involved cardiac patients receiving sublingual GTN attending the outpatient and inpatient departments of Taiping Hospital, a non-academic public care hospital. The minimum calculated sample size was 92, but 100 patients were conveniently sampled. Respondents were interviewed on 3 areas, including demographic data, knowledge and use of sublingual GTN. Eight items were used to calculate each subject’s knowledge score and six items were used to calculate use score. Results: Of the 96 patients who consented to participate, majority (96.9%) were well aware of the indication of sublingual GTN. With regards to the mechanism of action of sublingual GTN, 73 (76%) patients did not know how the medication works. Majority of the patients (66.7%) knew about the proper storage of the tablet. In relation to the maximum number of sublingual GTN tablets that can be taken during each angina episode, 36.5% did not know that up to 3 tablets of sublingual GTN can be taken during each episode of angina. Fifty four (56.2%) patients were not aware that they need to replace sublingual GTN every 8 weeks after receiving the tablets. Majority (69.8%) of the patients demonstrated lack of knowledge with regards to the use of sublingual GTN as prevention of chest pain. Conclusion: Overall, patients’ knowledge regarding the self administration of sublingual GTN is still inadequate. The findings support the need for more frequent reinforcement of patient education, especially in the areas of preventive use, storage and drug stability.

Keywords: glyceryl trinitrate, knowledge, adherence, patient education

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Bang Haeyong

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Purpose: The objectives of this study were to determine the prevalence, incidence, and risk factors for postoperative fever after lumbar fusion. Methods: This study was a retrospective chart review of 291 patients who underwent lumbar fusion between March 2015 and February 2016 at the Asan Medical Center. Information was extracted from electronic medical records. Postoperative fever was measured at Tmax > 37.7 ℃ and Tmax > 38.3 ℃. The presence of postoperative fever, blood culture, urinary excretion, and/or chest x-ray were evaluated. Patients were evaluated for infection after lumbar fusion. Results: We found 222 patients (76.3%) had a postoperative temperature of 37.7 ℃, and 162 patients (55.7%) had a postoperative temperature of 38.3 ℃ or higher. The percentage of febrile patients trended down following the mean 1.8days (from the first postoperative day to seventh postoperative day). Infection rate was 9 patients (3.1%), respiratory virus (1.7%), urinary tract infection (0.3%), phlebitis (0.3%), and surgical site infection (1.4%). There was no correlation between Tmax > 37.7℃ or Tmax > 38.3℃, and timing of fever, positive blood or urine cultures, pneumonia, or surgical site infection. Risk factors for increased postoperative fever following surgery were confirmed to be delay of defecation (OR=1.37, p=.046), and shorten of remove drainage (OR=0.66, p=.037). Conclusions: The incidence of fever was 76.3% after lumbar fusion and the drainage time was faster in the case of fever. It was thought that the bleeding was absorbed at the operation site and fever occurred. The prevalence of febrile septicemia was higher in patients with long bowel movements before surgery than after surgery. Clinical symptoms should be considered because postoperative fever cannot be determined by fever alone because fever and infection are not significant.

Keywords: lumbar surgery, fever, postoperative, risk factor

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Authors: Mohammad Rawashdeh, Mark McEntee, Maha Zaitoun, Mostafa Abdelrahman, Patrick Brennan, Haytham Alewaidat, Sarah Lewis, Charbel Saade

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Despite the tremendous advancements that have been generated by Computed Tomography (CT) in the field of diagnosis, concerns have been raised about the potential cancer induction risk from CT because of the exponentially increased use of it in medicine. This study aims at investigating the application and knowledge of practicing radiographers in Jordan about CT radiation. In order to collect the primary data of this study, a questionnaire was designed and distributed by social media using a snow-balling sampling method. The respondents (n=54) have answered 36 questions including the questions about their demographic information, knowledge about Diagnostic Reference Levels (DRLs), CT exposure and adaptation of pediatric patients exposure. The educational level of the respondents was either at a diploma degree (35.2%) or bachelor (64.8%). The results of this study have indicated a good level of general knowledge between radiographers about the relationship between image quality, exposure parameters, and patient dose. The level of knowledge related to DRL was poor where less than 7.4 percent of the sample members were able to give specific values for a number of common anatomical fields, including abdomen, brain, and chest. Overall, Jordanian radiographers need to gain more knowledge about the expected levels of the dose when applying good practice. Additional education on DRL or DRL inclusion in educational programs is highlighted.

Keywords: computed tomography, CT scan, DRLs, exposure parameters, image quality, radiation dose

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Martyna Ekiert, Natalia Grzechnik, Joanna Karbowniczek, Urszula Stachewicz, Andrzej Mlyniec

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Tendon grafting is a common procedure performed to treat tendon rupture. Before the surgical procedure, tissues intended for grafts (i.e., Achilles tendon) are stored in ultra-low temperatures for a long time and also may be subjected to unfavorable conditions, such as repetitive freezing (F) and thawing (T). Such storage protocols may highly influence the graft mechanical properties, decrease its functionality and thus increase the risk of complications during the transplant procedure. The literature reports on the influence of multiple F/T cycles on internal structure and mechanical properties of tendons stay inconclusive, confirming and denying the negative influence of multiple F/T at the same time. An inconsistent research methodology and lack of clear limit of F/T cycles, which disqualifies tissue for surgical graft purposes, encouraged us to investigate the issue of multiple F/T cycles by the mean of biomechanical tensile tests supported with Scanning Electron Microscope (SEM) imaging. The study was conducted on male bovine Achilles tendon-derived from the local abattoir. Fresh tendons were cleaned of excessive membranes and then sectioned to obtained fascicle bundles. Collected samples were randomly assigned to 6 groups subjected to 1, 2, 4, 6, 8 and 12 cycles of freezing-thawing (F/T), respectively. Each F/T cycle included deep freezing at -80°C temperature, followed by thawing at room temperature. After final thawing, thin slices of the side part of samples subjected to 1, 4, 8 and 12 F/T cycles were collected for SEM imaging. Then, the width and thickness of all samples were measured to calculate the cross-sectional area. Biomechanical tests were performed using the universal testing machine (model Instron 8872, INSTRON®, Norwood, Massachusetts, USA) using a load cell with a maximum capacity of 250 kN and standard atmospheric conditions. Both ends of each fascicle bundle were manually clamped in grasping clamps using abrasive paper and wet cellulose wadding swabs to prevent tissue slipping while clamping and testing. Samples were subjected to the testing procedure including pre-loading, pre-cycling, loading, holding and unloading steps to obtain stress-strain curves for representing tendon stretching and relaxation. The stiffness of AT fascicles bundle samples was evaluated in terms of modulus of elasticity (Young’s modulus), calculated from the slope of the linear region of stress-strain curves. SEM imaging was preceded by chemical sample preparation including 24hr fixation in 3% glutaraldehyde buffered with 0.1 M phosphate buffer, washing with 0.1 M phosphate buffer solution and dehydration in a graded ethanol solution. SEM images (Merlin Gemini II microscope, ZEISS®) were taken using 30 000x mag, which allowed measuring a diameter of collagen fibrils. The results confirm a decrease in fascicle bundles Young’s modulus as well as a decrease in the diameter of collagen fibrils. These results confirm the negative influence of multiple F/T cycles on the mechanical properties of tendon tissue.

Keywords: biomechanics, collagen, fascicle bundles, soft tissue

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Authors: Zerrin Orbak, Busra Demir

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Osteopetrosis is a rare genetic disease characterized by impaired bone resorption and increased bone sclerosis. Clinical presentation is very different in osteopetrosis. It can be asymptomatic or can be seen with typical symptoms. Here, a case of osteopetrosis was presented when evaluated for nystagmus. She was 10 months old. Parents were second-degree relatives. On physical examination, pigeon chest deformity and horizontal nystagmus were observed. There was a failure of thrive but no fracture. The cardiovascular examination was normal. Cranial, vertebral and long bone roentgenograms revealed characteristic deformities of osteopetrosis and diffuse sclerosis. The diagnosis was confirmed by genetic testing. A Homozygous mutation was detected in the TNFRSF11A gene (c.508A>G p.(Arg170Gly)). RANKL is encoded by the tumor necrosis factor ligand superfamily member 11 (TNFSF11) gene, and the binding to its receptor RANK, encoded by the TNFRSF11A gene, determines the activation of the downstream pathway that drives osteoclast differentiation and activation (51). The complete absence of osteoclasts is the key feature of the osteoclast-poor form of osteopetrosis (46). Patients are characterized by the absence of TRAP-positive osteoclasts in bone biopsies. The osteoclast-poor subtype of osteopetrosis caused by mutations in TNFSF11 gene is ultra-rare in humans. Clinical presentation is usually severe, with onset in early infancy or in fetal life. But here, a case was presented with horizontal nystagmus. A case presented with horizontal nystagmus, which was evaluated by neurology and diagnosed incidentally, was shared.

Keywords: osteopetrosis, nystagmus, bone, osteoclast-poor

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Authors: Igor Belykh

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Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when a digital image is resized on a diagnostic monitor. In this paper, we propose an automated grid artifacts detection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: grid, computed radiography, pattern recognition, image processing, filtering

Procedia PDF Downloads 281

Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

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Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: features extraction, image segmentation, medical images, tumor detection

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Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam

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Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi, and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.

Keywords: shannon, maximum entropy, Renyi, Tsallis entropy

Procedia PDF Downloads 461