Search results for: medical diagnostic imaging

Authors: Murat Durucu

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Glaucoma is a condition of irreversible blindness, early diagnosis and appropriate interventions to make the patients able to see longer time. In this study, it addressed that the importance of developing a decision support system for glaucoma diagnosis. Glaucoma occurs when pressure happens around the eyes it causes some damage to the optic nerves and deterioration of vision. There are different levels ranging blindness of glaucoma disease. The diagnosis at an early stage allows a chance for therapies that slows the progression of the disease. In recent years, imaging technology from Heidelberg Retinal Tomography (HRT), Stereoscopic Disc Photo (SDP) and Optical Coherence Tomography (OCT) have been used for the diagnosis of glaucoma. This better accuracy and faster imaging techniques in response technique of OCT have become the most common method used by experts. Although OCT images or HRT precision and quickness, especially in the early stages, there are still difficulties and mistakes are occurred in diagnosis of glaucoma. It is difficult to obtain objective results on diagnosis and placement process of the doctor's. It seems very important to develop an objective decision support system for diagnosis and level the glaucoma disease for patients. By using OCT images and pattern recognition systems, it is possible to develop a support system for doctors to make their decisions on glaucoma. Thus, in this recent study, we develop an evaluation and support system to the usage of doctors. Pattern recognition system based computer software would help the doctors to make an objective evaluation for their patients. It is intended that after development and evaluation processes of the software, the system is planning to be serve for the usage of doctors in different hospitals.

Keywords: decision support system, glaucoma, image processing, pattern recognition

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Authors: Saman Ahani, Aboozar Dehghan, Roham Vali, Hamid Salehian, Amin Ebrahimi

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Pulsed-wave (PW) doppler ultrasonography is a non-invasive, relatively accurate imaging technique that can measure blood speed. The imaging could be obtained via the common carotid artery, as one of the main vessels supplying the blood of vital organs. In horses, factors such as susceptibility to depression of the cardiovascular system and their large muscular mass have rendered them vulnerable to changes in blood speed. One of the most important factors causing blood velocity changes is the administration of anesthetic drugs, including Ketamine and Acepromazine. Thus, in this study, the Pulsed-wave doppler technique was performed to assess the highest blood velocity in the common carotid artery following administration of Ketamine and Acepromazine. Six male and six female healthy Kurdish horses weighing 351 ± 46 kg (mean ± SD) and aged 9.2 ± 1.7 years (mean ± SD) were housed under animal welfare guidelines. After fasting for six hours, the normal blood flow velocity in the common carotid artery was measured using a Pulsed-wave doppler ultrasonography machine (BK Medical, Denmark), and a high-frequency linear transducer (12 MHz) without applying any sedative drugs as a control group. The same procedure was repeated after each individual received the following medications: 1.1, 2.2 mg/kg Ketamine (Pfizer, USA), and 0.5, 1 mg/kg Acepromizine (RACEHORSE MEDS, Ukraine), with an interval of 21 days between the administration of each dose and/or drug. The ultrasonographic study was done five (T5) and fifteen (T15) minutes after injecting each dose intravenously. Lastly, the statistical analysis was performed using SPSS software version 22 for Windows and a P value less than 0.05 was considered to be statistically significant. Five minutes after administration of Ketamine (1.1, 2.2 mg/kg) in both male and female horses, the blood velocity decreased to 38.44, 34.53 cm/s in males, and 39.06, 34.10 cm/s in females in comparison to the control group (39.59 and 40.39 cm/s in males and females respectively) while administration of 0.5 mg/kg Acepromazine led to a significant rise (73.15 and 55.80 cm/s in males and females respectively) (p<0.05). It means that the most drastic change in blood velocity, regardless of gender, refers to the latter dose/drug. In both medications and both genders, the increase in doses led to a decrease in blood velocity compared to the lower dose of the same drug. In all experiments in this study, the blood velocity approached its normal value at T15. In another study comparing the blood velocity changes affected by Ketamine and Acepromazine through femoral arteries, the most drastic changes were attributed to Ketamine; however, in this experiment, the maximum blood velocity was observed following administration of Acepromazine via the common carotid artery. Therefore, further experiments using the same medications are suggested using Pulsed-wave doppler measuring the blood velocity changes in both femoral and common carotid arteries simultaneously.

Keywords: Acepromazine, common carotid artery, horse, ketamine, pulsed-wave doppler ultrasonography

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Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

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The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

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Authors: M. Sandhya, R. M. Madhumitha, Sharmila Sankar

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Interoperable medical devices (IMDs) face threats due to the increased attack surface accessible by interoperability and the corresponding infrastructure. Initiating networking and coordination functionalities primarily modify medical systems' security properties. Understanding the threats is a vital first step in ultimately crafting security solutions for such systems. The key to this problem is coming up with some common types of threats or attacks with those of security and privacy, and providing this information as a roadmap. This paper analyses the security issues in interoperability of devices and presents the main types of threats that have to be considered to build a secured system.

Keywords: interoperability, threats, attacks, medical devices

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Authors: Nadir A. Carreon, Christa Sonderer, Aakarsh Rao, Roman Lysecky

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With the advent of complex software and increased connectivity, the security of life-critical medical devices is becoming an increasing concern, particularly with their direct impact on human safety. Security is essential, but it is impossible to develop completely secure and impenetrable systems at design time. Therefore, it is important to assess the potential impact on the security and safety of exploiting a vulnerability in such critical medical systems. The common vulnerability scoring system (CVSS) calculates the severity of exploitable vulnerabilities. However, for medical devices it does not consider the unique challenges of impacts to human health and privacy. Thus, the scoring of a medical device on which human life depends (e.g., pacemakers, insulin pumps) can score very low, while a system on which human life does not depend (e.g., hospital archiving systems) might score very high. In this paper, we propose a medical vulnerability scoring system (MVSS) that extends CVSS to address the health and privacy concerns of medical devices. We propose incorporating two new parameters, namely health impact, and sensitivity impact. Sensitivity refers to the type of information that can be stolen from the device, and health represents the impact on the safety of the patient if the vulnerability is exploited (e.g., potential harm, life-threatening). We evaluate fifteen different known vulnerabilities in medical devices and compare MVSS against two state-of-the-art medical device-oriented vulnerability scoring systems and the foundational CVSS.

Keywords: common vulnerability system, medical devices, medical device security, vulnerabilities

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Authors: Koteswara Rao Pagolu, Raghava Rao Tamanam

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The present study was aimed to find out the prevalence of DD's in Visakhapatnam, one of the north coastal districts of Andhra Pradesh, India during a span of five years. A cross-sectional investigation was held at District early intervention center (DEIC), Visakhapatnam from 2016 to 2020. To identify the pattern and trend of different DD's including seasonal variations, a retrospective analysis of the health center's inpatient database for the past 5 years was done. Male and female children aged 2 months-18 years are included in the study with the prior permission of the concerned medical officer. The screening tool developed by the Ministry of health and family welfare, India, was used for the study. Among 26,423 cases, children with birth defects are 962, 2229 with deficiencies, 7516 with diseases, and 15716 with disabilities were admitted during the study period. From birth defects, congenital deafness occurred in large numbers with 22.66%, and neural tube defect observed in a small number of cases with 0.83% during the period. From the side of deficiencies, severe acute malnutrition has mostly occurred (66.80 %) and a small number of children were affected with goiter (1.70%). Among the diseases, dental carriers (67.97%) are mostly found and these cases were at peak during the years 2016 and 2019. From disabilities, children with vision impairment (20.55%) have mostly approached the center. Over the past 5 years, the admission rate of down's syndrome and congenital deafness cases showed a rising trend up to 2019 and then declined. Hearing impairment, motor delay, and learning disorder showed a steep rise and gradual decline trend, whereas severe anemia, vitamin-D deficiency, otitis media, reactive airway disease, and attention deficit hyperactivity disorder showed a declining trend. However, congenital heart diseases, dental caries, and vision impairment admission rates showed a zigzag pattern over the past 5 years. This center had inadequate diagnostic facilities related to genetic disease management. For advanced confirmation, the cases are referred to a district government hospital or private diagnostic laboratories in the city for genetic tests. Information regarding the overall burden and pattern of admissions in the health center is obtained by the review of DEIC records. Through this study, it is observed that the incidence of birth defects, as well as genetic disease burden, is high in the Visakhapatnam district. Hence there is a need for strengthening of management services for these diseases in this region.

Keywords: child health screening, developmental delays, district early intervention center, genetic disease management, infrastructural facility, Visakhapatnam district

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Authors: Mona Elhelbawy, Mac Gray

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Traditional wired endoscopy is an intrusive process that requires a long flexible tube to be inserted through the patient’s mouth while intravenously sedated. Only images of the upper 4 feet of stomach, colon, and rectum can be captured, leaving the remaining 20 feet of small intestines. Wireless capsule endoscopy offers a painless, non-intrusive, efficient and effective alternative to traditional endoscopy. In wireless capsule endoscopy (WCE), ingestible vitamin-pill-shaped capsules with imaging capabilities, sensors, batteries, and antennas are designed to send images of the gastrointestinal (GI) tract in real time. In this paper, we investigate the radiation performance and specific absorption rate (SAR) of a miniature conformal capsule antenna operating at the Medical Implant Communication Service (MICS) frequency band in the human body. We perform numerical simulations using the finite element method based commercial software, high-frequency structure simulator (HFSS) and the ANSYS human body model (HBM). We also investigate the in-body channel characteristics between the implantable capsule and an external antenna placed on the surface of the human body.

Keywords: IEEE 802.15.6, MICS, SAR, WCE

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Authors: Mohammed Saeed Jawad

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Metaverse involves the convergence of three major technologies trends of AI, VR, and AR. Together these three technologies can provide an entirely new channel for delivering healthcare with great potential to lower costs and improve patient outcomes on a larger scale. Telepresence is the technology that allows people to be together even if they are physically apart. Medical doctors can be symbolic as interactive avatars developed to have smart conversations and medical recommendations for patients at the different stages of the treatment. Medical digital assets such as Medical IoT for real-time remote healthcare monitoring as well as the symbolic doctors’ avatars as well as the hospital and clinical physical constructions and layout can be immersed in extended realities 3D metaverse environments where doctors, nurses, and patients can interact and socialized with the related digital assets that facilitate the data analytics of the sensed and collected personal medical data with visualized interaction of the digital twin of the patient’s body as well as the medical doctors' smart conversation and consultation or even in a guided remote-surgery operation.

Keywords: personal healthcare, metaverse, telemedicine, telepresence, avatar, medical consultation, remote-surgery

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Authors: Ramkumar Gunasekaran, John Cater, Vinod Suresh, Haribalan Kumar

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The main objective of this project is to develop a statistical shape model using principal component analysis that could be used for analyzing the shape of the human airway. The ultimate goal of this project is to identify geometric risk factors for diagnosis and management of Obstructive Sleep Apnoea (OSA). Anonymous CBCT scans of 25 individuals were obtained from the Otago Radiology Group. The airways were segmented between the hard-palate and the aryepiglottic fold using snake active contour segmentation. The point data cloud of the segmented images was then fitted with a bi-cubic mesh, and pseudo landmarks were placed to perform PCA on the segmented airway to analyze the shape of the airway and to find the relationship between the shape and OSA risk factors. From the PCA results, the first four modes of variation were found to be significant. Mode 1 was interpreted to be the overall length of the airway, Mode 2 was related to the anterior-posterior width of the retroglossal region, Mode 3 was related to the lateral dimension of the oropharyngeal region and Mode 4 was related to the anterior-posterior width of the oropharyngeal region. All these regions are subjected to the risk factors of OSA.

Keywords: medical imaging, image processing, FEM/BEM, statistical modelling

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Authors: Palash Dutta

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More frequently uncertainties are encountered in medical diagnosis and therefore it is the most important and interesting area of applications of fuzzy set theory. In this present study, an attempt has been made to extend Sanchez’s approach for medical diagnosis via interval valued picture fuzzy sets and exhibit the technique with suitable case studies. In this article, it is observed that a refusal can be expressed in the databases concerning the examined objects. The technique is performing diagnosis on the basis of distance measures and as a result, this approach makes it possible to introduce weights of all symptoms and consequently patient can be diagnosed directly.

Keywords: medical diagnosis, uncertainty, fuzzy set, picture fuzzy set, interval valued picture fuzzy set

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Authors: Cherif Y., Ghariani R., Derbal S., Farhati S., Ben Dahmen F., Abdallah M.

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Introduction: Tuberculosis (TBC) is a frequent infection and is still a major public health problem in Tunisia. The aim of this work is to focus on diagnostic and therapeutic characteristics of TBC in patients referred to our internal medicine department. Patients and Methods: The study was retrospective and descriptive of a cohort of consecutive cases treated from January 2016 to December 2019, collecting patients with latent or patent TBC. Twenty-eight medical records of adults diagnosed with TBC were reviewed. Results: Twenty-eight patients, including 18 women and 10 men, were diagnosed with TBC. Their mean age is 48 years (range: 22-78 years). Five patients have a medical history of diabetes mellitus, 1 patient was followed for systemic lupus erythematosus treated with corticosteroids and immunosuppressant drugs, and another was treated with corticosteroids for Mac Duffy syndrome. The TBC is latent in 12 cases and patent in 16 cases. The most common symptoms were fever and weight loss and were found in 10 cases, a cough in 2 cases, sputum in 3 cases, lymph nodes in 4 cases, erythema nodosum in 2 cases, and neurological signs in 3 cases. Lymphopenia is noticed in 3 cases and a biological inflammatory syndrome in 18 of the cases. The purified protein derivate reaction was positive in 17 cases, anergic in 3 cases, negative in 5 cases, and not done in 3 cases. The acid-fast bacilli stain culture was strongly positive in one patient. The histopathological study was conclusive in 11 patients and showed granulomatosis with caseous necrosis. TBC was pulmonary in 7 patients, lymph node in 7 cases, peritoneal in 7 cases, digestive in 1 case, neuromeningeal in 3 cases, and thyroïd in 1 case. Seven patients had multifocal TBC. All the patients received anti-tuberculosis treatment with a mean duration of 8 months with no failure or relapse with an average follow-up time of 10.58 months. Conclusion: Diagnosis and management of TBC remain essential to avoid serious complications. The survey is necessary to ensure timely detection and treatment of infected adults to decrease its incidence. The best treatment remains preventive through vaccination and improving social and economic conditions.

Keywords: tuberculosis, infection, autoimmune disease, granulomatosis

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Authors: Bruno RamaëL, GwenaëL Page, Catherine Knopf-Lenoir, Olivier Baledent, Anne-Virginie Salsac

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No routine technique currently exists for clinicians to measure the mechanical properties of vascular walls non-invasively. Most of the data available in the literature come from traction or dilatation tests conducted ex vivo on native blood vessels. The objective of the study is to develop a non-invasive characterization technique based on Magnetic Resonance Imaging (MRI) measurements of the deformation of vascular walls under pulsating blood flow conditions. The goal is to determine the mechanical properties of the vessels by inverse analysis, coupling imaging measurements and numerical simulations of the fluid-structure interactions. The hyperelastic properties are identified using Solidworks and Ansys workbench (ANSYS Inc.) solving an optimization technique. The vessel of interest targeted in the study is the common carotid artery. In vivo MRI measurements of the vessel anatomy and inlet velocity profiles was acquired along the facial vascular network on a cohort of 30 healthy volunteers: - The time-evolution of the blood vessel contours and, thus, of the cross-section surface area was measured by 3D imaging angiography sequences of phase-contrast MRI. - The blood flow velocity was measured using a 2D CINE MRI phase contrast (PC-MRI) method. Reference arterial pressure waveforms were simultaneously measured in the brachial artery using a sphygmomanometer. The three-dimensional (3D) geometry of the arterial network was reconstructed by first creating an STL file from the raw MRI data using the open source imaging software ITK-SNAP. The resulting geometry was then transformed with Solidworks into volumes that are compatible with Ansys softwares. Tetrahedral meshes of the wall and fluid domains were built using the ANSYS Meshing software, with a near-wall mesh refinement method in the case of the fluid domain to improve the accuracy of the fluid flow calculations. Ansys Structural was used for the numerical simulation of the vessel deformation and Ansys CFX for the simulation of the blood flow. The fluid structure interaction simulations showed that the systolic and diastolic blood pressures of the common carotid artery could be taken as reference pressures to identify the mechanical properties of the different arteries of the network. The coefficients of the hyperelastic law were identified using Ansys Design model for the common carotid. Under large deformations, a stiffness of 800 kPa is measured, which is of the same order of magnitude as the Young modulus of collagen fibers. Areas of maximum deformations were highlighted near bifurcations. This study is a first step towards patient-specific characterization of the mechanical properties of the facial vessels. The method is currently applied on patients suffering from facial vascular malformations and on patients scheduled for facial reconstruction. Information on the blood flow velocity as well as on the vessel anatomy and deformability will be key to improve surgical planning in the case of such vascular pathologies.

Keywords: identification, mechanical properties, arterial walls, MRI measurements, numerical simulations

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Authors: Mehdi Modabberifar, Sanaz Jabary, Mojtaba Ghodsi

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Stiffness sensing is an important issue in medical diagnostic, robotics surgery, safe handling, and safe grasping of objects in production lines. Detecting and obtaining the characteristics in dwelling lumps embedded in a soft tissue and safe removing and handling of detected lumps is needed in surgery. Also in industry, grasping and handling an object without damaging in a place where it is not possible to access a human operator is very important. In this paper, a method for object handling is presented. It is based on the use of an intelligent gripper to detect the object stiffness and then setting a programmable force for grasping the object to move it. The main components of this system includes sensors (sensors for measuring force and displacement), electrical (electrical and electronic circuits, tactile data processing and force control system), mechanical (gripper mechanism and driving system for the gripper) and the display unit. The system uses a rotary potentiometer for measuring gripper displacement. A microcontroller using the feedback received by the load cell, mounted on the finger of the gripper, calculates the amount of stiffness, and then commands the gripper motor to apply a certain force on the object. Results of Experiments on some samples with different stiffness show that the gripper works successfully. The gripper can be used in haptic interfaces or robotic systems used for object handling.

Keywords: gripper, haptic, stiffness, robotic

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Catherine Bernard

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The maldistribution of clinicians within countries is well documented. It is a common theme throughout the world that rural areas often struggle to recruit and retain health workers resulting in inadequate healthcare for many. This paper will concentrate on the responsibilities that medical schools may have in addressing this shortage of rural health workers. Recommendations are made with regards to targeted rural student admissions, rurally-based medical schools, rural clinical rotations and a curriculum orientated towards rural health issues. The evidence gathered suggests that individual factors are positive in encouraging health workers to practice in rural locations. However, there is strength in numbers, and combining all the recommendations will likely result in a synergistic effect, thereby increasing numbers of rural health workers and achieving accessible healthcare for those living in rural populations.

Keywords: medical education, medical education design, public health, rural health

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Authors: Fatemeh Noughani, Seyd Mehdi Sadat

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Medical tourism or travel therapy is travelling from one country to another to be under medical treatment, utilizing the health factors of natural sector like mineral water springs and so on. From 1990s medical tourism around the world developed and grew because of different factors like globalization and free trade in the fields of health services, changes in exchange rates in the world economy (which caused the desirability of Asian countries as a medical tourist attraction) in a way that currently there is a close competition in this field among famous countries in medical services to make them find a desirable place in medical tourism market of the world as a complicated and growing industry in a short time. Perhaps tourism is an attractive industry and a good support for the economy of Iran, if we try to merge oil earnings and tourism industry it would be better and more constructive than putting them in front of each other. Moving from oil toward tourism economy especially medical tourism, must be one of the prospects of Iran's government for the oil industry to provide a few percent of the yearly earnings of the country. Among the achievements in medical tourism we can name the prevention of brain drain to other countries and an increase in employment rate for healthcare staff, increase in foreign exchange earnings of the country because of the tourists' staying and followed by increasing the quality of life and cultural transmission as well as empowering the medical human resources.

Keywords: developing countries, health tourism, quality of life, cultural transmission

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Authors: Mahdi Farajzadeh Ajirlou

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The detailed serious adverse effects raised the stresses around the safety of individuals who have gotten COVID-19 vaccines. Numerous verification referrers that disease with COV-19 causes neurological dysfunction in a significant proportion of influenced patients, where these side effects show up seriously amid the disease, and still less is known approximately the potential long-term results for the brain, where the loss of olfaction could be a neurological sign and simple indications of COVID-19. Since publishing effective clinical trial results of mRNA coronavirus disease 2019 (COVID-19) and injecting it to the volunteers in 2020, numerous reports have emerged approximately about cardiovascular complications followed by the mRNA vaccination. Vaccination-associated adenopathy could be a constant imaging finding after the organization of COVID-19 antibodies that will lead to a symptomatic problem in patients with shown or suspected cancer, in whom it may be vague from dangerous nodal inclusion. In spite of all the benefits and viability of the coronavirus infection 2019 (COVID-19) antibodies specified in later clinical trials, a few other post-vaccination side impacts, such as lymphadenopathy (LAP), were observed. Also, numerous variables, including financial conditions, have played a critical part in expanding the number of people with COVID-19 infection and also much more side effects in that country. Amid the Coronavirus widespread, Iran has been experiencing extreme sanctions, which has faced this nation with an extreme financial crisis. Additionally, with COVID-19 widespread, there was a developing concern around the abuse of imaging exams extraordinarily within the pediatric populace, which highlights the issues pointed out by this review.

Keywords: radiology, vaccines, COVID-19, side effect

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Authors: Hyuk-Hoon Kim, Young Gi Min

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Background: In carbon monoxide (CO) intoxication, the pathophysiology of delayed neurological sequelae (DNS) is very complex and remains poorly understood. And predicting whether patients who exhibit resolved acute symptoms have escaped or will experience DNS represents a very important clinical issue. Brain magnetic resonance (MR) imaging has been conducted to assess the severity of brain damage as an objective method to predict prognosis. And co-ingestion of a second poison in patients with intentional CO poisoning occurs in almost one-half of patients. Among patients with co-ingestions, 66% ingested ethanol. We assessed the effects of ethanol on neurologic sequelae prevalence in acute CO intoxication by means of abnormal lesion in brain MR. Method: This study was conducted retrospectively by collecting data for patients who visited an emergency medical center during a period of 5 years. The enrollment criteria were diagnosis of acute CO poisoning and the measurement of the serum ethanol level and history of taking a brain MR during admission period. Official readout data by radiologist are used to decide whether abnormal lesion is existed or not. The enrolled patients were divided into two groups: patients with abnormal lesion and without abnormal lesion in Brain MR. A standardized extraction using medical record was performed; Mann Whitney U test and logistic regression analysis were performed. Result: A total of 112 patients were enrolled, and 68 patients presented abnormal brain lesion on MR. The abnormal brain lesion group had lower serum ethanol level (mean, 20.14 vs 46.71 mg/dL) (p-value<0.001). In addition, univariate logistic regression analysis showed the serum ethanol level (OR, 0.99; 95% CI, 0.98 -1.00) was independently associated with the development of abnormal lesion in brain MR. Conclusion: Ethanol could have neuroprotective effect in acute CO intoxication by sedative effect in stressful situation and mitigative effect in neuro-inflammatory reaction.

Keywords: carbon monoxide, delayed neuropsychological sequelae, ethanol, intoxication, magnetic resonance

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Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

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Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

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Authors: Emmanuel Temitope Adaranijo

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Medical error is on the increase in many nations and like many developing nations, Nigeria is not excluded and more importantly, Lafia, Nasarawa state, where the study was carried. The study was undertaken to explore Patients' knowledge and their reactions to medical errors in hospitals in Lafia Local Government Area; therefore, five objectives were formulated to guide the study. The survey research design was employed and triangulation of quantitative and qualitative instruments was used to collect data. The total population for the study was 330,712 and the sample size was 400; however, only 343 patients and three doctors responded to the quantitative and qualitative study, respectively. Frequency distribution, simple percentage, and r test were used to analyze the data obtained from respondents. The findings revealed that medical errors are prevalent in hospitals in Lafia and the patients are neither aware nor willing to report such occurrence. The study recommends that social workers, hospital management, and governments should take up their roles in reducing the occurrence of medical errors.

Keywords: health, hospital, medical errors, social work

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Authors: Olivier Mulisya, Guelord Barasima, Henry Mark Lugobe, Philémon Matumo, Bienfait Mumbere Vahwere, Hilaire Mutuka, Zawadi Léocadie, Wesley Lumika

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Abdominal pregnancy is defined as pregnancy anywhere within the peritoneal cavity, exclusive of tubal, ovarian, or broad ligament locations. It is a rare form of ectopic pregnancy with high morbidity and mortality for both the mother and the fetus. Diagnosis can be frequently missed in most poor-resource settings because of poor antenatal coverage, low socioeconomic status in most of the patients as well as lack of adequate medical resources. Clinical diagnosis can be very difficult and an ultrasound scan is very helpful during the early stages of gestation but can also be disappointing in the later stages. We report a case of a 25-year-old woman with severe abdominal pain not amended with any medication. A clinical picture of shock lead to an emergency laparotomy which confirmed the diagnosis of abdominal pregnancy. The ministry of health in developing countries should make an effort to make routine early ultrasounds accessible to pregnant women, and obstetricians should keep in mind the possibility of ectopic pregnancy, irrespective of the gestational age.

Keywords: abdominal pregnancy, live new bron, ultrasound imaging, abdominal pain

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Authors: Timea Harmath-Tánczos

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Drug-resistant epilepsy (DRE) is defined as the persistence of seizures despite at least two syndrome-adapted antiseizure drugs (ASD) used at efficacious daily doses. About a third of patients with epilepsy suffer from drug resistance. Cognitive assessment has a crucial role in the diagnosis and clinical management of epilepsy. Previous studies have addressed the clinical targets and indications for measuring neuropsychological functions; best to our knowledge, no studies have examined it in a Hungarian therapy-resistant population. To fill this gap, we investigated the Hungarian diagnostic protocol between 18 and 65 years of age. This study aimed to describe and analyze neuropsychological functions in patients with drug-resistant epilepsy and identify factors associated with neuropsychology deficits. We perform a prospective case-control study comparing neuropsychological performances in 50 adult patients and 50 healthy individuals between March 2023 and July 2023. Neuropsychological functions were examined in both patients and controls using a full set of specific tests (general performance level, motor functions, attention, executive facts., verbal and visual memory, language, and visual-spatial functions). Potential risk factors for neuropsychological deficit were assessed in the patient group using a multivariate analysis. The two groups did not differ in age, sex, dominant hand and level of education. Compared with the control group, patients with drug-resistant epilepsy showed worse performance on motor functions and visuospatial memory, sustained attention, inhibition and verbal memory. Neuropsychological deficits could therefore be systematically detected in patients with drug-resistant epilepsy in order to provide neuropsychological therapy and improve quality of life. The analysis of the classical and complex indices of the special neuropsychological tasks presented in the presentation can help in the investigation of normal and disrupted memory and executive functions in the DRE.

Keywords: drug-resistant epilepsy, Hungarian diagnostic protocol, memory, executive functions, cognitive neuropsychology

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Authors: Zheng Yuxun

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This review critically assesses the advancements and prospective developments in defect detection methodologies within the semiconductor industry, an essential domain that significantly affects the operational efficiency and reliability of electronic components. As semiconductor devices continue to decrease in size and increase in complexity, the precision and efficacy of defect detection strategies become increasingly critical. Tracing the evolution from traditional manual inspections to the adoption of advanced technologies employing automated vision systems, artificial intelligence (AI), and machine learning (ML), the paper highlights the significance of precise defect detection in semiconductor manufacturing by discussing various defect types, such as crystallographic errors, surface anomalies, and chemical impurities, which profoundly influence the functionality and durability of semiconductor devices, underscoring the necessity for their precise identification. The narrative transitions to the technological evolution in defect detection, depicting a shift from rudimentary methods like optical microscopy and basic electronic tests to more sophisticated techniques including electron microscopy, X-ray imaging, and infrared spectroscopy. The incorporation of AI and ML marks a pivotal advancement towards more adaptive, accurate, and expedited defect detection mechanisms. The paper addresses current challenges, particularly the constraints imposed by the diminutive scale of contemporary semiconductor devices, the elevated costs associated with advanced imaging technologies, and the demand for rapid processing that aligns with mass production standards. A critical gap is identified between the capabilities of existing technologies and the industry's requirements, especially concerning scalability and processing velocities. Future research directions are proposed to bridge these gaps, suggesting enhancements in the computational efficiency of AI algorithms, the development of novel materials to improve imaging contrast in defect detection, and the seamless integration of these systems into semiconductor production lines. By offering a synthesis of existing technologies and forecasting upcoming trends, this review aims to foster the dialogue and development of more effective defect detection methods, thereby facilitating the production of more dependable and robust semiconductor devices. This thorough analysis not only elucidates the current technological landscape but also paves the way for forthcoming innovations in semiconductor defect detection.

Keywords: semiconductor defect detection, artificial intelligence in semiconductor manufacturing, machine learning applications, technological evolution in defect analysis

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Authors: Sanjeev Sharma, Suman Lata

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With the availability of diverse printed, electronic literature and web sites on medical and health related information, it is impossible for the medical professional to get the information he seeks in the shortest possible time. For all these problems information literacy is the only solution. Thus, information literacy is recognized as an important aspect of medical education. In the present study, an attempt has been made to know the information literacy skills of the faculty and students at medical colleges of Haryana, Punjab and Chandigarh. The scope of the study was confined to the 12 selected medical colleges of three States (Haryana, Punjab, and Chandigarh). The findings of the study were based on the data collected through 1018 questionnaires filled by the respondents of the medical colleges. It was found that Online Medical Websites (such as WebMD, eMedicine and Mayo Clinic etc.) were frequently used by 63.43% of the respondents of Chandigarh which is slightly more than Haryana (61%) and Punjab (55.65%). As well, 30.86% of the respondents of Chandigarh, 27.41% of Haryana and 27.05% of Punjab were familiar with the controlled vocabulary tool; 25.14% respondents of Chandigarh, 23.80% of Punjab, 23.17% of Haryana were familiar with the Boolean operators; 33.05% of the respondents of Punjab, 28.19% of Haryana and 25.14% of Chandigarh were familiar with the use and importance of the keywords while searching an electronic database; and 51.43% of the respondents of Chandigarh, 44.52% of Punjab and 36.29% of Haryana were able to make effective use of the retrieved information. For accessing information in electronic format, 47.74% of the respondents rated their skills high, while the majority of respondents (76.13%) were unfamiliar with the basic search technique i.e. Boolean operator used for searching information in an online database. On the basis of the findings, it was suggested that a comprehensive training program based on medical professionals information needs should be organized frequently. Furthermore, it was also suggested that information literacy may be included as a subject in the health science curriculum so as to make the medical professionals information literate and independent lifelong learners.

Keywords: information, information literacy, medical professionals, medical colleges

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Authors: Naglaa A. Abd Elkader, Haithem A. Farghali

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The present study carried out on fifteen clinical cases of different species of dogs which admitted to surgical clinic of veterinary medicine with different symptoms (Acute vomiting, hematemesis and anorexia). There was diagnostic march which including plain radiograph and endoscopic examination. Treatment was including surgical interference and endoscopic retrieval followed by medicinal treatment. This study was aimed the detection of different foreign bodies by the most suitable method according to the type of the foreign bodies.

Keywords: stomach, endoscopy, foreign bodies, dogs

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Vadanasundari Vedarethinam, Kun Qian

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The metabolic analysis is more distal over proteomics and genomics engaging in clinics and needs rationally distinct techniques, designed materials, and device for clinical diagnosis. Conventional techniques such as spectroscopic techniques, biochemical analyzers, and electrochemical have been used for metabolic diagnosis. Currently, there are four major challenges including (I) long-term process in sample pretreatment; (II) difficulties in direct metabolic analysis of biosamples due to complexity (III) low molecular weight metabolite detection with accuracy and (IV) construction of diagnostic tools by materials and device-based platforms for real case application in biomedical applications. Development of chips with nanomaterial is promising to address these critical issues. Mass spectroscopy (MS) has displayed high sensitivity and accuracy, throughput, reproducibility, and resolution for molecular analysis. Particularly laser desorption/ ionization mass spectrometry (LDI MS) combined with devices affords desirable speed for mass measurement in seconds and high sensitivity with low cost towards large scale uses. We developed a plasmonic chip for clinical metabolic fingerprinting as a hot carrier in LDI MS by series of chips with gold nanoshells on the surface through controlled particle synthesis, dip-coating, and gold sputtering for mass production. We integrated the optimized chip with microarrays for laboratory automation and nanoscaled experiments, which afforded direct high-performance metabolic fingerprinting by LDI MS using 500 nL of serum, urine, cerebrospinal fluids (CSF) and exosomes. Further, we demonstrated on-chip direct in-vitro metabolic diagnosis of early-stage lung cancer patients using serum and exosomes without any pretreatment or purifications. To our best knowledge, this work initiates a bionanotechnology based platform for advanced metabolic analysis toward large-scale diagnostic use.

Keywords: plasmonic chip, metabolic fingerprinting, LDI MS, in-vitro diagnostics

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Authors: Anny Retnowati, Elisabeth Sundari

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This research aims to elaborate the meaning of personal data protection principles on patient access to health data in medical records in Indonesia and its implications. The method uses normative legal research by examining health law in Indonesia regarding the patient's right to access their health data in medical records. The data will be analysed qualitatively using the interpretation method to elaborate on the limitation of the meaning of personal data protection principles on patients' access to their data in medical records. The results show that patients only have the right to obtain copies of their health data in medical records. There is no right to inspect directly at any time. Indonesian health law limits the principle of patients' right to broad access to their health data in medical records. This restriction has implications for the reduction of personal data protection as part of human rights. This research contribute to show that a limitaion of personal data protection may abuse the human rights.

Keywords: access, health data, medical records, personal data, protection

Procedia PDF Downloads 66

Authors: Yong Zhang

Abstract:

Light has proven to be useful in a wide range of biomedical applications such as fluorescence imaging, photoacoustic imaging, optogenetics, photodynamic therapy, photothermal therapy, and light controlled drug/gene delivery. Taking photodynamic therapy (PDT) as an example, PDT has been proven clinically effective in early lung cancer, bladder cancer, head, and neck cancer and is the primary treatment for skin cancer as well. However, clinical use of PDT is severely constrained by the low penetration depth of visible light through thick tissue, limiting its use to target regions only a few millimeters deep. One way to enhance the range is to use invisible near-infrared (NIR) light within the optical window (700–1100nm) for biological tissues, extending the depth up to 1cm with no observable damage to the intervening tissue. We have demonstrated use of NIR-to-visible upconversion fluorescent nanoparticles (UCNPs), emitting visible fluorescence when excited by a NIR light at 980nm, as a nanotransducer for PDT to convert deep tissue-penetrating NIR light to visible light suitable for activating photosensitizers. The unique optical properties of UCNPs enable the upconversion wavelength to be tuned and matched to the activation absorption wavelength of the photosensitizer. At depths beyond 1cm, however, tissue remains inaccessible to light even within the NIR window, and this critical depth limitation renders existing phototherapy ineffective against most deep-seated cancers. We have demonstrated some new treatment modalities for deep-seated cancers based on UCNP hydrogel implants and miniaturized, wirelessly powered optoelectronic devices for light delivery to deep tissues.

Keywords: upconversion, fluorescent, nanoparticle, bioimaging, photodynamic therapy

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Authors: Chiung-Yun Chang, Po-Chou Chen, Jiun-Shiang Tzeng, Ka-Wai Mac, Chia-Chi Hsiao, Jo-Chi Jao

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This study aimed to measure R2* relaxation rates in the liver of New Zealand White (NZW) rabbits. R2* relaxation rate has been widely used in various hepatic diseases for iron overload by quantifying iron contents in liver. R2* relaxation rate is defined as the reciprocal of T2* relaxation time and mainly depends on the composition of tissue. Different tissues would have different R2* relaxation rates. The signal intensity decay in Magnetic resonance imaging (MRI) may be characterized by R2* relaxation rates. In this study, a 1.5T GE Signa HDxt whole body MR scanner equipped with an 8-channel high resolution knee coil was used to observe R2* values in NZW rabbit’s liver and muscle. Eight healthy NZW rabbits weighted 2 ~ 2.5 kg were recruited. After anesthesia using Zoletil 50 and Rompun 2% mixture, the abdomen of rabbit was landmarked at the center of knee coil to perform 3-plane localizer scan using fast spoiled gradient echo (FSPGR) pulse sequence. Afterward, multi-planar fast gradient echo (MFGR) scans were performed with 8 various echo times (TEs) (2/4/6/8/10/12/14/16 ms) to acquire images for R2* calculations. Regions of interest (ROIs) at liver and muscle were measured using Advantage workstation. Finally, the R2* was obtained by a linear regression of ln(SI) on TE. The results showed that the longer the echo time, the smaller the signal intensity. The R2* values of liver and muscle were 44.8  10.9 s-1 and 37.4  9.5 s-1, respectively. It implies that the iron concentration of liver is higher than that of muscle. In conclusion, R2* is correlated with iron contents in tissue. The correlations between R2* and iron content in NZW rabbit might be valuable for further exploration.

Keywords: liver, magnetic resonance imaging, muscle, R2* relaxation rate

Procedia PDF Downloads 418