Search results for: chest radiography

Authors: Sahar Heidary

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Radiography and radiotherapy have emerged as crucial pillars of modern medical practice, revolutionizing diagnostics and treatment for a myriad of health conditions. This abstract highlights the pivotal role of radiography and radiotherapy in favor of healthcare and society. Radiography, a non-invasive imaging technique, has significantly advanced medical diagnostics by enabling the visualization of internal structures and abnormalities within the human body. With the advent of digital radiography, clinicians can obtain high-resolution images promptly, leading to faster diagnoses and informed treatment decisions. Radiography plays a pivotal role in detecting fractures, tumors, infections, and various other conditions, allowing for timely interventions and improved patient outcomes. Moreover, its widespread accessibility and cost-effectiveness make it an indispensable tool in healthcare settings worldwide. On the other hand, radiotherapy, a branch of medical science that utilizes high-energy radiation, has become an integral component of cancer treatment and management. By precisely targeting and damaging cancerous cells, radiotherapy offers a potent strategy to control tumor growth and, in many cases, leads to cancer eradication. Additionally, radiotherapy is often used in combination with surgery and chemotherapy, providing a multifaceted approach to combat cancer comprehensively. The continuous advancements in radiotherapy techniques, such as intensity-modulated radiotherapy and stereotactic radiosurgery, have further improved treatment precision while minimizing damage to surrounding healthy tissues. Furthermore, radiography and radiotherapy have demonstrated their worth beyond oncology. Radiography is instrumental in guiding various medical procedures, including catheter placement, joint injections, and dental evaluations, reducing complications and enhancing procedural accuracy. On the other hand, radiotherapy finds applications in non-cancerous conditions like benign tumors, vascular malformations, and certain neurological disorders, offering therapeutic options for patients who may not benefit from traditional surgical interventions. In conclusion, radiography and radiotherapy stand as indispensable tools in modern medicine, driving transformative improvements in patient care and treatment outcomes. Their ability to diagnose, treat, and manage a wide array of medical conditions underscores their favor in medical practice. As technology continues to advance, radiography and radiotherapy will undoubtedly play an ever more significant role in shaping the future of healthcare, ultimately saving lives and enhancing the quality of life for countless individuals worldwide.

Keywords: radiology, radiotherapy, medical imaging, cancer treatment

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Authors: G. E. Okungbowa, H. O. Adams, S. E. Eze

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This study is on the estimation of adult patient doses for Chest X-ray diagnostic examinations of new admitted undergraduate students attending a tertiary institution health centre as part of their routine clearance and check up on admitted into the institution. A total of 531 newly admitted undergraduate students were recruited for this survey in the first quarter of 2016 (January to March, 2016). CALDOSE_X 5.0 software was used to compute the Entrance Surface Dose (ESD) and Effective Dose (ED); while the Statistical Package for Social Sciences (SPSS) version 21.0 was used to carry out the statistical analyses. The basic patients' data and exposure parameters required for the software are age, sex, examination type, projection posture, tube potential and current-time product. The mean Entrance Surface Dose and Effective Doses of the undergraduate students were calculated using the software, and the values were compared with existing literature and internationally established diagnostic reference levels. The mean ESD calculated is 0.29 mGy, and the mean effective dose is 0.04 mSv. The values of ESD and ED obtained are below the internationally established diagnostic reference levels, which could be attributed to good radiographic techniques employed during the chest X-ray procedure for these students.

Keywords: x-ray, dose, examination, chest

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Authors: Parisa Mansour

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Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19.

Keywords: chest, HRCT, covid-19, artificial intelligence, chest HRCT

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Authors: Slawomir Pilip, Michal Wasilewski, Daniel Celinski, Leszek Szpakowski, Grzegorz Michalak

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The aim of the study was to evaluate the effectiveness of cardiopulmonary resuscitation taken by Medical Emergency Teams (MET) at the place of an accident including the usage of mechanical chest compression systems. In the period of January-May 2017, there were 137 cases of a sudden cardiac arrest in a chosen region of Eastern Poland with 360.000 inhabitants. Medical records and questionnaires filled by METs were analysed to prove the effectiveness of cardiopulmonary resuscitations that were considered to be effective when an early indication of spontaneous circulation was provided and the patient was taken to hospital. A chest compression system used by METs was applied in 60 cases (Lucas3 - 34 patients; Auto Pulse - 24 patients). The effectiveness of cardiopulmonary resuscitation among patients who were employed a chest compression system was much higher (43,3%) than the manual cardiac massage (36,4%). Thus, the usage of Lucas3 chest compression system resulted in 47% while Auto Pulse was 33,3%. The average ambulance arrival time could have had a significant impact on the subsequent effectiveness of cardiopulmonary resuscitation in these cases. Ambulances equipped with Lucas3 reached the destination within 8 minutes, and those with Auto Pulse needed 12,1 minutes. Moreover, taking effective basic life support (BLS) by bystanders before the ambulance arrival was much more frequent for ambulances with Lucas3 than Auto Pulse. Therefore, the percentage of BLS among the group of patients who were employed Lucas3 by METs was 26,5%, and 20,8% for Auto Pulse. The total percentage of taking BLS by bystanders before the ambulance arrival resulted in 25% of patients who were later applied a chest compression system by METs. Not only was shockable cardiac rhythm obtained in 47% of these cases, but an early indication of spontaneous circulation was also provided in all these patients. Both Lucas3 and Auto Pulse were evaluated to be significantly useful in improving the effectiveness of cardiopulmonary resuscitation by 97% of Medical Emergency Teams. Therefore, implementation of chest compression systems essentially makes the cardiopulmonary resuscitation even more effective. The ambulance arrival time, taking successful BLS by bystanders before the ambulance arrival and the presence of shockable cardiac rhythm determine an early indication of spontaneous circulation among patients after a sudden cardiac arrest.

Keywords: cardiac arrest, effectiveness, mechanical chest compression systems, resuscitation

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Authors: Sepehr Moradi, Mehdi Asadi Rad

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The aim of this study is to evaluate and compare chest weight of pure and mixed races Kabood 30-day Pigeons to investigate about their sex, race, and some auxiliary variables. In this paper, 62 pieces of pigeons as 31 male and female pairs with equal age are studied randomly. A natural incubation was done from each pair. All produced chickens were slaughtered at 30 days age after 12 hours hunger. Then their chests were weighted by a scale with one gram precision. A covariance analysis was used since there were many auxiliary variables and unequal observations. SAS software was used for statistical analysis. Mean weight of chests in pure race (Kabood-Kabood) with 8 records, 123.8±32.3g and mixed races of Kabood-Namebar, Kabood-Parvazy, Kabood-Tizpar, Namebar-Kabood, Tizpar-Kabood, and Parvazi-Kabood with 8, 8, 6, 12, 10, and 10 records were 139.4±23.5, 7/122±23.8, 124.7±30.1, 50.3±29.3, 51.4±26.4, and 137±28.6 gr, respectively. Mean weight of 30-day chests in male and female sex were 87.3±2.5 and 82.7±2.6g, respectively. Difference chest weight of 30-day chests of Kabood-Kabood race with Kabood-Namebar, Kabood-Parvazi, Tizpar-Kabood, Kabood-Tizpar, Namebar-Kabood and Parvazi-Kabood mixed races was not significant. Effect of sex was also significant in 5% level (P<0.05), but mutual effect of sex and race was not significant. Auxiliary variable of father weight was significant in 1% level (p < 0.01), but auxiliary variable of mother weight was not significant. The results showed that most and least weights belonged to Kabood-Namebar and Namebar-Kabood.

Keywords: squab, Kabood race, 30-day chest weight, pigeons

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Authors: Maris Eugênia Dela Rosa, Ana Luiza Menegatti Pavan, Marcela De Oliveira, Diana Rodrigues De Pina, Luis Carlos Vulcano

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In medical veterinary as well as in human medicine, radiological study is essential for a safe diagnosis in clinical practice. Thus, the quality of radiographic image is crucial. In last year’s there has been an increasing substitution of image acquisition screen-film systems for computed radiology equipment (CR) without technical charts adequacy. Furthermore, to carry out a radiographic examination in veterinary patient is required human assistance for restraint this, which can compromise image quality by generating dose increasing to the animal, for Occupationally Exposed and also the increased cost to the institution. The image optimization procedure and construction of radiographic techniques are performed with the use of homogeneous phantoms. In this study, we sought to develop a homogeneous phantom of canine chest to be applied to the optimization of these images for the CR system. In carrying out the simulator was created a database with retrospectives chest images of computed tomography (CT) of the Veterinary Hospital of the Faculty of Veterinary Medicine and Animal Science - UNESP (FMVZ / Botucatu). Images were divided into four groups according to the animal weight employing classification by sizes proposed by Hoskins & Goldston. The thickness of biological tissues were quantified in a 80 animals, separated in groups of 20 animals according to their weights: (S) Small - equal to or less than 9.0 kg, (M) Medium - between 9.0 and 23.0 kg, (L) Large – between 23.1 and 40.0kg and (G) Giant – over 40.1 kg. Mean weight for group (S) was 6.5±2.0 kg, (M) 15.0±5.0 kg, (L) 32.0±5.5 kg and (G) 50.0 ±12.0 kg. An algorithm was developed in Matlab in order to classify and quantify biological tissues present in CT images and convert them in simulator materials. To classify tissues presents, the membership functions were created from the retrospective CT scans according to the type of tissue (adipose, muscle, bone trabecular or cortical and lung tissue). After conversion of the biologic tissue thickness in equivalent material thicknesses (acrylic simulating soft tissues, bone tissues simulated by aluminum and air to the lung) were obtained four different homogeneous phantoms, with (S) 5 cm of acrylic, 0,14 cm of aluminum and 1,8 cm of air; (M) 8,7 cm of acrylic, 0,2 cm of aluminum and 2,4 cm of air; (L) 10,6 cm of acrylic, 0,27 cm of aluminum and 3,1 cm of air and (G) 14,8 cm of acrylic, 0,33 cm of aluminum and 3,8 cm of air. The developed canine homogeneous phantom is a practical tool, which will be employed in future, works to optimize veterinary X-ray procedures.

Keywords: radiation protection, phantom, veterinary radiology, computed radiography

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

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Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: Prof. Ammal Mokhtar Metwally, Samia M. Sami, Nihad A. Ibrahim, Fatma A. Shaaban, Iman I. Salama

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Objectives: Reducing neonatal mortality by 2030 is still a challenging goal in developing countries. low birth weight (LBW) is a significant contributor to this, especially where weighing newborns is not possible routinely. The present study aimed to determine a simple, easy, reliable anthropometric measure(s) that can predict LBW) and neonatal mortality. Methods: A prospective cohort study of 570 babies born in districts of El Menia governorate, Egypt (where most deliveries occurred at home) was examined at birth. Newborn weight, length, head, chest, mid-arm, and thigh circumferences were measured. Follow up of the examined neonates took place during their first four weeks of life to report any mortalities. The most predictable anthropometric measures were determined using the statistical package of SPSS, and multiple Logistic regression analysis was performed.: Results: Head and chest circumferences with cut-off points < 33 cm and ≤ 31.5 cm, respectively, were the significant predictors for LBW. They carried the best combination of having the highest sensitivity (89.8 % & 86.4 %) and least false negative predictive value (1.4 % & 1.7 %). Chest circumference with a cut-off point ≤ 31.5 cm was the significant predictor for neonatal mortality with 83.3 % sensitivity and 0.43 % false negative predictive value. Conclusion: Using chest circumference with a cut-off point ≤ 31.5 cm is recommended as a single simple anthropometric measurement for the prediction of both LBW and neonatal mortality. The predicted measure could act as a substitute for weighting newborns in communities where scales to weigh them are not routinely available.

Keywords: low birth weight, neonatal mortality, anthropometric measures, practical screening

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Authors: Aicha Akrout, Amira Echtioui, Mohamed Ghorbel

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Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition.

Keywords: chest x-ray, lung diseases, transfer learning, pneumonia detection

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Naridchaya Aberdour, Joanna Kao, Anne Miller, Timothy Shore, Richard Maher, Zhixin Liu

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Background: COVID-19 has and continues to be a strain on healthcare globally, with the number of patients requiring hospitalization exceeding the level of medical support available in many countries. As chest x-rays are the primary respiratory radiological investigation, the Radiological Assessment of Lung Edema (RALE) score was used to quantify the extent of pulmonary infection on baseline imaging. Assessment of RALE score's reproducibility and associations with clinical outcome parameters were then evaluated to determine implications for patient management and prognosis. Methods: A retrospective study was performed with the inclusion of patients testing positive for COVID-19 on nasopharyngeal swab within a single Local Health District in Sydney, Australia and baseline x-ray imaging acquired between January to June 2020. Two independent Radiologists viewed the studies and calculated the RALE scores. Clinical outcome parameters were collected and statistical analysis was performed to assess RALE score reproducibility and possible associations with clinical outcomes. Results: A total of 78 patients met inclusion criteria with the age range of 4 to 91 years old. RALE score concordance between the two independent Radiologists was excellent (interclass correlation coefficient = 0.93, 95% CI = 0.88-0.95, p<0.005). Binomial logistics regression identified a positive correlation with hospital admission (1.87 OR, 95% CI= 1.3-2.6, p<0.005), oxygen requirement (1.48 OR, 95% CI= 1.2-1.8, p<0.005) and invasive ventilation (1.2 OR, 95% CI= 1.0-1.3, p<0.005) for each 1-point increase in RALE score. For each one year increased in age, there was a negative correlation with recovery (0.05 OR, 95% CI= 0.92-1.0, p<0.01). RALE scores above three were positively associated with hospitalization (Youden Index 0.61, sensitivity 0.73, specificity 0.89) and above six were positively associated with ICU admission (Youden Index 0.67, sensitivity 0.91, specificity 0.78). Conclusion: The RALE score can be used as a surrogate to quantify the extent of COVID-19 infection and has an excellent inter-observer agreement. The RALE score could be used to prognosticate and identify patients at high risk of deterioration. Threshold values may also be applied to predict the likelihood of hospital and ICU admission.

Keywords: chest radiography, coronavirus, COVID-19, RALE score

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Authors: Abdelrahman Mohamed Abdelrahman

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Canopic jars are one of the vessels of funerary nature used by the ancient Egyptian in mummification process that were used to save the viscera of the mummified body after being extracted from the body and treated. Canopic jars are made of several types of materials like Limestone, Alabaster, and Pottery. The studied canopic jar dates back to Late period, located in the Grand Egyptian Museum (GEM), Giza, Egypt. This jar carved from limestone with carved hieroglyphic inscriptions, and it filled and closed by mortar from inside. Some aspects of damage appeared in the jar, such as dust, dirts, classification, wide crack, weakness of limestone. In this study, we used documentation and investigation modern techniques to document and examine the jar. 3D scanning and X-ray Radiography imaging used in applied study. X-ray imaging showed that the mortar was placed at a time when the jar contained probably viscera where the mortar appeared that not reach up to the base of the inner jar. Through the three-dimensional photography, the jar was documented, and we have 3D model of the jar, and now we have the ability through the computer to see any part of the jar in all its details. After that, conservation procedures have been applied with high accuracy to conserve the jar, including mechanical, wet, and chemical cleaning, filling wide crack in the body of the jar using mortar consisting of calcium carbonate powder mixing with primal E330 S, and consolidation, so the limestone became strong after using paraloid B72 2% concentrate as a consolidate material.

Keywords: vessel, limestone, canopic jar, mortar, 3D scanning, X-ray radiography

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Authors: Hassan Almoslim

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Background: The machine resistance training is an exercise that uses the equipment as loads to strengthen and condition the musculoskeletal system and improving muscle tone. The machine resistance training is easy to use, allow the individual to train with heavier weights without assistance, useful for beginners and elderly populations and specific muscle groups. Purpose: The purpose of this study was to examine the impact of nine weeks of machine resistance training on maximum strength among lean and normal weight male college students. Method: Thirty-six male college students aged between 19 and 21 years from King Fahd University of petroleum & minerals participated in the study. The subjects were divided into two an equal groups called Lean Group (LG, n = 18) and Normal Weight Group (NWG, n = 18). The subjects whose body mass index (BMI) is less than 18.5 kg / m2 is considered lean and who is between 18.5 to 24.9 kg / m2 is normal weight. Both groups performed machine resistance training nine weeks, twice per week for 40 min per training session. The strength measurements, chest press, leg press and abdomen exercises were performed before and after the training period. 1RM test was used to determine the maximum strength of all subjects. The training program consisted of several resistance machines such as leg press, abdomen, chest press, pulldown, seated row, calf raises, leg extension, leg curls and back extension. The data were analyzed using independent t-test (to compare mean differences) and paired t-test. The level of significance was set at 0.05. Results: No change was (P ˃ 0.05) observed in all body composition variables between groups after training. In chest press, the NWG recorded a significantly greater mean different value than the LG (19.33 ± 7.78 vs. 13.88 ± 5.77 kg, respectively, P ˂ 0.023). In leg press and abdomen exercises, both groups revealed similar mean different values (P ˃ 0.05). When the post-test was compared with the pre-test, the NWG showed significant increases in the chest press by 47% (from 41.16 ± 12.41 to 60.49 ± 11.58 kg, P ˂ 001), abdomen by 34% (from 45.46 ± 6.97 to 61.06 ± 6.45 kg, P ˂ 0.001) and leg press by 23.6% (from 85.27 ± 15.94 to 105.48 ± 21.59 kg, P ˂ 0.001). The LG also illustrated significant increases by 42.6% in the chest press (from 32.58 ± 7.36 to 46.47 ± 8.93 kg, P ˂ 0.001), the abdomen by 28.5% (from 38.50 ± 7.84 to 49.50 ± 7.88 kg, P ˂ 0.001) and the leg press by 30.8% (from 70.2 ± 20.57 to 92.01 ± 22.83 kg, P ˂ 0.001). Conclusion: It was concluded that the lean and the normal weight male college students can benefit from the machine resistance-training program remarkably.

Keywords: body composition, lean, machine resistance training, normal weight

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Authors: Rezvan Hosseinian

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Aim: Systemic sclerosis (SSc) is a chronic connective tissue disease with the clinical hallmark of skin thickening and tethering. The correlation of musculoskeletal features with other parameters should be considered in SSc patients. Methods: We reviewed the records of all patients who had more than one visit and standard anteroposterior radiography of hand. We used univariate analysis, and factors with p<0.05 were included in logistic regression to find out dependent factors. Results: Overall, 180 SSc patients were enrolled in our study, 161 (89.4%) of whom were women. The median age (IQR) was 47.0 years (16), and 52% had a diffuse subtype of the disease. In multivariate analysis, tendon friction rubs (TFRs) were associated with the presence of calcinosis, muscle tenderness, and flexion contracture (FC) on physical examination (p<0.05). Arthritis showed no differences in the two subtypes of the disease (p=0.98), and in multivariate analysis, there were no correlations between radiographic arthritis and serological and clinical features. The radiographic results indicated that disease duration correlated with joint erosion, acro-osteolysis, resorption of the distal ulna, calcinosis and radiologic FC (p< 0.05). Acro-osteolysis was more frequent in the dcSSc subtype, TFRs, and anti-TOPO I antibody. Radiologic FC showed an association with skin score, calcinosis and haematocrit <30% (p<0.05). Joint flexion on radiography was associated with disease duration, modified Rodnan skin score, calcinosis, and low hematocrit (P<0.01). Conclusion: Disease duration was a main dependent factor for developing joint erosion, acro-osteolysis, bone resorption, calcinosis, and flexion contracture on hand radiography. Acro-osteolysis presented in the severe form of the disease. Acro-osteolysis was the only dependent variable associated with bone demineralization.

Keywords: disease subsets, hand radiography, joint erosion, sclerosis

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Authors: Saad S. Alrwashdeh, Henning Markötter, Handri Ammari, Jan Haußmann, Tobias Arlt, Joachim Scholta, Ingo Manke

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In this investigation, synchrotron X-ray imaging is used to study water transport inside polymer electrolyte membrane fuel cells. Two measurement techniques are used, namely in-situ radiography and quasi-in-situ tomography combining together in order to reveal the relationship between the structures of the microporous layers (MPLs) and the gas diffusion layers (GDLs), the operation temperature and the water flow. The developed cell is equipped with a thick GDL and a high back pressure MPL. It is found that these modifications strongly influence the overall water transport in the whole adjacent GDM.

Keywords: polymer electrolyte membrane fuel cell, microporous layer, water transport, radiography, tomography

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Authors: Kaouther Bergaui, Nafaa Reguigui, Charles Gary

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Characterization and the applications of deuterium-deuterium (DD) neutron generator developed by Adelphie technology and acquired by the National Centre of Nuclear Science and Technology (NCNST) were presented in this work. We study the performance of the neutron generator in terms of neutron yield, production efficiency, and the ionic current as a function of the acceleration voltage at various RF powers. We provide the design and optimization of the PGNAA chamber and thus give insight into the capabilities of the planned PGNAA facility. Additional non-destructive techniques were studied employing the DD neutron generator, such as PGNAA and neutron radiography: The PGNAA is used for determining the concentration of 10B in Si and SiO2 matrices by using a germanium detector HPGe and the results obtained are compared with PGNAA system using a Sodium Iodide detector (NaI (Tl)); Neutron radiography facility was tested and simulated, using a camera device CCD and simulated by the Monte Carlo code; and the explosive detection system (EDS) also simulated using the Monte Carlo code. The study allows us to show that the new models of DD neutron generators are feasible and that superior-quality neutron beams could be produced and used for various applications. The feasibility of Boron neutron capture therapy (BNCT) for cancer treatment using a neutron generator was assessed by optimizing Beam Shaping Assembly (BSA) on a phantom using Monte-Carlo (MCNP6) simulations.

Keywords: neutron generator deuterium-deuterium, Monte Carlo method, radiation, neutron flux, neutron activation analysis, born, neutron radiography, explosive detection, BNCT

Procedia PDF Downloads 193

Authors: M. Bolacalı, Y. Öztürk, O. Yılmaz, M. Küçük, M. A. Karslı

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The aim of the study was to determine various body measurements from the birth to the 30-day age of Boer x Hair goats F1 crossbred kids and pure Hair goat kids raised in Van in Eastern Anatolia region, and reveal factors such as the effects of year, dame body weight, genotype, dame age, birth type and sex on this parameter. 49 kids born in 2012 and 76 kids born in 2014 were utilized in the study. In the statistical analysis of various body measurements data was performed using the General Lineer Model procedure in SPSS software. Duncan's multiple range test was used for multiple comparisons. Boer x Hair goats F1 crossbred kids and pure Hair goat kids from various body measurements cidago height, body length, chest length, chest depth, chest circumference, circumference of leg, cannon bone circumference, chest width were determinated in general respectively 29.90 and 27.88 cm; 29.49 and 27.93 cm; 17.28 and 16.68 cm; 13.34 and 12.82 cm; 31.74 and 29.85 cm; 28.43 and 23.95 cm; 5.41 and 5.15 cm; 8.71 and 7.63 cm at birth, respectively; 35.01 and 32.98 cm; 35.20 and 33.30 cm; 18.82 and 18.17 cm; 15.64 and 14.83 cm; 39.08 and 37.30 cm; 34.29 and 29.25 cm; 5.80 and 5.42 cm; 9.87 and 8.85 cm at 30 days age, respectively. Among factors affecting cidago height in this study, the effect of dame body weight and sex were not significant, but genotype, dame age and birth type were significant (P < 0,05 and P < 0,01) at birth; dame body weight effect of the cidago height was not significant, but the effect of genotype, birth type, of dame age and sex were significant (P < 0.05, P < 0.05 and P<0.001) at 30-day age. The effect of genotype and sex of body length were not significant, but dam age, dame body weight and birth type were significant (P < 0.05, P < 0.05 and P<0.001, respectively) at birth; the effect of sex to body length was not significant, but genotype, dame age, dame body weight and birth type were significant (P < 0.01, P < 0.05, P < 0.05 and P < 0.001, respectively) at 30-day age. While circumference of leg was insignificant the effect of dame age and sex, genotype, dame body weight and type of the birth were significant (P < 0.001, P < 0.05 and P < 0.001) at birth; the circumstance of leg at 30-day age was found to be important the effect of examined other factors except for sex (P < 0.05 and P < 0.001). The obtained results, when considered in terms of a variety of body sizes, from birth to 30-day age growth period, showed that the kids of Boer x Hair Goat F1 hybrids have higher values than the kids of Hair Goats.

Keywords: Boer x hair goat F1 crossbred, hair goat, body measurements, cidago height

Procedia PDF Downloads 349

Authors: N. Noroozian, M. Halim, B. Holloway

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Computed Tomography (CT) has become the largest source of radiation exposure in modern countries however, recent technological advances have created new methods to reduce dose without negatively affecting image quality. SAFIRE has emerged as a new software package which utilizes full raw data projections for iterative reconstruction, thereby allowing for lower CT dose to be used. this audit was performed to compare CT doses in certain examinations before and after the introduction of SAFIRE at our Radiology department which showed CT doses were significantly lower using SAFIRE compared with pre-SAFIRE software at SAFIRE 3 setting for the following studies:CSKUH Unenhanced brain scans (-20.9%), CABPEC Abdomen and pelvis with contrast (-21.5%), CCHAPC Chest with contrast (-24.4%), CCHAPC Abdomen and pelvis with contrast (-16.1%), CCHAPC Total chest, abdomen and pelvis (-18.7%).

Keywords: dose reduction, iterative reconstruction, low dose CT techniques, SAFIRE

Procedia PDF Downloads 285

Authors: S. Djaziri, F. Sket, A. Hynowska, S. Milenkovic

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The use of Fe-Al based intermetallics as an alternative to Cr/Ni based stainless steels is very promising for industrial applications that use critical raw materials parts under extreme conditions. However, the development of advanced Fe-Al based intermetallics with appropriate mechanical properties presents several challenges that involve appropriate processing and microstructure control. A processing strategy is being developed which aims at producing a net-shape porous Fe-based preform that is infiltrated with molten Al or Al-alloy. In the present work, porous Fe-based preforms produced by two different methods (selective laser melting (SLM) and Kochanek-process (KE)) are studied during infiltration with molten aluminum. In the objective to elucidate the mechanisms underlying the formation of Fe-Al intermetallic phases during infiltration, an in-house furnace has been designed for in situ observation of infiltration at synchrotron facilities combining x-ray radiography (XR) and x-ray diffraction (XRD) techniques. The feasibility of this approach has been demonstrated, and information about the melt flow front propagation has been obtained. In addition, reactive infiltration has been achieved where a bi-phased intermetallic layer has been identified to be formed between the solid Fe and liquid Al. In particular, a tongue-like Fe₂Al₅ phase adhering to the Fe and a needle-like Fe₄Al₁₃ phase adhering to the Al were observed. The growth of the intermetallic compound was found to be dependent on the temperature gradient present along the preform as well as on the reaction time which will be discussed in view of the different obtained results.

Keywords: combined synchrotron radiography and diffraction, Fe-Al intermetallic compounds, in-situ molten Al infiltration, porous solid Fe preforms

Procedia PDF Downloads 226

Authors: Ram Sharan Mehta, Gayanandra Malla, Anita Gurung, Anu Aryal, Divya Labh, Hricha Neupane

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Objectives: Lack of resuscitation skills of nurses and doctors in basic life support (BLS) and advanced life support (ALS) has been identified as a contributing factor to poor outcomes of cardiac arrest victims. The objective of this study was to examine retention of life support measures (BLS/ALS) knowledge and skills of nurses following education intervention programme. Materials and Methods: Pre-experimental research design was used to conduct the study among the nurses working in medical units of B.P Koirala Institute of Health Sciences, where CPR is very commonly performed. Using convenient sampling technique total of 20 nurses agreed to participate and give consent were included in the study. The theoretical, demonstration and re-demonstration were arranged involving the trained doctors and nurses during the three hours educational session. Post-test was carried out after two week of education intervention programme. The 2010 BLS & ALS guidelines were used as guide for the study contents. The collected data were analyzed using SPSS-15 software. Results: It was found that there is significant increase in knowledge after education intervention in the components of life support measures (BLS/ALS) i.e. ratio of chest compression to ventilation in BLS (P=0.001), correct sequence of CPR (p <0.001), rate of chest compression in ALS (P=0.001), the depth of chest compression in adult CPR (p<0.001), and position of chest compression in CPR (P=0.016). Nurses were well appreciated the programme and request to continue in future for all the nurses. Conclusions: At recent BLS/ALS courses (2010), a significant number of nurses remain without any such training. Action is needed to ensure all nurses receive BLS training and practice this skill regularly in order to retain their knowledge.

Keywords: pre-experimental, basic and advance life support, nurses, sampling technique

Procedia PDF Downloads 254

Authors: Sean Yao Zu Kong, Khong Yik Chew

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Introduction: We described a case report of the successful use of advanced surgical techniques in a patient with recurrent breast cancer who underwent a wide resection including the hemi-sternum, clavicle, multiple ribs, and a lobe of the lung due to tumor involvement. This extensive resection exposed critical structures, requiring a creative approach to reconstruction. To address this complex chest wall reconstruction, a free fibula flap and a 4-zone rectus abdominis musculocutaneous flap were successfully utilized. The use of a free vascularized bone flap allowed for rapid osteointegration and resistance against osteoradionecrosis after adjuvant radiation, while a four-zone tram flap allowed for reconstruction of both the chest wall and breast mound. Although limited recipient vessels made free flaps challenging, the free fibula flap served as both a bony reconstruction and vascular conduit, supercharged with the distal peroneal artery and veins of the peroneal artery from the fibula graft. Our approach highlights the potential of advanced surgical techniques to improve outcomes in complex cases of chest wall reconstruction in patients with recurrent breast cancer, which is becoming increasingly relevant as breast cancer incidence rates increases. Case presentation: This report describes a successful reconstruction of a patient with recurrent breast cancer who required extensive resection, including the anterior chest wall, clavicle, and sternoclavicular joint. Challenges arose due to the loss of accessory muscles and the non-rigid rib cage, which could lead to compromised ventilation and instability. A free fibula osteocutaneous flap and a four-zone TRAM flap with vascular supercharging were utilized to achieve long-term stability and function. The patient has since fully recovered, and during the review, both flaps remained viable, and chest mound reconstruction was satisfactory. A planned nipple/areolar reconstruction was offered pending the patient’s decision after adjuvant radiotherapy. Conclusion: In conclusion, this case report highlights the successful use of innovative surgical techniques in addressing a complex case of recurrent breast cancer requiring extensive resection and radical reconstruction. Our approach, utilized a combination of a free fibula flap and a 4-zone rectus abdominis musculocutaneous flap, demonstrates the potential for advanced techniques in chest wall reconstruction to minimize complications and ensure long-term stability and function. As the incidence of breast cancer continues to rise, it is crucial that healthcare professionals explore and utilize innovative techniques to improve patient outcomes and quality of life.

Keywords: free fibula flap, rectus abdominis musculocutaneous flap, post-adjuvant radiotherapy, reconstructive surgery, malignancy

Procedia PDF Downloads 62

Authors: Jaemoon Lim

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To construct the lumped spring-mass model considering the occupants for the offset frontal crash, the SISAME software and the NHTSA test data were used. The data on 56 kph 40% offset frontal vehicle to deformable barrier crash test of a MY2007 Mazda 6 4-door sedan were obtained from NHTSA test database. The overall behaviors of B-pillar and engine of simulation models agreed very well with the test data. The trends of accelerations at the driver and passenger head were similar but big differences in peak values. The differences of peak values caused the large errors of the HIC36 and 3 ms chest g’s. To predict well the behaviors of dummies, the spring-mass model for the offset frontal crash needs to be improved.

Keywords: chest g’s, HIC36, lumped spring-mass model, offset frontal impact, SISAME

Procedia PDF Downloads 457

Authors: Eunhye Cho, Hyuk-Hoon Kim, Sieun Lee, Minjung Kathy Chae

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Introduction: I-gel is a commonly used supraglottic advanced airway device in prehospital out-of-hospital cardiac arrest (OHCA) allowing for minimal interruption of continuous chest compression. However, previous studies have shown that prehospital supraglottic airway had inferior neurologic outcomes and survival compared to no advanced prehospital airway with conventional bag mask ventilation. We hypothesize that continuous compression with i-gel as an advanced airway may cause insufficient ventilation compared to 30:2 chest compression with conventional BVM. Therefore, we investigated the ventilation efficacy of i-gel with the initial arterial blood gas analysis in OHCA patients visiting our ER. Material and Method: Demographics, arrest parameters including i-gel insertion, initial arterial blood gas analysis was retrospectively analysed for 119 transported OHCA patients that visited our ER. Linear regression was done to investigate the association with i-gel insertion and initial pCO2 as a surrogate of prehospital ventilation. Result: A total of 52 patients were analysed for the study. Of the patients who visited the ER during OHCA, 24 patients had i-gel insertion and 28 patients had BVM as airway management in the prehospital phase. Prehospital i-gel insertion was associated with the initial pCO2 level (B coefficient 29.9, SE 10.1, p<0.01) after adjusting for bystander CPR, cardiogenic cause of arrest, EMS call to arrival. Conclusion: Despite many limitations to the study, prehospital insertion of i-gel was associated with high initial pCO2 values in OHCA patients visiting our ER, possibly indicating insufficient ventilation with prehospital i-gel as an advanced airway and continuous chest compressions.

Keywords: arrest, I-gel, prehospital, ventilation

Procedia PDF Downloads 335

Authors: Adenike O. Olatunji-Akioye, Emmanual B Farayola

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In order to improve the animal protein recommended daily intake of Nigerians, there is an upsurge in breeding of hitherto shunned food animals one of which is the rabbit. Radiography and ultrasonography are tools for diagnosing disease and evaluating the anatomical architecture of parts of the body non-invasively. As the rabbit is becoming a more important food animal, to achieve improved breeding of these animals, the best of the species form a breeding stock and will usually depend on breeding soundness which may be evaluated by assessment of the male reproductive organs by these tools. Four male intact rabbits weighing between 1.2 to 1.5 kg were acquired and acclimatized for 2 weeks. Dorsoventral views of the testes were acquired using a digital radiographic machine and a 5 MHz portable ultrasound scanner was used to acquire images of the testes in longitudinal, sagittal and transverse planes. Radiographic images acquired revealed soft tissue images of the testes in all rabbits. The testes lie in individual scrotal sacs sides on both sides of the midline at the level of the caudal vertebrae and thus are superimposed by caudal vertebrae and the caudal limits of the pelvic girdle. The ultrasonographic images revealed mostly homogenously hypoechogenic testes and a hyperechogenic mediastinum testis. The dorsal and ventral poles of the testes were heterogeneously hypoechogenic and correspond to the epididymis and spermatic cord. The rabbit is unique in the ability to retract the testes particularly when stressed and so careful and stressless handling during the procedures is of paramount importance. The imaging of rabbit testes can be safely done using both imaging methods but ultrasonography is a better method of assessment and evaluation of soundness for breeding.

Keywords: breeding soundness, rabbit, radiography, ultrasonography

Procedia PDF Downloads 131

Authors: Hannah Nagel, Hayley Lang, Albert Sole Guitart, Natasha Lean, Rachel Allavena, Cleide Sprohnie-Barrera, Alex Young

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Aggressive neoplasia of the hoof is a rare occurrence in horses and has been only sporadically described in the literature. In the few cases reported intra-hoof wall, aggressive neoplasia has been documented radiographically and has been described with variable imaging characteristics. These include a well-defined osteolytic area, a smoothly outlined semi-circular defect, an extensive draining tract beneath the hoof wall, as well as an additional large area of osteolysis or an extensive central lytic region. A 20-year-old Quarterhorse gelding and a 10-year-old Thoroughbred gelding were both presented for chronic reoccurring lameness in the left forelimb and left hindlimb, respectively. Both of the cases displayed radiographic lesions that have been previously described but also displayed osteoproliferative expansile regions of additional bone formation. Changes associated with hoof neoplasia are often non-specific due to the nature and capacity of bone to react to pathological insult, which is either to proliferate or be absorbed. Both cases depict and describe imaging findings seen on radiography, contrast radiography, computed tomography, and magnetic resonance imaging before reaching a histological diagnosis of malignant melanoma and squamous cell carcinoma. Although aggressive hoof wall neoplasia is rare, there are some imaging features which may raise our index of suspicion for an aggressive hoof wall lesion. This case report documents two horses with similar imaging findings who underwent multiple assessments, surgical interventions, and imaging modalities with a final diagnosis of malignant neoplasia.

Keywords: horse, hoof, imaging, radiography, neoplasia

Procedia PDF Downloads 131

Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

Procedia PDF Downloads 43

Authors: Vandna Raghuvanshi, Vikrant Thakur, Anupam Jhobta

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Objective: To design HRCT criterion to forecast the threat of pulmonary tuberculosis. Material and methods: This was a prospective study of 69 patients with clinical suspicion of pulmonary tuberculosis. We studied their medical characteristics, numerous separate HRCT-results, and a combination of HRCT findings to foresee the danger for PTB by utilizing univariate and multivariate investigation. Temporary HRCT diagnostic criteria were planned in view of these outcomes to find out the risk of PTB and tested these criteria on our patients. Results: The results of HRCT chest were analyzed, and Rank was given from 1 to 4 according to the HRCT chest findings. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. Rank 1: Highly suspected PTB. Rank 2: Probable PTB Rank 3: Nonspecific or difficult to differentiate from other diseases Rank 4: Other suspected diseases • Rank 1 (Highly suspected TB) was present in 22 (31.9%) patients, all of them finally diagnosed to have pulmonary tuberculosis. The sensitivity, specificity, and negative likelihood ratio for RANK 1 on HRCT chest was 53.6%, 100%, and 0.43, respectively. • Rank 2 (Probable TB) was present in 13 patients, out of which 12 were tubercular, and 1 was non-tubercular. • The sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of the combination of Rank 1 and Rank 2 was 82.9%, 96.4%, 23.22, and 0.18, respectively. • Rank 3 (Non-specific TB) was present in 25 patients, and out of these, 7 were tubercular, and 18 were non-tubercular. • When all these 3 ranks were considered together, the sensitivity approached 100% however, the specificity reduced to 35.7%. The positive likelihood ratio and negative likelihood ratio were 1.56 and 0, respectively. • Rank 4 (Other specific findings) was given to 9 patients, and all of these were non-tubercular. Conclusion: HRCT is useful in selecting individuals with greater chances of pulmonary tuberculosis.

Keywords: pulmonary, tuberculosis, multivariate, HRCT

Procedia PDF Downloads 172

Authors: Saria Almarzook, Monika Reissmann, Gudrun Brockmann

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Due to its history, occurrence in different ecosystems and diverse using, the modern horse (Equus caballus) shows large variability in size, appearance, behavior and habits. At all times, breeders try to create groups (breeds, strains) representing high homology but showing clear differences in comparison to other groups. A great interest of analyzing phenotypic and genetic traits looking for real diversity and genetic uniqueness existents for Arabian horses in Syria. 90 Arabian horses from governmental research center of Arabian horses in Damascus were included. The horses represent three strains (Kahlawi, Saklawi, Hamdani) originated from different geographical zones. They were raised on the same farm, under stable conditions. Twelve phenotypic traits were measured: wither height (WH), croup width (CW), croup height (CH), neck girth (NG), thorax girth (TG), chest girth (ChG), chest depth (ChD), chest width (ChW), back line length (BLL), body length (BL), fore cannon length (FCL) and hind cannon length (HCL). The horses were divided into groups according to age (less than 2 years, 2-4 years, 4-9 years, over 9 years) and to sex (male, female). The statistical analyzes show that age has significant influence of WH while the strain has only a very limited effect. On CW, NG, BLL, FCL and HCL, there is only a significant influence of sex. Age has significant effect on CH and BL. All sources of classes have a significant effect on TG, ChG, ChD and ChW. Strain has a significant effect on the BL. These results provide first information for real biodiversity in and between the strains and can be used to develop the breeding work in the Arabian horse breed.

Keywords: Arabian horse, phenotypic traits, strains, Syria

Procedia PDF Downloads 391