Search results for: tumour imaging

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

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Authors: Abraham J. Rizkalla, Tristan D. Yan

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Atrial myxoma is the most common primary cardiac tumor, and can result in cardiac failure secondary to obstruction, or systemic embolism due to fragmentation. Traditionally, excision of atrial an myxoma has been performed through median sternotomy, however the robotic approach offers several advantages including less pain, improved cosmesis, and faster recovery. Here, we highlight the less well recognized advantages and technical aspects to robotic myxoma resection. This video-presentation demonstrates the resection of a papillary subtype left atrial myxoma using the DaVinci© Xi surgical robot. The 10x magnification and 3D vision allows for the interface between the tumor and the interatrial septum to be accurately dissected, without the need to patch the interatrial septum. Several techniques to avoid tumor fragmentation and embolization are demonstrated throughout the procedure. The tumor was completely excised with clear margins. There was no atrial septal defect or mitral valve injury on post operative transesophageal echocardiography. The patient was discharged home on the fourth post-operative day. This video-presentation highlights the advantages of the robotic approach in atrial myxoma resection compared with sternotomy, as well as emphasizing several technical considerations to avoid potential complications.

Keywords: cardiac surgery, left atrial myxoma, cardiac tumour, robotic resection

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Authors: L. José, S. Vieira, E. Melo, A. R. Pinheiro

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Objectives: This study aims to characterize the stroke profile and the health care provided for people with a stroke in Luanda, Angola. Methods: A prospective longitudinal study was conducted at two Health centers, from March to November 2023, enrolling stroke patients. Data was gathered using a survey created by the researchers and validated by a health panel of experts from Angola. The analysis focused on demographic and stroke characteristics, as well as the care provided. Ethical approval and informed consent were obtained. Results: Preliminary results of a total of 186 patients are described, 122 from a Central Acute Care Hospital, with a mean age of 51.3±14.35 years old, a BMI of 26.7±4.15 kg/m2, 41% male, and 64 patients from a Rehabilitation Center, with 55.6±11.55 years old, a BMI of 27.0±3.8 kg/m2, 53% male. Ischemic stroke was reported as the most representative type in both centers (71.3% and 70.3%, respectively), though 100% of patients had no imaging diagnosis confirmation, neither data about the subtype was given. For patients admitted to the Hospital, discharge occurred before rehabilitation, and no follow-up was possible. No rehabilitation care was delivered in the first 7 days after the stroke. In the Rehabilitation Center, patient’s rehabilitation started in the late subacute phase, after a mean of 171.8±11.5 days. Conclusions: Stroke diagnosis lacks imaging confirmation, which is decisive for proper treatment, and rehabilitation starts during the late subacute phase, which is too late considering the international guidelines and the best window of opportunity for neuroplasticity and recovery. These results highlight the urgent need for the definition of Stroke-directed Health Care Policies in Angola.

Keywords: stroke, personalized health care, functional recovery, quality of life, health policies

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Authors: Julia Wimmers-Klick

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At the Canadian University of British Columbia's Faculty of Medicine, anatomy has traditionally been taught through a combination of lectures and dissection labs in the first two years, with radiology taught separately through lectures and online modules. However, this separation may leave students underprepared for medical practice, as medical imaging is essential for diagnosing anatomical and pathological conditions. To address this, a pilot project was initiated aimed at integrating radiological imaging into anatomy dissection labs from day one of medical school. The incorporated radiological images correlated with the current dissection areas. Additional stations were added within the lab, tailored to the specific content being covered. These stations focused on bones, and quiz questions, along with light-box exercises using radiographs, CT scans, and MRIs provided by the radiology department. The images used were free of pathologies. Examples of these will be presented in the poster. Feedback from short interviews with students and instructors has been positive, particularly among second-year students who appreciated the integration compared to their first-year experience. This low-budget approach was easy to implement but faced challenges, as lab instructors were not radiologists and occasionally struggled to answer students' questions. Instructors expressed a desire for basic training or a refresher course in radiology image reading, particularly focused on identifying healthy landmarks. Overall, all participants agreed that integrating radiology with anatomy reinforces learning during dissection, enhancing students' understanding and preparation for clinical practice.

Keywords: quality improvement, radiology education, anatomy education, integration

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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: 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: Ghoul Rachid Brahim, Trad Khodja Rafik

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Vertebral localization of the hydatid cyst is a severe form of bone hydatidosis, is a parasitic infection caused by the larval forms of the tapeworms Echinococcus granulosus, The disease is slowly remaining silent (a long incubation period) which may explain why this pathology is often discovered at the stage of neurological complications. The objective of this study is to recall the clinical and radiological aspects of this condition and the importance of early diagnosis and appropriate management. We report a study of 5 patients with vertebral hydatidosis, four men and one woman, four (04) patients operated in the emergency setting for spinal cord compression (decompression by wide laminectomy with evacuation of intra and extra canal vesicles).Albendazole-based medical treatment is instituted in all patients. Results: The evolution was favorable for three patients, the other two patients reoperated for a local recurrence. Conclusion: Vertebral hydatidosis is a rare condition with a poor prognosis due to the risk of neurological damage, the infiltrating nature of bone lesions, the frequency of relapses and therapeutic difficulties. The only curative method remains surgery, which must aim for complete and large excision of the lesions as if it were a “malignant tumour”.

Keywords: hydatidosis, Echinococcosis granulosus, hydatid cyst, spinal cord compression, laminectomy

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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

Procedia PDF Downloads 63

Authors: Cecilia Moreira, Rita Paiva, Daniela Macedo, Leonor Ribeiro, Isabel Fernandes, Luis Costa

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Background: Head and neck paragangliomas are a rare group of tumors with a large spectrum of clinical manifestations. The approach to evaluate and treat these lesions has evolved over the last years. Surgery was the standard for the approach of these patients, but nowadays new techniques of imaging and radiation therapy changed that paradigm. Despite advances in treating, the growth potential and clinical outcome of individual cases remain largely unpredictable. Objectives: Characterization of our institutional experience with clinical management of these tumors. Methods: This was a cross-sectional study of patients followed in our institution between 01 January and 31 December 2017 with paragangliomas of the head and neck and cranial base. Data on tumor location, catecholamine levels, and specific imaging modalities employed in diagnostic workup, treatment modality, tumor control and recurrence, complications of treatment and hereditary status were collected and summarized. Results: A total of four female patients were followed between 01 January and 31 December 2017 in our institution. The mean age of our cohort was 53 (± 16.1) years. The primary locations were at the level of the tympanic jug (n=2, 50%) and carotid body (n=2, 50%), and only one of the tumors of the carotid body presented pulmonary metastasis at the time of diagnosis. None of the lesions were catecholamine-secreting. Two patients underwent genetic testing, with no mutations identified. The initial clinical presentation was variable highlighting the decrease of visual acuity and headache as symptoms present in all patients. In one of the cases, loss of all teeth of the lower jaw was the presenting symptomatology. Observation with serial imaging, surgical extirpation, radiation, and stereotactic radiosurgery were employed as treatment approaches according to anatomical location and resectability of lesions. As post-therapeutic sequels the persistence of tinnitus and disabling pain stands out, presenting one of the patients neuralgia of the glossopharyngeal. Currently, all patients are under regular surveillance with a median follow up of 10 months. Conclusion: Ultimately, clinical management of these tumors remains challenging owing to heterogeneity in clinical presentation, the existence of multiple treatment alternatives, and potential to cause serious detriment to critical functions and consequently interference with the quality of life of the patients.

Keywords: clinical outcomes, head and neck, management, paragangliomas

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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: Umedov Mekhroz, Griaznova Svetlana

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In connection with the growth of oncological diseases, the design of centers for diagnostics and the production of radiopharmaceuticals is the most relevant area of healthcare facilities. The design of new nuclear medicine centers should be carried out from the standpoint of solving the following tasks: the availability of medical care, functionality, environmental friendliness, sustainable development, improving the safety of drugs, the use of which requires special care, reducing the rate of environmental pollution, ensuring comfortable conditions for the internal microclimate, adaptability. The purpose of this article is to substantiate architectural and planning solutions, formulate recommendations and principles for the design of nuclear medicine centers and determine the connections between the production and medical functions of a building. The advantages of combining the production of radiopharmaceuticals and the department of medical care: less radiation activity is accumulated, the cost of the final product is lower, and there is no need to hire a transport company with a special license for transportation. A medical imaging department is a structural unit of a medical institution in which diagnostic procedures are carried out in order to gain an idea of the internal structure of various organs of the body for clinical analysis. Depending on the needs of a particular institution, the department may include various rooms that provide medical imaging using radiography, ultrasound diagnostics, and the phenomenon of nuclear magnetic resonance. The production of radiopharmaceuticals is an object intended for the production of a pharmaceutical substance containing a radionuclide and intended for introduction into the human body or laboratory animal for the purpose of diagnosis, evaluation of the effectiveness of treatment, or for biomedical research. The research methodology includes the following subjects: study and generalization of international experience in scientific research, literature, standards, teaching aids, and design materials on the topic of research; An integrated approach to the study of existing international experience of PET / CT scan centers and the production of radiopharmaceuticals; Elaboration of graphical analysis and diagrams based on the system analysis of the processed information; Identification of methods and principles of functional zoning of nuclear medicine centers. The result of the research is the identification of the design principles of nuclear medicine centers with the functions of the production of radiopharmaceuticals and the department of medical imaging. This research will be applied to the design and construction of healthcare facilities in the field of nuclear medicine.

Keywords: architectural planning solutions, functional zoning, nuclear medicine, PET/CT scan, production of radiopharmaceuticals, radiotherapy

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Authors: Cristina Maria Ribeiro Martins Pereira Caridade, Ana Rita Ferreira Morais

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The use of computational tools has become essential in the context of interactive learning, especially in engineering education. In the medical industry, teaching medical image processing techniques is a crucial part of training biomedical engineers, as it has integrated applications with healthcare facilities and hospitals. The aim of this article is to present a teaching-learning simulation tool developed in MATLAB using a graphical user interface for medical image fusion that explores different image fusion methodologies and processes in combination with image pre-processing techniques. The application uses different algorithms and medical fusion techniques in real time, allowing you to view original images and fusion images, compare processed and original images, adjust parameters, and save images. The tool proposed in an innovative teaching and learning environment consists of a dynamic and motivating teaching simulation for biomedical engineering students to acquire knowledge about medical image fusion techniques and necessary skills for the training of biomedical engineers. In conclusion, the developed simulation tool provides real-time visualization of the original and fusion images and the possibility to test, evaluate and progress the student’s knowledge about the fusion of medical images. It also facilitates the exploration of medical imaging applications, specifically image fusion, which is critical in the medical industry. Teachers and students can make adjustments and/or create new functions, making the simulation environment adaptable to new techniques and methodologies.

Keywords: image fusion, image processing, teaching-learning simulation tool, biomedical engineering education

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Authors: Yong Zhang

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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

Procedia PDF Downloads 159

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

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Awad Mohamed Elkhadir, Rajab M. Ben Yousef

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Background/Aim: Radiological technologists are medical professionals who perform diagnostic imaging tests such as X-rays, magnetic resonance imaging (MRI) scans, and computer tomography (CT) scans. Despite the recognition of image interpretation by British radiologists, it is still considered a problem in the Arab world. This study evaluates the perceptions of radiologists in the Middle East concerning the plain image interpretation of adults by radiologic technologist specialists. Methods: This is a cross-sectional study that follows a quantitative approach. A close-ended questionnaire was distributed among 103 participants who were radiologists by profession from various hospitals in Saudi Arabia and Sudan. The gathered data was then analyzed through Statistical Package for Social Sciences (SPSS). Results: The results showed that 29% recognized the Radiologic Technologist Specialist (RTS) role of writing image reports, while 61% did not. A total of 38% of participants believed that RTS image interpretation would help diagnose unreported radiographs. 47% of the sample responded that the workload and stress on radiologists would reduce by allowing reporting for RTS, while 37% did not. Lastly, 43% believe that image interpretation by RTS can be introduced into the Middle East in the future. Conclusion: The study's findings reveal that the combination of image reporting and radiography improves the care of the patients. The study's outcomes also show that the burden of the medical practitioners reduces due to image reporting of the radiographers. Further researches need to be conducted in the Arab World to obtain and measure the associated factors of the desired criteria.

Keywords: Arab world, image interpretation, radiographer, radiologist, Saudi Arabia, Sudan

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Authors: Daud Muhammad

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Introduction: Ankle radiographs are frequently requested in Emergency Departments (ED) for patients presenting with traumatic ankle pain. The Ottawa Ankle Rules (OAR) serve as a clinical guideline to determine the necessity of these radiographs, aiming to reduce unnecessary imaging. This audit was conducted to evaluate the adequacy of clinical information provided in radiograph requests in relation to the OAR. Methods: A retrospective analysis was performed on 50 consecutive ankle radiograph requests under ED clinicians' names for patients aged above 5 years, specifically excluding follow-up radiographs for known fractures. The study assessed whether the provided clinical information met the criteria outlined by the OAR. Results: The audit revealed that none of the 50 radiograph requests contained sufficient information to satisfy the Ottawa Ankle Rules. Furthermore, 10 out of the 50 radiographs (20%) identified fractures. Discussion: The findings indicate a significant lack of adherence to the OAR, suggesting potential overuse of radiography and unnecessary patient exposure to radiation. This non-compliance may also contribute to increased healthcare costs and resource utilization, as well as possible delays in diagnosis and treatment. Recommendations: To address these issues, the following recommendations are proposed: (1) Education and Training: Enhance awareness and training among ED clinicians regarding the OAR. (2) Standardised Request Forms: Implement changes to imaging request forms to mandate relevant information according to the OAR. (3) Scan Vetting: Promote awareness among radiographers to discuss the appropriateness of scan requests with clinicians. (4) Regular re-audits should be conducted to monitor improvements in compliance.

Keywords: Ottawa ankle rules, ankle radiographs, emergency department, traumatic pain

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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

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Authors: K. Hinde, R. Bookun, P. Tran

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Percutaneous CT guided biopsies provide a fast, minimally invasive, cost effective and safe method for obtaining tissue for histopathology and culture. Standards for diagnostic yield vary depending on whether the tissue is being obtained for histopathology or culture. We present a retrospective audit from Western Health in Melbourne Australia over a 12-month period which aimed to determine the diagnostic yield, technical success and complication rate for CT guided bone biopsies and identify factors affecting these results. The digital imaging storage program (Synapse Picture Archiving and Communication System – Fujifilm Australia) was analysed with key word searches from October 2015 to October 2016. Nineteen CT guided bone biopsies were performed during this time. The most common referring unit was oncology, work up imaging included CT, MRI, bone scan and PET scan. The complication rate was 0%, overall diagnostic yield was 74% with a technical success of 95%. When performing biopsies for histologic analysis diagnostic yield was 85% and when performing biopsies for bacterial culture diagnostic yield was 60%. There was no significant relationship identified between size of lesion, distance of lesion to skin, lesion appearance on CT, the number of samples taken or gauge of needle to diagnostic yield or technical success. CT guided bone biopsy at Western Health meets the standard reported at other major clinical centres for technical success and safety. It is a useful investigation in identification of primary malignancy in distal bone metastases.

Keywords: bone biopsy, computed tomography, core biopsy, histopathology

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: T. Vijayashree, A. Gopal

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The aim of the work is to classify and authenticate medicinal plant materials and herbs widely used for Indian herbal medicinal preparation. The quality and authenticity of these raw materials are to be ensured for the preparation of herbal medicines. These raw materials are to be carefully screened, analyzed and documented due to mistaken of look-alike materials which do not have medicinal characteristics.

Keywords: authenticity, standardization, principal component analysis, imaging processing, signal processing

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Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

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This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control

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Authors: Hyeona Kim, Kichang Lee, Seunghee Lee, Jeongsu An, Kyungjun Min

Abstract:

Contrast videofluoroscopy is the diagnostic imaging technique for evaluating cat with dysphagia. Generally, videofluoroscopic studies have been done with the cat restrained in lateral recumbency. It is different from the neutral position such as standing or sternal recumbency which is actual swallowing posture. We hypothesized that measurement of esophageal transit and peristalsis would be affected by body position. This experimental study analyzed the imaging findings of barium esophagram in 5 cats. Each cat underwent videofluoroscopy during swallowing of liquid barium and barium-soaked kibble in standing position and lateral recumbency. Esophageal transit time and the number of esophageal peristaltic waves were compared among body positions. Transit time in the cervical esophagus (0.57s), cranial thoracic esophagus (2.5s), and caudal thoracic esophagus(1.10s) was delayed when cats were in lateral recumbency for liquid barium. For kibble, transit time was more delayed than that of liquid through the entire esophagus in lateral recumbency. Liquid and kibble frequently started to delay at thoracic inlet region, transit time in the thoracic esophagus was significantly delayed than the cervical esophagus. In standing position, 60.2% of liquid swallows stimulated primary esophageal peristalsis. In lateral recumbency, 50.5% of liquid swallows stimulated primary esophageal peristalsis. Other variables were not significantly different. Lateral body positioning increases entire esophageal transit time and thoracic esophageal transit time is most significantly delayed. Thus, lateral recumbency decreases the number of primary esophageal peristalsis.

Keywords: barium esophagram, body positioning, cat, videofluoroscopy

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Authors: Shakir H. Mohammed Al-Alwany, Saad Hasan M. Ali, Ibrahim Mohammed S. Shnawa

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The study was aimed to define the percentage of detection of high-oncogenic risk types of HPV and their genotyping in archival tissue specimens that ranged from apparently healthy tissue to invasive breast cancer by using one of the recent versions of In Situ Hybridization(ISH) 0.2. To find out rational significance of such genotypes as well as over expressed products of mutants P53 and RB genes on the severity of underlying breast cancers. The DNA of HPV was detected in 46.5 % of tissues from breast cancers while HPV DNA in the tissues from benign breast tumours was detected in 12.5%. No HPV positive–ISH reaction was detected in healthy breast tissues of the control group. HPV DNA of genotypes (16, 18, 31 and 33) was detected in malignant group in frequency of 25.6%, 27.1%, 30.2% and 12.4%, respectively. Over expression of p53 was detected by IHC in 51.2% breast cancer cases and in 50% benign breast tumour group, while none of control group showed P53- over expression. Retinoblastoma protein was detected by IHC test in 49.7% of malignant breast tumours, 54.2% of benign breast tumours but no signal was reported in the tissues of control group. The significance prevalence of expression of mutated p53 & Rb genes as well as detection of high-oncogenic HPV genotypes in patients with breast cancer supports the hypothesis of an etiologic role for the virus in breast cancer development.

Keywords: human papilloma virus, P53, RB, breast cancer

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Authors: Mrinal Kanti Bhowmik, Kakali Das Jr., Barin Kumar De, Debotosh Bhattacharjee

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Breast cancer is the most common cancer and a leading cause of death for women in the 35 to 55 age group. Early detection of breast cancer can decrease the mortality rate of breast cancer. Mammography is considered as a ‘Gold Standard’ for breast cancer detection and a very popular modality, presently used for breast cancer screening and detection. The screening of digital mammograms often leads to over diagnosis and a consequence to unnecessary traumatic & painful biopsies. For that reason recent studies involving the use of thermal imaging as a screening technique have generated a growing interest especially in cases where the mammography is limited, as in young patients who have dense breast tissue. Tumor is a significant sign of breast cancer in both mammography and thermography. The tumors are complex in structure and they also exhibit a different statistical and textural features compared to the breast background tissue. Fractal geometry is a geometry which is used to describe this type of complex structure as per their main characteristic, where traditional Euclidean geometry fails. Over the last few years, fractal geometrics have been applied mostly in many medical image (1D, 2D, or 3D) analysis applications. In breast cancer detection using digital mammogram images, also it plays a significant role. Fractal is also used in thermography for early detection of the masses using the thermal texture. This paper presents an overview of the recent aspects and initiatives of fractals in breast cancer detection in both mammography and thermography. The scope of fractal geometry in automatic breast cancer detection using digital mammogram and thermogram images are analysed, which forms a foundation for further study on application of fractal geometry in medical imaging for improving the efficiency of automatic detection.

Keywords: fractal, tumor, thermography, mammography

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Authors: Najla M. Salkho, Vinod Paul, Pierre Kawak, Rute F. Vitor, Ana M. Martin, Nahid Awad, Mohammad Al Sayah, Ghaleb A. Husseini

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Liposomes are popular lipid bilayer nanoparticles that are highly efficient in encapsulating both hydrophilic and hydrophobic therapeutic drugs. Liposomes promote a low risk controlled release of the drug avoiding the side effects of the conventional chemotherapy. One of the great potentials of liposomes is the ability to attach a wide range of ligands to their surface producing ligand-mediated active targeting of cancer tumour with limited adverse off-target effects. Ultrasound can also aid in the controlled and specified release of the drug from the liposomes by breaking it apart and releasing the drug in the specific location where the ultrasound is applied. Our research focuses on the synthesis of PEGylated liposomes (contain poly-ethylene glycol) encapsulated with the model drug calcein and studying the effect of low frequency ultrasound applied at different power densities on calcein release. In addition, moieties are attached to the surface of the liposomes for specific targeting of the cancerous cells which over-express the receptors of these moieties, ultrasound is then applied and the release results are compared with the moiety free liposomes. The results showed that attaching these moieties to the surface of the PEGylated liposomes not only enhance their active targeting but also stimulate calcein release from these liposomes.

Keywords: active targeting, liposomes, moieties, ultrasound

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Authors: Sylvain Amailland, Jean-Hugh Thomas, Charles Pézerat, Romuald Boucheron, Jean-Claude Pascal

Abstract:

The noise requirements for naval and research vessels have seen an increasing demand for quieter ships in order to fulfil current regulations and to reduce the effects on marine life. Hence, new methods dedicated to the characterization of propeller noise, which is the main source of noise in the far-field, are needed. The study of cavitating propellers in closed-section is interesting for analyzing hydrodynamic performance but could involve significant difficulties for hydroacoustic study, especially due to reverberation and boundary layer noise in the tunnel. The aim of this paper is to present a numerical methodology for the identification of hydroacoustic sources on marine propellers using hydrophone arrays in a large hydrodynamic tunnel. The main difficulties are linked to the reverberation of the tunnel and the boundary layer noise that strongly reduce the signal-to-noise ratio. In this paper it is proposed to estimate the reflection coefficients using an inverse method and some reference transfer functions measured in the tunnel. This approach allows to reduce the uncertainties of the propagation model used in the inverse problem. In order to reduce the boundary layer noise, a cleaning algorithm taking advantage of the low rank and sparse structure of the cross-spectrum matrices of the acoustic and the boundary layer noise is presented. This approach allows to recover the acoustic signal even well under the boundary layer noise. The improvement brought by this method is visible on acoustic maps resulting from beamforming and DAMAS algorithms.

Keywords: acoustic imaging, boundary layer noise denoising, inverse problems, model adaptation

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Authors: Angelis P. Barlampas

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Purpose: A 29 years old woman presented in the emergency department with psychiatric symptoms. The psychiatrist ordered a computed tomography scan as part of a general examination. Material and methods: The CT showed bilateral enlarged choroid plexus structures mimicking papillomata and situated in the trigones of the lateral ventricles. The left choroid plexus was heavily calcified, but the right one has no any obvious calcifications. Results: It is well kown that any brain mass can present with behavioral changes and even psychiatric symptomatology. Papillomata of the ventricular system have been described to cause psychotic episodes. According to literature, choroid plexus papillomas are seldom neuroepithelial intraventricular tumors, which are benign and categorized as WHO grade 1 tumors. They are more common in the pediatric population, but they can occur in the adults, too1. In addition, the distinction between choroid plexus papilloma and carcinoma is very difficult and impossible by imagine alone. It can only be implied with more advanced imaging, such as arterial spin labeling and MRI. The final diagnosis is, of course, after surgical excision. The usual location in adults is the fourth ventricle, but in children, it is the lateral ventricles. Their imaging appearance is that of a solid vascular tumor, which enhances intensely after the intravenous administration of contrast material. One out of fourth tumors presents speckled calcifications1. In our case, there are symmetrically sized masses at the trigones, and there are no calcifications in one of them, whereas the other one is grossly calcified. Also, there is no obvious hydrocephalus or any other evidence of increased intracranial pressure. General conclusions: When there is a new psychiatric patient, someone must undergo any possible examination, and of course, a brain CT study should be done to exclude any rare organic causes that may be responsible for the disease.

Keywords: phycosis, intraventricular masses, CT, brain calcifications

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Authors: Awf A. Al-Khan, Michael J. Day, Judith Nimmo, Mourad Tayebi, Stewart D. Ryan, Samantha J. Richardson, Janine A. Danks

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Osteosarcoma (OS) is the most common type of malignant primary bone tumour in dogs. In addition to their critical roles in bone formation and remodeling, parathyroid hormone-related protein (PTHrP) and its receptor (PTHR1) are involved in progression and metastasis of many types of tumours in humans. The aims of this study were to determine the localisation and expression levels of PTHrP and PTHR1 in canine OS tissues using immunohistochemistry and to investigate if this expression is correlated with survival time. Formalin-fixed, paraffin-embedded tissue samples from 44 dogs with known survival time that had been diagnosed with primary osteosarcoma were analysed for localisation of PTHrP and PTHR1. Findings showed that both PTHrP and PTHR1 were present in all OS samples. The dogs with high level of PTHR1 protein (16%) had decreased survival time (P<0.05) compared to dogs with less PTHR1 protein. PTHrP levels did not correlate with survival time (P>0.05). The results of this study indicate that the PTHR1 is expressed differently in canine OS tissues and this may be correlated with poor prognosis. This may mean that PTHR1 may be useful as a prognostic indicator in canine OS and could represent a good therapeutic target in OS.

Keywords: dog, expression, osteosarcoma, parathyroid hormone receptor 1 (PTHR1), parathyroid hormone-related protein (PTHrP), survival

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Authors: Stefan Gruden, Charlott Brunmark, Bo Holmqvist, Erwin D. Brenndorfer, Martin Johansson, Jian Liu, Ying Zhao, Niklas Axen, Moustapha Hassan

Abstract:

Aim: The study was designed to evaluate the ability of the calcium sulfate-based NanoZolid® drug delivery technology to locally release the epidermal growth factor (EGF) protein while maintaining its biological activity. Methods: NanoZolid-formulated EGF protein labelled with a near-infrared dye (EGF-NIR) depots or EGF-NIR dissolved in PBS were injected subcutaneously into mice bearing EGF receptor (EGFR) positive human A549 lung cancer tumors inoculated subcutaneously. The release and biodistribution of the EGF-NIR were investigated in vivo longitudinally up to 96 hours post-administration, utilizing whole-body fluorescence imaging. In order to confirm the in vivo findings, histological analysis of tumor cryosections was performed to investigate EGF-NIR fluorescent signal and EGFR expression level by immunofluorescence labelling. Results: The in vivo fluorescence imaging showed a controlled release profile of the EGF-NIR loaded in the NanoZolid depots compared to free EGF-NIR. Histological analysis of the tumors further demonstrated a prevailing distribution of EGF-NIR in regions with high levels of EGFR expression. Conclusion: Calcium sulfate based depots can be used to formulate EGF while maintaining its biological activity, e.g., receptor binding capability. This may have good clinical potential for local delivery of biomolecules to enhance treatment efficacy and minimize systemic adverse effects.

Keywords: bioresorbable, calcium sulfate, controlled release, NanoZolid

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