Objectives: Small field of view gamma detection and imaging technologies for monitoring in vivo tracer uptake are rapidly expanding and being introduced for bed-side imaging and image guided surgical procedures. The Hybrid Gamma Camera (HGC) has been developed to enhance the localization of targeted radiopharmaceuticals during surgical procedures; for example in sentinel lymph node (SLN) biopsies and for bed-side imaging in procedures such as lacrimal drainage imaging and thyroid scanning. In this study, a prototype anthropomorphic head and neck phantom has been designed, constructed, and evaluated using representative modelled medical scenarios to study the capability of the HGC to detect SLNs and image small organs. Methods: An anthropomorphic head and neck phantom has been designed to mimic the adult head and neck including some internal organs and tissues of interest, such as the thyroid gland and sentinel lymph nodes. The design of the head and neck phantom included an adjustable inner jig holding the simulated SLNs and thyroid gland. The simulated thyroid gland was designed and 3D printed taking into consideration the size and the shape of a healthy adult thyroid gland. The inner sealed space of the thyroid was filled with 15MBq of 99mTc through two upper filling valves. Sealed micro-tubes (0.2ml) have been employed to simulate SLNs containing various 99mTc activity concentrations ranging between 0.1MBq and 1MBq, and can be positioned at any desired place in the head and neck region. An active background was simulated through mixing 10MBq of 99mTc solution with the water used to fill the outer shell of the head and neck phantom. Results: The head and neck phantom was employed to simulate a situation where there are four SLNs distributed at two different vertical levels and at two depths within the neck. Contrast to noise ratio (CNR) calculations were performed for the detected SLNs at an 80mm distance between both pinhole collimators (i.e. 0.5mm and 1.0mm diameters) and the surface of the head and neck phantom with a 100s acquisition time. The recorded CNR values for the simulated SLNs are higher when the HGC was fitted with the 1.0mm diameter pinhole collimator. For instance, the recorded CNR values for the superficially simulated SLN containing 0.1MBq of 99mTc using 0.5mm and 1.0mm diameter pinhole collimators are 6.48 and 16.42, respectively (~87% difference). The anatomical context provided by the hybrid imaging aided the localization process of radioactivity accumulation in simulated SLNs. Gamma and hybrid optical images were acquired using the HGC with both available pinhole collimators for the simulated thyroid gland. The thyroid images produced varied in terms of spatial resolution and detectability. The count profiles through the middle of the simulated thyroid gland images provided by both pinhole collimators were obtained. The HGC could clearly differentiate the individual peaks of both thyroid lobes in the gamma image produced by the 0.5mm pinhole collimator. In contrast, the recorded count profile for the acquired image using the 1.0mm diameter pinhole collimator showed broader peaks for both lobes, reflecting the degradation of the spatial resolution with increasing the diameter of the pinhole collimator. Conclusion: The capability of the HGC has been evaluated utilizing a prototype anthropomorphic head and neck phantom, and the gamma and hybrid images obtained demonstrate that it is ideally suited for intraoperative SLNs detection and small organ imaging. The standardization of test phantoms and protocols for SFOV portable gamma systems will provide an opportunity to collect data across various medical centers and research groups. Moreover, it will provide a technical baseline for researchers and clinical practitioners to consider when assessing their SFOV gamma imaging systems. The anthropomorphic head and neck phantom described is cost effective, reproducible, flexible and anatomically representative.
Abstract:
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Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conduc
... Show MoreAn encryption system needs unpredictability and randomness property to maintain information security during transmission and storage. Although chaotic maps have this property, they have limitations such as low Lyapunov exponents, low sensitivity and limited chaotic regions. The paper presents a new improved skewed tent map to address these problems. The improved skew tent map (ISTM) increases the sensitivity to initial conditions and control parameters. It has uniform distribution of output sequences. The programs for ISTM chaotic behavior were implemented in MATLAB R2023b. The novel ISTM produces a binary sequence, with high degree of complexity and good randomness properties. The performance of the ISTM generator shows effective s
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Background: Since its introduction to musculoskeletal imaging in the early 1980, magnetic resonance imaging (MRI) has revolutionized diagnostic imaging of the knee. It is therefore become the examination of choice in the evaluation of internal joint structures of the knee like menisci, cruciate ligaments, and articular cartilage.Objectives: to describe the MRI finding in various knee injuries.Patients and methods: A cross sectional study was done on 130 patients with history of knee injury in MRI unit at institute of radiology and al-Shaheed Ghazi Al-Hariri Hospital in medical city complex - Baghdad, from October 2011 to February 2013 includes 103 men, 27 women; the mean age was 33.86 years. MR imaging studies of the knee performed using
... Show MoreThe aim of the research was to prepare the fields and items for safe environment scale form professional basketball players and coaches’ point of view. The researchers used the descriptive method on professional athletes of players and coaches from (11) clubs; for the pilot study (21) athletes were selected and for the building sample (103) athletes, and standardization sample (101) athletes from the participants in the Iraqi league (2018-2019). The scale of the safe environment was concluded with (6) fields and (52) items. The researchers came up with the safe environment scale from the point of view of professional basketball players and coaches. Finally the researchers recommended paying attention to providing safe environment for athl
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.
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