Yazar "Abuzaid, Mohamed M." seçeneğine göre listele

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    Establishment of diagnostic reference levels in cone beam computed tomography scans in the united arab emirates
    (MDPI, 2022) Abuzaid, Mohamed M.; Elshami, Wiam; Jayachandran, Deepa; Korappil, Noushad; Tekin, Hüseyin Ozan
    This study aimed to address the knowledge gap in assessing the radiation doses from cone beam computed tomography (CBCT) procedures, establishing a typical value, and estimating effective and organ doses. A total of 340 patients aged 18-80 years were included in this study. Organ doses were estimated using VirtualDose IR software. The typical values were based on median values estimated as 1000 mGy cm2. The mean ED (µSv) per procedure was 149.5 ± 56, and the mean of the peak skin dose during the CBCT examination was 39.29 mGy. The highest organ dose was received by the salivary glands (2.71 mGy), the extrathoracic region (1.64 mGy), thyroid (1.24 mGy) and eyes (0.61 mGy). The patients' doses were higher than in previous studies. Staff awareness, education, training and dose optimisation are highly recommended. With the establishment of local DRLs, patient dosages can be reduced successfully without compromising image quality.
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    A focusing study on radioprotective and antioxidant effects of Annona muricata leaf extract in the circulation and liver tissue: clinical and experimental studies
    (De Gruyter Open Ltd, 2022) Elmas, Özlem; Şahin, Havva Hande Keser; Güven, Berrak; Abuzaid, Mohamed M.; Elshami, Wiam; Almisned, Ghada; Zakaly, Hesham M. H.; Ene, Antoaneta; Tekin, Hüseyin Ozan
    Objectives: This study investigates the effect of Annona muricata (AM) leaf extract against irradiation-induced damage by the evaluation of hepatic tissue and the levels of oxidative and inflammatory stress in the circulation. Methods: An experimental study with 37 female Wistar albino rats randomized into four groups (controls and three intervention groups) was performed. The first interventional group (group 2) received 300 mg/kg of AM leaf extract by oral gavage once a day for 9 days, group 3 received a single dose of whole-body radiation (8.3 Gy) after a 9-day oral gavage treatment with saline, and the last group received the same irradiation of 8.3 Gy after being treated with 300 mg/kg of AM leaf extract by oral gavage once a day for 9 days. Results: Radiation was found to elevate reactive oxygen species parameters, and AM administration before irradiation was found to decrease total oxidant status (TOS), increase caspase 9, and improve hepatic damage when compared with the group that received only irradiation. Conclusion: The damage caused by irradiation may be ameliorated by the use of the AM extract, which appears to be effective in preventing oxidative stress and inflammatory activity.
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    Infection control and radiation safety practices in the radiology department during the COVID-19 outbreak
    (Public Library Science, 2022) Abuzaid, Mohamed M.; Elshami, Wiam; Tekin, Hüseyin Ozan
    Rationale and objectives Radiology personnel must have good knowledge, experience and adherence to radiation protection and infection control practices to ensure patient safety and prevent the further spread of the COVID-19 virus. This study analysed compliance and adherence to radiation protection and infection control during COVID-19 mobile radiography. Methods A cross-sectional using online survey was conducted from September to December 2021. Data on demographic characteristics, adherence to radiation protection and infection control practice were collected during mobile radiography for COVID-19 patients in the study. A random sample of the radiographers working in COVID-19 centres in the United Arab Emirates. Results Responses were received from 140 participants, with a response rate of 87.5%. Females were the predominant participants (n = 81; 58%). Participants aged ages between 18-25 years (n = 46; 33%) and 26-35 years (n = 42; 30%), (n = 57; 41%) had less than five years of experience, followed by participants who had more than 15 years (n = 38; 27%). Most participants (n = 81; 57.9%) stated that they performed approximately 1-5 suspected or confirmed COVID-19 cases daily. The participants had moderate to high adherence to radiation protection, with a mean and standard deviation of 42.3 6.28. Additionally, infection control adherence was high, with 82% of the participants showing high adherence. Conclusion Continuous guidance, training and follow-up are recommended to increase adherence and compliance to radiation protection and infection control compliance. Educational institutions and professional organisations must collaborate to provide structured training programmes for radiology practitioners to overcome the practice and knowledge gap.
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    Utilization of artificial intelligence approach for prediction of DLP values for abdominal CT scans: A high accuracy estimation for risk assessment
    (Frontiers, 2022) Tekin, Hüseyin Ozan; Almisned, Faisal; Ergüzel, Türker Tekin; Abuzaid, Mohamed M.; Ene, Antoaneta; Zakaly, Hesham M.; Elshami, Wiam
    Purpose: This study aimed to evaluate Artificial Neural Network (ANN) modeling to estimate the significant dose length product (DLP) value during the abdominal CT examinations for quality assurance in a retrospective, cross-sectional study. Methods: The structure of the ANN model was designed considering various input parameters, namely patient weight, patient size, body mass index, mean CTDI volume, scanning length, kVp, mAs, exposure time per rotation, and pitch factor. The aforementioned examination details of 551 abdominal CT scans were used as retrospective data. Different types of learning algorithms such as Levenberg-Marquardt, Bayesian and Scaled-Conjugate Gradient were checked in terms of the accuracy of the training data. Results: The R-value representing the correlation coefficient for the real system and system output is given as 0.925, 0.785, and 0.854 for the Levenberg-Marquardt, Bayesian, and Scaled-Conjugate Gradient algorithms, respectively. The findings showed that the Levenberg-Marquardt algorithm comprehensively detects DLP values for abdominal CT examinations. It can be a helpful approach to simplify CT quality assurance. Conclusion: It can be concluded that outcomes of this novel artificial intelligence method can be used for high accuracy DLP estimations before the abdominal CT examinations, where the radiation-related risk factors are high or risk evaluation of multiple CT scans is needed for patients in terms of ALARA. Likewise, it can be concluded that artificial learning methods are powerful tools and can be used for different types of radiation-related risk assessments for quality assurance in diagnostic radiology.