Background/Aim: Endometrial abnormalities represent a diagnostic challenge due to overlapping imaging features with normal endometrium. Aim of this study was to assess accuracy of dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging (MRI) in evaluation of endometrial lesions in comparison with T2 and to assess local staging validity and degree of myometrial invasion in malignancy. Methods: Forty patients with abnormal vaginal bleeding or sonographic thickened endometrial were recruited. MRI examination of pelvis was per-formed using 1.5 T scanner with a pelvic array coil. Conventional T1-and T2, dynamic contrast-enhanced (DCE) sequences and diffusion-weighted image (DWI) were performed. Results: Mean age of patients was 53.2 years and 60 % of patients COM-plained of post-menopausal bleeding. Irregular margin, type III enhancement curve, a high signal in T2WI and DWI and low signal of apparent diffusion coefficient (ADC) were significantly associated with malignancy. The optimum ADC threshold value for distinguishing benign from malignant endometrial lesions was 0.905 × 10 -3 mm 2 /S, with 95.5 % sensitivity and 92.9 % specificity. DWI was most sensitive to malignant endometrial lesions, followed by DCE (89.6 %, 98.4 %) and T2 (86.7 %, 91.4 %). DWI and DCE staging correlated with FIGO staging (p = 0.0001 and p = 0.019, respectively). DWI had the best sensitivity for myometrial invasion (95.6 %), followed by DCE (91.9 %) and T2WI (90.1 %). All three sequences had 89.7 % specificity. Conclusion: DWI and DCE MRI were superior to conventional MRI at distinguishing malignant from benign endometrial lesions and can improve myometrial invasion depth evaluation and therapy planning when COM-bined with morphological T2WI. ADC cutoff at a high b value improved MRI diagnostic sensitivity and specificity.
In light of the developments and intense competition that the world has witnessed, the need to search for a sustainable and continuous competitive advantage for economic units has emerged, as the economic units must not lose sight of their interest in the activities they perform to achieve that advantage, and it can be said that the goal of the research is to identify the theoretical dimensions of the green value chain represented by: (Green research and development, green design, green manufacturing, green marketing, green services) and the dimensions of the sustainable competitive advantage represented by (quality, creativity, innovation, cost, response to the customer), as well as identifyi
... Show MoreIn this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured to simulate steady state harmonic load at different operating frequencies. Total of 84 physical models were performed. The footing parameters are related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were tested at the surface and at 50 mm depth below model surface. Meanwhile the investigated parameters of the soil condition include dry and saturated sand for two relative densities 30% and 80%. The response of the footing was ela
... Show MoreIn the present work a dynamic analysis technique have been developed to investigate and characterize the quantity of elastic module degradation of cracked cantilever plates due to presence of a defect such as surface of internal crack under free vibration. A new generalized technique represents the first step in developing a health monitoring system, the effects of such defects on the modal frequencies has been the main key quantifying the elasticity modulii due to presence any type of un-visible defect. In this paper the finite element method has been used to determine the free vibration characteristics for cracked cantilever plate (internal flaws), this present work achieved by different position of crack. Stiffness re
... Show MoreThis numerical study explores dynamic melting as an enhancement strategy to improve heat transfer in thermal energy storage (TES) systems utilizing phase change materials (PCM) with openings. Optimizing such systems is crucial for advancing renewable energy storage and integration. A 3D model simulates RT35 PCM flowing through a shell-and-tube heat exchanger annulus. The effects of varying PCM inlet slot diameter (2.5–7.5 mm), inlet pressure (1–40 Pa), and inlet/outlet port positioning on melting fraction and temperature distributions are computationally evaluated. Results show that increasing slot diameter from 2.5 mm to 7.5 mm reduces melting time by 13.6 % (from 550 to 475 min). Raising inlet pressure from 10 Pa to 40 Pa cuts melting
... Show MoreRadiation treatment has long been the conventional approach for treating nasopharyngeal cancer (NPC) tumors due to its anatomic features, biological characteristics, and radiosensitivity. The most common treatment for nasopharyngeal carcinoma is radiotherapy. This study aimed to assess the better quality of radiotherapy treatment techniques using intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT). The VMAT and IMRT are comparative techniques. Forty patients with nasopharyngeal carcinoma and forwarded for radiotherapy were treated with both advanced techniques, IMRT and VMAT, using eclipse software from Varian. The x-ray energy was set at 6 MV. The total prescribed dose was 70 Gy. The results show that the
... Show MoreThe Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats. This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat
... Show More This study includes Estimating scale parameter, location parameter and reliability function for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).
Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (RP=1000)
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