Purpose: To evaluate the role of DTI (with fibretracking) and T2-weighted imaging (T2-WI) used together for predicting extra-capsular extension in patients with localized prostate cancer.
Method And Materials: Thirty-six patients with biopsy-proven diagnosis of prostatic neoplasia performed MRI and underwent radical prostatectomy. Histopathological analysis showed ECE in 15/36 and capsule sparing in 21/36. By means of T2-WI, ECE was evaluated in a qualitative manner, according to PI-RADS v.2 (two groups with low and high risk of ECE); sensitivity and specificity were calculated for both groups. We performed a quantitative analysis on two tractographic parameters, fractional anisotropy (FA) and apparent diffusion coefficient (ADC) and computed the ratio between the lesion quadrant and its contralateral (L/H ratio). We compared L/H ratios of patients with and without ECE; ROC analyses were performed to determinate ECE cut-off values of tractographic parameters. These cut-off values were used in association with T2-WI to reassess patients and to evaluate whether specificity and sensitivity of ECE detection change.
Results: T2-WI showed a sensitivity of 80% and a specificity of 71% in detection of ECE. Tractography displayed a significant difference in L/H ratio for FA and ADC between patients with and without ECE. The simultaneous use of T2-WI and tractography revealed high sensitivity (100%) on patients with low suspect of ECE (on T2-WI) and high specificity (83%) on patients with high suspect of ECE (on T2-WI).
Conclusion: The morphologic component of T2-weighted imaging and functional aspect of DTI should be interpreted together to more successfully assess the presence of ECE.
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Sci Rep
January 2025
Department of Electrical and Computer Engineering, Aarhus University, Aarhus, 8200, Denmark.
Significant progress has been made through the optimization of modelling and device architecture solar cells has proven to be a valuable and highly effective approach for gaining a deeper understanding of the underlying physical processes in solar cells. Consequently, this research has conducted a two-dimensional (2D) perovskite solar cells (PSCs) simulation to develop an accurate model. The approach utilized in this study is based on the finite element method (FEM).
View Article and Find Full Text PDFAlzheimers Dement
December 2024
New York University Grossman School of Medicine, New York, NY, USA.
Background: Alzheimer's disease is associated with neurotoxic amyloid-beta (Aβ) plaques. Studies in mice demonstrated that cerebrospinal fluid (CSF) clearance, if impaired, reduces Aβ clearance by 70% and that sleep enhances CSF clearance via expanding extracellular space by 60%. However, the impact of sleep on extracellular volume in human remains unclear due to lack of non-invasive technology.
View Article and Find Full Text PDFPLoS One
January 2025
Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
Bed regulation within Brazil's National Health System (SUS) plays a crucial role in managing care for patients in need of hospitalization. In Rio Grande do Norte, Brazil, the RegulaRN Leitos Gerais platform was the information system developed to register requests for bed regulation for COVID-19 cases. However, the platform was expanded to cover a range of diseases that require hospitalization.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
Soil and Water Department, Faculty of Agriculture, Fayoum University, Fayoum, 63514, Egypt.
Background: Globally, salinity poses a threat to crop productivity by hindering plant growth and development via osmotic stress and ionic cytotoxicity. Plant extracts have lately been employed as exogenous adjuvants to improve endogenous plant defense mechanisms when grown under various environmental stresses, such as salinity. This study investigated the potential of melatonin (Mt; 0, 50, and 100 mM) as an antioxidant and licorice root extract (LRE; 0.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Wireless Sensing and Imaging Laboratory & 6G Research Laboratory, SRM University AP, Amaravati 522502, India.
This study presents a numerical modeling approach that utilizes millimeter-wave (mm-Wave) Frequency-Modulated Continuous-Wave (FMCW) radar to reconstruct and classify five weapon types: grenades, knives, guns, iron rods, and wrenches. A dataset of 1000 images of these weapons was collected from various online sources and subsequently used to generate 3605 samples in the MATLAB (R2022b) environment for creating reflectivity-added images. Background reflectivity was considered to range from 0 to 0.
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