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AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact.
EJNMMI Phys
January 2025
Department of Nuclear Medicine, Rambam Health Care Campus, P.O.B. 9602, 3109601, Haifa, Israel.
Background: A recently released digital solid-state positron emission tomography/x-ray CT (PET/CT) scanner with bismuth germanate (BGO) scintillators provides an artificial intelligence (AI) based system for automatic patient positioning. The efficacy of this digital-BGO system in patient placement at the isocenter and its impact on image quality and radiation exposure was evaluated.
Method: The digital-BGO PET/CT with AI-based auto-positioning was compared (χ, Mann-Whitney tests) to a solid-state lutetium-yttrium oxyorthosilicate (digital-LYSO) PET/CT with manual patient positioning (n = 432 and 343 studies each, respectively), with results split into groups before and after the date of a recalibration of the digital-BGO auto-positioning camera.
Electrochemical Filtration of Gadolinium from Patient Urine after Magnetic Resonance Imaging.
ACS Appl Mater Interfaces
January 2025
Department of Chemistry, Wayne State University, Detroit, Michigan 48202, United States.
The widespread use of gadolinium-based contrast agents for magnetic resonance imaging (MRI) in recent decades has led to a growing demand for Gd and raised environmental concerns due to their direct discharge into wastewater systems. In response, we developed an electrochemical filtration method to recover Gd from patient urine following contrast-enhanced MRI. This method involves modifying a conventional vacuum filtration apparatus by introducing electrodes into the filter membrane, creating a strong electric field of ∼5 kV/m and a steep three-zone pH gradient within the filter membrane.
View Article and Find Full Text PDFInvestigation of boiler energy consumption in the gas refinery units using RSM ANN and Aspen HYSYS.
Heliyon
January 2025
Faculty of Mechanical Engineering, University of Tehran, Iran.
In order to lower total energy consumption, this study focuses on optimizing energy use in refinery boilers. Using Aspen HYSYS simulations and modeling approaches like Artificial Neural Networks (ANNs) and Response Surface Methodology (RSM), data from 579 days of boiler operation was gathered and examined. Radial Basis Function (RBF) and Multi-Layer Perceptron (MLP) techniques were used in the ANN modeling.
View Article and Find Full Text PDFMutagenicity and carcinogenicity prediction of sugar substitutes: an approach with compound-gene interactions network.
Toxicol Res (Camb)
February 2025
Department of Bioinformatics, Bharathidasan University, Tiruchirappalli, Tamil Nadu 620024, India.
Sugar substitutes are mostly artificial, man-made industrial products used as additives in food and beverages. Most of these substances flow through the digestive tract and food chains, becoming emerging organic contaminants in various abiotic and biotic environmental media. Here, we predict the mutagenicity and carcinogenicity of commonly used sugar substitutes using in silico based methods.
View Article and Find Full Text PDFA rationale for the poor response to alectinib in a patient with adenocarcinoma of the lung harbouring a fusion by artificial intelligence and molecular modelling: a case report.
Transl Lung Cancer Res
December 2024
Department of Physics and Center for Complexity and Biosystems, Università degli Studi di Milano and INFN, Milano, Italy.
Background: Non-small cell lung cancers (NSCLCs) with fusions are effectively treated with tyrosine kinase inhibitors (TKIs). The widespread use of next-generation sequencing (NGS) assays to study the molecular profile of NSCLCs, can identify rare fusion partners of . Therapy decisions are made without considering which fusion partner is present and its potential oncogenic properties.
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