Objective: The purpose of this study was to determine whether coronal maximum-intensity-projection (MIP) reformations improve urinary tract stone detection and density measurements compared with routine axial and coronal images.
Materials And Methods: Forty-five consecutive patients who underwent MDCT for suspected urolithiasis were included. Two radiologists independently determined the number of stones on 5-, 3-, and 1.25-mm axial, 5- and 3-mm coronal, and 5-mm coronal MIP images. The reference standard was obtained by consensus review using all six datasets. Stone density was determined for all calculi 4 mm or larger on all datasets.
Results: There were a total of 115 stones. Reader 1 identified 111 (96.5%), 112 (97.4%), 97 (84.3%), 102 (88.7%), 99 (86.1%), and 85 (73.9%) stones and reader 2 identified 105 (91.3%), 102 (88.7%), 85 (73.9%), 89 (77.4%), 89 (77.4%), and 76 (66.1%) stones on the MIP, 1.25-mm axial, 3-mm axial, 3-mm coronal, 5-mm coronal, and 5-mm axial images, respectively. Both readers identified more stones on the MIP images than on the 3- or 5-mm axial or coronal images (p < 0.0001). The mean difference in stone attenuation compared with the thin axial images was significantly less for the MIP images (44.6 HU) compared with 3-mm axial (235 HU), 3-mm coronal (309 HU), and 5-mm coronal (329.6 HU) or axial images (347.8 HU) (p < 0.0001).
Conclusion: Coronal MIP reformations allow more accurate identification and density measurements of urinary tract stones compared with routine axial and coronal reformations.
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http://dx.doi.org/10.2214/AJR.12.10389 | DOI Listing |
Ecotoxicol Environ Saf
January 2025
College of Resource and Environment, Henan Polytechnic University, Jiaozuo 454003, China.
Identifying and quantifying the dominant factors influencing heavy metal (HM) pollution sources are essential for maintaining soil ecological health and implementing effective pollution control measures. This study analyzed soil HM samples from 53 different land use types in Jiaozuo City, Henan Province, China. Pollution sources were identified using Absolute Principal Component Score (APCS), with 8 anthropogenic factors, 9 natural factors, and 4 soil physicochemical properties mapped using Geographic Information System (GIS) kernel density estimation.
View Article and Find Full Text PDFJ Neurophysiol
January 2025
Department of Integrative Physiology, University of Colorado Boulder.
Our purpose was to compare the influence of the spectral content of motor unit recordings on the calculation of electromechanical delay and on the prediction of force fluctuations from measures of the variability in discharge times and neural drive during steady isometric contractions with the first dorsal interosseus muscle. Participants ( = 42; 60 ± 13 yrs) performed contractions at 5% and 20% MVC. After satisfying inclusion criteria, high-density surface EMG recordings from a subset of 23 participants were decomposed into the discharge times of 530 motor units.
View Article and Find Full Text PDFPeerJ
January 2025
Department of Entomology, The Pennsylvania State University, University Park, PA, United States of America.
Background: Preventative pesticide seed treatments (hereafter preventative pest management or PPM) are common corn and soybean treatments, and often include both fungicides and neonicotinoid insecticides. While PPM is intended to protect crops from soil-borne pathogens and early season insect pests, these seed treatments may have detrimental effects on biological control of weed seeds by insects.
Methods: Here, in two 3-year corn-soy rotations in Pennsylvania USA, we investigated a PPM approach to insect management compared to an integrated pest management approach (IPM) and a "no (insect) pest management" (NPM) control.
J Clin Exp Dent
December 2024
DDS. Titular Professor. Universidad de Antioquia U de A, Medellín, Colombia. Biomedical Stomatology Research Group, Universidad de Antioquia U de A, Medellín, Colombia.
Background: The RTK-VEGF4 receptor family, which includes VEGFR-1, VEGFR-2, and VEGFR-3, plays a crucial role in tissue regeneration by promoting angiogenesis, the formation of new blood vessels, and recruiting stem cells and immune cells. Machine learning, particularly graph neural networks (GNNs), has shown high accuracy in predicting these interactions. This study aims to predict drug-gene interactions of the RTK-VEGF4 receptor family in periodontal regeneration using graph neural networks.
View Article and Find Full Text PDFBackground: Diabetes is known to cause cognitive impairments and synaptic dysfunction. This study investigates the effects of (EO), (CT), Vitamin C, and metformin on cognitive function and synaptic density (SYN) in diabetic rats. This work aims to evaluate the impact of various treatments on spatial learning, memory, and SYN in a diabetic rat model.
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