Objective: The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the elbow regarding image quality and visualization of anatomy.
Materials And Methods: Between October 2020 and June 2021, seventeen participants (eight patients, nine healthy subjects; mean age: 43 ± 16 (20-70) years, eight men) were prospectively included in this study. Each patient underwent two examinations: standard MRI, including TSE sequences reconstructed with a generalized autocalibrating partial parallel acquisition reconstruction (TSE), and prospectively undersampled TSE sequences reconstructed with a DL reconstruction (TSE). Two radiologists evaluated the images concerning image quality, noise, edge sharpness, artifacts, diagnostic confidence, and delineation of anatomical structures using a 5-point Likert scale, and rated the images concerning the detection of common pathologies.
Results: Image quality was significantly improved in TSE (mean 4.35, IQR 4-5) compared to TSE (mean 3.76, IQR 3-4, = 0.008). Moreover, TSE showed decreased noise (mean 4.29, IQR 3.5-5) compared to TSE (mean 3.35, IQR 3-4, = 0.004). Ratings for delineation of anatomical structures, artifacts, edge sharpness, and diagnostic confidence did not differ significantly between TSE and TSE ( > 0.05). Inter-reader agreement was substantial to almost perfect (κ = 0.628-0.904). No difference was found concerning the detection of pathologies between the readers and between TSE and TSE. Using DL, the acquisition time could be reduced by more than 35% compared to TSE.
Conclusion: TSE provided improved image quality and decreased noise while receiving equal ratings for edge sharpness, artifacts, delineation of anatomical structures, diagnostic confidence, and detection of pathologies compared to TSE. Providing more than a 35% reduction of acquisition time, TSE may be clinically relevant for elbow imaging due to increased patient comfort and higher patient throughput.
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http://dx.doi.org/10.3390/diagnostics13172747 | DOI Listing |
Plant Dis
January 2025
University of California Davis, Cooperative Extension, Napa, California, United States;
The timely detection of viral pathogens in vineyards is a critical aspect of management. Diagnostic methods can be labor-intensive and may require specialized training or facilities. The emergence of artificial intelligence (AI) has the potential to provide innovative solutions for disease detection but requires a significant volume of high-quality data as input.
View Article and Find Full Text PDFSurg Technol Int
January 2025
Department of Psychiatry and Narcology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russian Federation.
Pelvic Venous Disorder (PEVD) and May-Thurner syndrome (MTS) represent relatively understudied vascular issues that can significantly impact patients' quality of life. This study aims to evaluate the efficacy of surgical treatment for PEVD and MTS, conduct a comparative analysis of outcomes, and determine the practical significance of different therapeutic approaches. The study was conducted from 2019 to 2022 in Moscow, Russia, encompassing two outpatient clinics.
View Article and Find Full Text PDFMagn Reson Med
January 2025
Department 8.1 - Biomedical Magnetic Resonance, Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.
Purpose: To develop a low-cost, high-performance, versatile, open-source console for low-field MRI applications that can integrate a multitude of different auxiliary sensors.
Methods: A new MR console was realized with four transmission and eight reception channels. The interface cards for signal transmission and reception are installed in PCI Express slots, allowing console integration in a commercial PC rack.
PLoS One
January 2025
Department of Business Economics and Management, Masaryk University Faculty of Economics and Administration, Brno, Czech Republic.
The subject of this paper is modeling customer satisfaction in the mobile telecommunication industry following the Covid-19 pandemic. Based on standard customer satisfaction models, a specialized model tailored for the mobile telecommunication industry has been developed to account for its unique characteristics, including market concentration. This model was created within the Slovakian context using the Structural Equation Modelling method.
View Article and Find Full Text PDFJAMA Neurol
January 2025
Department of Neurology, UAB Heersink School of Medicine, University of Alabama at Birmingham, Birmingham.
Importance: In the Atrial Cardiopathy and Antithrombotic Drugs in Prevention After Cryptogenic Stroke (ARCADIA) randomized clinical trial, anticoagulation did not prevent recurrent stroke among patients with a recent cryptogenic stroke and atrial cardiopathy. It is unknown whether anticoagulation prevents covert infarcts in this population.
Objective: To test the use of apixaban vs aspirin for prevention of nonlacunar covert infarcts after cryptogenic stroke in patients with atrial cardiopathy.
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