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Motion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising.
Invest Radiol
January 2025
From the Department of Radiology, Stanford University, Stanford, CA (K.W., M.J.M., A.M.L., A.B.S., A.J.H., D.B.E., R.L.B.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA (K.W.); GE HealthCare, Houston, TX (X.W.); GE HealthCare, Boston, MA (A.G.); and GE HealthCare, Menlo Park, CA (P.L.).
Objectives: Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off resonance-induced artifacts like distortion and blurring while cardiovascular motion-induced phase inconsistency leads to quantitative errors and signal loss, limiting its utility. Multishot DWI (msDWI) offers reduced image distortion and blurring relative to single-shot methods but increases sensitivity to motion artifacts. Motion-compensated diffusion-encoding gradients (MCGs) reduce motion artifacts and could improve motion robustness of msDWI but come with the cost of extended echo time, further reducing signal.
View Article and Find Full Text PDFPolyethylene Glycol (PEG) Application Triggers Plant Dehydration but Does Not Accurately Simulate Drought.
Plants (Basel)
December 2024
College of Science and Engineering, Biological Sciences, Flinders University, Adelaide, SA 5042, Australia.
Polyethylene glycol (PEG), especially at high molecular weights, is highly soluble in water, and these solutions have reduced water potential. It is convenient to use PEG in hydroponics (liquid nutrient solution) for experiments with plants. However, some authors have been found to describe the application of PEG to plants incorrectly, such as drought, dehydration, osmotic, or water stresses, which can mislead readers.
View Article and Find Full Text PDFEvaluating the impact of the Radiomics Quality Score: a systematic review and meta-analysis.
Eur Radiol
January 2025
School of Physics, Mathematics and Computing, University of Western Australia, Crawley, WA, Australia.
Article Synopsis
- The study aimed to conduct a systematic review and meta-analysis on the adherence of radiomics studies to the Radiomics Quality Score (RQS).
- A total of 130 systematic reviews were analyzed, revealing that while adherence to RQS has improved over time, many studies still struggle to provide high-quality evidence necessary for clinical application.
- Overall, only a small percentage of studies achieved a high RQS, indicating that the quality of radiomics research varies significantly between different imaging modalities.
Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning: A Prospective Study.
Korean J Radiol
January 2025
Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Objective: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2) and a conventional T2-w FSE Dixon sequence (T2) for breast magnetic resonance imaging (MRI).
Materials And Methods: This prospective study was conducted between November 2022 and April 2023 using a 3T scanner. Both T2 and T2 sequences were acquired for each patient.
Reader's digest version of scientific writing: comparative evaluation of summarization capacity between large language models and medical students in analyzing scientific writing in sleep medicine.
Front Artif Intell
December 2024
Department of Medical Education and Clinical Skills, California University of Science and Medicine, Colton, CA, United States.
Introduction: As artificial intelligence systems like large language models (LLM) and natural language processing advance, the need to evaluate their utility within medicine and medical education grows. As medical research publications continue to grow exponentially, AI systems offer valuable opportunities to condense and synthesize information, especially in underrepresented areas such as Sleep Medicine. The present study aims to compare summarization capacity between LLM generated summaries of sleep medicine research article abstracts, to summaries generated by Medical Student (humans) and to evaluate if the research content, and literary readability summarized is retained comparably.
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