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Recent years have seen growing interest in measuring axonal water fraction (AWF) using the spherical mean diffusion weighted signal, but information about the reproducibility of this method is needed before applying it in large-scale studies. The current study aims to evaluate the reproducibility of AWF derived from the spherical mean signal method. This retrospective study analyzed the Human Connectome Project (HCP) test-retest diffusion data of ten healthy adults. The diffusion scan was performed two times for each subject. Diffusion tensor imaging-based fractional anisotropy (FA) was calculated with b = 1000 s/mm. AWF was calculated with b = 3000 s/mm using the spherical mean signal method. Gradient nonlinearities were corrected in both methods. Reproducibility was assessed using the reproducibility error, which is the percent absolute change relative to the mean. The mean reproducibility error of fractional anisotropy (FA) is 9.7 ± 1.0% in white matter and 18.0 ± 2.0% in gray matter. The mean reproducibility error of AWF is 4.6 ± 0.6% in white matter and 7.0 ± 1.5% in gray matter. Spherical mean signal-based AWF is more reproducible than FA for the HCP high resolution, low signal-to-noise ratio diffusion data.
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http://dx.doi.org/10.1016/j.mri.2019.08.024 | DOI Listing |
Lab Anim Res
September 2025
Korea Model Animal Priority Center (KMPC), Seoul, Republic of Korea.
Background: Laboratory animal veterinarians play a crucial role as a bridge between the ethical use of laboratory animals and the advancement of scientific and medical knowledge in biomedical research. They alleviate pain and reduce distress through veterinary care of laboratory animals. Additionally, they enhance animal welfare by creating environments that mimic natural habitats through environmental enrichment and social associations.
View Article and Find Full Text PDFJ Refract Surg
September 2025
From the Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Purpose: To determine the accuracy of a new machine learning-based open-source IOL formula (PEARLS-DGS) in 100 patients who underwent uncomplicated cataract surgery and had a history of laser refractive surgery for myopic defects.
Methods: The setting for this retrospective study was HUMANITAS Research Hospital, Milan, Italy. Data from 100 patients with a history of photorefractive keratectomy or laser in situ keratomileusis were retrospectively analyzed to assess the accuracy of the formula.
BMJ Oncol
August 2025
Radiation Medicine Program, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada.
Background: The advent of artificial intelligence (AI) tools in oncology to support clinical decision-making, reduce physician workload and automate workflow inefficiencies yields both great promise and caution. To generate high-quality evidence on the safety and efficacy of AI interventions, randomised controlled trials (RCTs) remain the gold standard. However, the completeness and quality of reporting among AI trials in oncology remains unknown.
View Article and Find Full Text PDFAdv Pharm Bull
July 2025
Department of Telecommunications & Systems Engineering, Universitat Autònoma de Barcelona, Sabadell, 08202, Spain.
Purpose: This study explores the potential of generative AI models to aid experts in developing scripts for pharmacokinetic (PK) models, with a focus on constructing a two-compartment population PK model using data from Hosseini et al.
Methods: Generative AI tools ChatGPT v3.5, Gemini v2.
Eur J Sport Sci
October 2025
Department of Intervention Research in Exercise Training, German Sport University Cologne, Cologne, Germany.
The concurrent validity of lactate thresholds (LT1, LT2) and between-day reliability data from the rowing-specific heart rate variability (HRV)-based thresholds (HRVT) were examined. Thus, 21 rowers (19.6 ± 2.
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