Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jfo.2024.104118 | DOI Listing |
MAGMA
January 2025
Translational Research Imaging Center (TRIC), Clinic of Radiology, University of Münster, Albert-Schweitzer-Campus 1, building A16, 48149, Münster, Germany.
Objective: Invasive multimodal fMRI in rodents is often compromised by susceptibility artifacts from adhesives used to secure cranial implants. We hypothesized that adhesive type, shape, and field strength significantly affect susceptibility artifacts, and systematically evaluated various adhesives.
Materials And Methods: Thirty-one adhesives were applied in constrained/unconstrained geometries and imaged with T2*-weighted EPI at 7.
J Neurol
January 2025
Western Institute of Neuroscience, Western University, London, Canada.
Background: Repeat neurological assessment is standard in cases of severe acute brain injury. However, conventional measures rely on overt behavior. Unfortunately, behavioral responses may be difficult or impossible for some patients.
View Article and Find Full Text PDFJ Neurol
January 2025
Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
Background: Tourette syndrome (TS) is a prevalent neurodevelopmental disorder with an uncertain etiology. Numerous neuroimaging studies have investigated patients with TS, but their conclusions remain inconsistent. The current study attempted to provide an unbiased statistical meta-analysis of published neuroimaging studies of TS.
View Article and Find Full Text PDFJ Neurol
January 2025
Department of Neurology, School of Medical Sciences, University of Campinas-UNICAMP, Universitaria "Zeferino Vaz", Rua Tessália Vieira de Camargo, 126. Cidade, Campinas, SP, 13083-887, Brazil.
Background: Skeletal and cardiac muscle damage have been increasingly recognized in female carriers of DMD pathogenic variants (DMDc). Little is known about cognitive impairment in these women or whether they have structural brain damage.
Objective: To characterize the cognitive profile in a Brazilian cohort of DMDc and determine whether they have structural brain abnormalities using multimodal MRI.
Osteoporos Int
January 2025
Academy for Engineering and Technology, Fudan University, Shanghai, China.
Unlabelled: This study utilized deep learning for bone mineral density (BMD) prediction and classification using biplanar X-ray radiography (BPX) images from Huashan Hospital Medical Checkup Center. Results showed high accuracy and strong correlation with quantitative computed tomography (QCT) results. The proposed models offer potential for screening patients at a high risk of osteoporosis and reducing unnecessary radiation and costs.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!