We investigated whether device-measured sleep parameters are associated with cortical thickness in older adults with probable mild cognitive impairment (MCI). We performed a cross-sectional, exploratory analysis of sleep and structural MRI data. Sleep data were collected with MotionWatch8© actigraphy over 7 days. We computed average and variability for sleep duration, sleep efficiency, and fragmentation index. T1-weighted MRI scans were used to measure cortical thickness in FreeSurfer. We employed surface-based analysis to determine the association between sleep measures and cortical thickness, adjusting for age, sex, Montreal Cognitive Assessment (MoCA) score, and sleep medication use. Our sample included 113 participants (age = 73.1 [5.7], female = 72 [63.7 %]). Higher fragmentation index variability predicted lower cortical thickness in the left superior frontal gyrus (cluster size = 970.9 mm, cluster-wise p = 0.017, cortical thickness range = 2.1 mm to 3.0 mm), adjusting for age, sex, MoCA, and sleep medication. Our results suggest that higher variability in sleep fragmentation, an indicator of irregular sleep pattern, is linked to lower cortical thickness. Future longitudinal studies are needed to determine the directionality of these associations.
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http://dx.doi.org/10.1016/j.exger.2022.111923 | DOI Listing |
J Bone Miner Res
January 2025
Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
The socioeconomic burden of hip fractures, the most severe osteoporotic fracture outcome, is increasing and the current clinical risk assessment lacks sensitivity. This study aimed to develop a method for improved prediction of hip fracture by incorporating measurements of bone microstructure and composition derived from high-resolution peripheral quantitative computed tomography (HR-pQCT). In a prospective cohort study of 3028 community-dwelling women aged 75 to 80, all participants answered questionnaires and underwent baseline examinations of anthropometrics and bone by dual x-ray absorptiometry (DXA) and HR-pQCT.
View Article and Find Full Text PDFBrain Struct Funct
January 2025
Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, 670 W Baltimore St, HSF III, R1173, Baltimore, MD, 21202, USA.
The brain entropy (BEN) reflects the randomness of brain activity and is inversely related to its temporal coherence. In recent years, BEN has been found to be associated with a number of neurocognitive, biological, and sociodemographic variables such as fluid intelligence, age, sex, and education. However, evidence regarding the potential relationship between BEN and brain structure is still lacking.
View Article and Find Full Text PDFHum Brain Mapp
February 2025
Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA.
Neurodegeneration is presumed to be the pathological process measure most proximal to clinical symptom onset in Alzheimer Disease (AD). Structural MRI is routinely collected in research and clinical trial settings. Several quantitative MRI-based measures of atrophy have been proposed, but their low correspondence with each other has been previously documented.
View Article and Find Full Text PDFJ Ultrasound Med
January 2025
Department of Radiodiagnosis, Government Medical College and Hospital, Chandigarh, India.
Objectives: To determine the efficacy of quantitative shear wave elastography in differentiating benign and malignant axillary lymph nodes (ALN).
Methods: Exactly 127 lymph nodes from 127 patients with clinically palpable axillary swelling were examined by both B-mode sonography and elastography from November 2022 to March 2024. Gray-scale sonograms were evaluated based on: the short-axis diameter, shape, hilum, maximum cortical thickness, and border of the ALN.
Front Aging Neurosci
January 2025
Department of Neurology, West China Hospital of Sichuan University, Chengdu, China.
Purpose: Differentiating between Alzheimer's disease (AD) and frontotemporal dementia (FTD) can be challenging due to overlapping cognitive and behavioral manifestations. Evidence regarding non-invasive and early-stage biomarkers remains limited. Our aim was to identify retinal biomarkers for the risk of AD and FTD in populations without dementia and explore underlying brain structural mechanisms.
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