Objective: To examine the relationship between white matter hyperintensities and headache.
Methods: White matter hyperintensities burden was assessed semi-quantitatively using Fazekas and Scheltens scales, and by manual and automated volumetry of MRI in a sub-study of the general population-based Nord-Trøndelag Health Study (HUNT MRI). Using validated questionnaires, participants were categorized into four cross-sectional headache groups: Headache-free (n = 551), tension-type headache (n = 94), migraine (n = 91), and unclassified headache (n = 126). Prospective questionnaire data was used to further categorize participants into groups according to the evolution of headache during the last 12 years: Stable headache-free, past headache, new onset headache, and persistent headache. White matter hyperintensities burden was compared across headache groups using adjusted multivariate regression models.
Results: Individuals with tension-type headache were more likely to have extensive white matter hyperintensities than headache-free subjects, with this being the case across all methods of white matter hyperintensities assessment (Scheltens scale: Odds ratio, 2.46; 95% CI, 1.44-4.20). Migraine or unclassified headache did not influence the odds of having extensive white matter hyperintensities. Those with new onset headache were more likely to have extensive white matter hyperintensities than those who were stable headache-free (Scheltens scale: Odds ratio, 2.24; 95% CI, 1.13-4.44).
Conclusions: Having tension-type headache or developing headache in middle age was linked to extensive white matter hyperintensities. These results were similar across all methods of assessing white matter hyperintensities. If white matter hyperintensities treatment strategies emerge in the future, this association should be taken into consideration.
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http://dx.doi.org/10.1177/0333102418764891 | DOI Listing |
BMC Neurol
January 2025
Faculty of Medicine, Department of Neurology, Al-Quds University, Jerusalem, Palestine.
Background: Vanishing white matter disease (VWMD) is a rare autosomal recessive leukoencephalopathy. It is typified by a gradual loss of white matter in the brain and spinal cord, which results in impairments in vision and hearing, cerebellar ataxia, muscular weakness, stiffness, seizures, and dysarthria cogitative decline. Many reports involve minors.
View Article and Find Full Text PDFBehav Brain Res
January 2025
Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, United States of America.
Background: Thalamocortical functional and structural connectivity alterations may contribute to clinical phenotype of Autism Spectrum Disorder. As previous studies focused mainly on thalamofrontal connections, we comprehensively investigated between-group differences of thalamic functional networks and white matter pathways projecting also to temporal, parietal, occipital lobes and their associations with core and co-occurring conditions of this population.
Methods: A total of 38 children (19 with Autism Spectrum Disorder) underwent magnetic resonance imaging and behavioral assessment.
Neuroimage
January 2025
College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China; Shenzhen Research Institute, Nanjing University of Aeronautics and Astronautics, Shenzhen, 518038, China; Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing, 210016, China. Electronic address:
The structural-functional brain connections coupling (SC-FC coupling) describes the relationship between white matter structural connections and the corresponding functional activation or functional connections. It has been widely used to identify brain disorders. However, the existing research on SC-FC coupling focuses on global and regional scales, and few studies have investigated the impact of brain disorders on this relationship from the perspective of multi-brain region cooperation (i.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China; Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women's Diseases (Yantai Yuhuangding Hospital), Yantai, Shandong 264000, PR China; Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China. Electronic address:
Purpose: To elucidate the structural-functional connectivity (SC-FC) coupling in white matter (WM) tracts in patients with major depressive disorder (MDD).
Methods: A total of 178 individuals diagnosed with MDD and 173 healthy controls (HCs) were recruited for this study. The Euclidean distance was calculated to assess SC-FC coupling.
BMC Neurol
January 2025
Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, School of Medicine, College of Medicine, National Sun Yat-Sen University, No. 123 Ta-Pei Road, Niao-Sung Dist, Kaohsiung, 83305, Taiwan.
Background And Purpose: White matter hyperintensities in brain MRI are key indicators of various neurological conditions, and their accurate segmentation is essential for assessing disease progression. This study aims to evaluate the performance of a 3D convolutional neural network and a 3D Transformer-based model for white matter hyperintensities segmentation, focusing on their efficacy with limited datasets and similar computational resources.
Materials And Methods: We implemented a convolution-based model (3D ResNet-50 U-Net with spatial and channel squeeze & excitation) and a Transformer-based model (3D Swin Transformer with a convolutional stem).
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