Background: High-risk congenital melanocytic nevi (CMN) are associated with abnormalities of the central nervous system (CNS), prompting magnetic resonance imaging (MRI) screening guidelines.
Objective: Describe MRI brain and spine abnormalities in children with CMN and report trends between nevus features, MRI findings, and neurologic outcomes.
Methods: Retrospective review of individuals aged ≤18 years with an MRI of the brain and/or spine and at least 1 dermatologist-diagnosed CMN.
Results: Three hundred fifty-two patients were identified. Forty-six children had CMN that prompted an MRI of the brain and/or spine (50% male, average age at first image, 354.8 days). In these children, 8 (17%) had melanin detected in the CNS, of whom all had >4 CMN. One developed brain melanoma (fatal). In patients without CNS melanin, 4 had concerning imaging. Concerning MRI patients had more neurodevelopmental problems, seizures, neurosurgery, and death than individuals with unremarkable imaging. Three hundred six patients received MRIs for other reasons; none detected melanin. No children with only multiple small CMN (n = 15) had concerning imaging.
Limitations: Lack of a control group, cohort size, and retrospective methods.
Conclusion: MRI of the brain and spine is useful for detecting intervenable abnormalities in high-risk children. Healthy infants with few small CMN may not require screening MRI.
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http://dx.doi.org/10.1016/j.jaad.2022.05.062 | DOI Listing |
Sci Adv
January 2025
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Genes on the X chromosome are extensively expressed in the human brain. However, little is known for the X chromosome's impact on the brain anatomy, microstructure, and functional networks. We examined 1045 complex brain imaging traits from 38,529 participants in the UK Biobank.
View Article and Find Full Text PDFPLoS One
January 2025
Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada.
Altered neural signaling in fibromyalgia syndrome (FM) was investigated with functional magnetic resonance imaging (fMRI). We employed a novel fMRI network analysis method, Structural and Physiological Modeling (SAPM), which provides more detailed information than previous methods. The study involved brain fMRI data from participants with FM (N = 22) and a control group (HC, N = 18), acquired during a noxious stimulation paradigm.
View Article and Find Full Text PDFPLoS One
January 2025
Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Background: Assessing various types of dysfunction in cerebral palsy is a key factor in the treatment and rehabilitation of patients. The objective of this study was to use meta-analysis and systematic review to identify the specific white matter lesions and DTI metrics strongly associated with various types of dysfunction in cerebral palsy.
Methods: We conducted a literature search of PubMed, Embase, Cochrane Library and Web of Science databases to identify trials published that had evaluated the correlation between DTI metrics in sensorimotor pathways and function scores in cerebral palsy.
Brain
January 2025
Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, USA.
Resective epilepsy surgery can be an effective treatment for patients with medication-resistant focal epilepsy. Epilepsy resection consists of the surgical removal of an epileptic focus to stop seizure generation and disrupt the epileptic network. However, even focal surgical resections for epilepsy lead to widespread brain network changes.
View Article and Find Full Text PDFHum Brain Mapp
February 2025
BCBL - Basque Center on Cognition Brain and Language, Donostia - San Sebastián, Spain.
Population receptive field (pRF) mapping is a quantitative functional MRI (fMRI) analysis method that links visual field positions with specific locations in the visual cortex. A common preprocessing step in pRF analyses involves projecting volumetric fMRI data onto the cortical surface, typically leading to upsampling of the data. This process may introduce biases in the resulting pRF parameters.
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