In this study, irregularity measures from MR images of corpus callosal brain structures in healthy and Mild Cognitive Impairment (MCI) conditions are extracted and their association with Cerebrospinal Fluid (CSF) biomarkers are analyzed. For this, MR images of healthy controls, Early MCI (EMCI) and Late MCI (LMCI) subjects are considered from a public database. The considered images are preprocessed and corpus callosal structure is segmented. Structural irregularity measures are extracted from the segmented regions using Fourier analysis. Statistical tests are performed to identify the significant features which can characterize the MCI stages. Association of these measures with CSF amyloid beta and tau concentrations are further investigated. Results demonstrate that Fourier spectral analysis is able to characterize the non-periodic variations in the corpus callosal structures of healthy, EMCI and LMCI MR images. The callosal irregularity measures increase as the disease progresses from healthy to LMCI. Phosphorylated tau concentrations in CSF demonstrate a positive correlation with irregularity measures across the diagnostic groups. Significant association of callosal measures and amyloid beta levels are found to be absent in MCI stages. As corpus callosal structural irregularities due to early MCI condition and their association with CSF markers remain uncharacterized in the literature, this study seems to be clinically significant for the timely intervention of pre-symptomatic MCI stages.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.neulet.2023.137329 | DOI Listing |
Med Biol Eng Comput
January 2025
Non-Invasive Imaging and Diagnostic Laboratory, Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, India.
Detection of early mild cognitive impairment (EMCI) is clinically challenging as it involves subtle alterations in multiple brain sub-anatomic regions. Among different brain regions, the corpus callosum and lateral ventricles are primarily affected due to EMCI. In this study, an improved deep canonical correlation analysis (CCA) based framework is proposed to fuse magnetic resonance (MR) image features from lateral ventricular and corpus callosal structures for the detection of EMCI condition.
View Article and Find Full Text PDFClin Neurol Neurosurg
December 2024
Department of Anatomy, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India. Electronic address:
Background: The complex structure and function of the cerebrum make it a key focus in neuroscience research. It develops from telencephalic vesicles through processes such as cell growth, division, and migration from the neuroepithelium's ventricular matrix, forming the six-layered isocortex or neocortex. Multipotent neuroepithelial cells give rise to both neuronal and glial precursors, which populate the cerebral cortex.
View Article and Find Full Text PDFACS Chem Neurosci
December 2024
Department of Radiology, The Second Affiliated Hospital, Zhejiang University of Medicine, Hangzhou 310009, China.
J Craniofac Surg
December 2024
Department of Anatomy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Background And Aims: The corpus callosum is recognized as the largest interhemispheric white matter structure, coordinating distinct functions of the brain. High-altitude environments may influence the structure of the corpus callosum. This study aims to evaluate the morphologic characteristics of the corpus callosum in Tibetans residing on the Qinghai-Tibet Plateau while investigating the effects of sex, age, and high-altitude exposure on its morphology.
View Article and Find Full Text PDFJAMA Netw Open
December 2024
Departments of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York City, New York.
Importance: Amidst an unprecedented opioid epidemic, identifying neurobiological correlates of change with medication-assisted treatment of heroin use disorder is imperative. White matter impairments in individuals with heroin use disorder (HUD) have been associated with drug craving, a reliable predictor of treatment outcomes; however, little is known about structural connectivity changes with inpatient treatment and abstinence in individuals with HUD.
Objective: To assess white matter microstructure and associations with drug craving changes with inpatient treatment in individuals with HUD (effects of time and rescan compared with controls).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!