scholarly journals Complementary Characteristics of Correlation Patterns in Morphometric Correlation Networks of Cortical Thickness, Surface Area, and Gray Matter Volume

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jin-Ju Yang ◽  
Hunki Kwon ◽  
Jong-Min Lee
Keyword(s):  
Surface Area ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Matter Volume ◽  
Correlation Networks

scholarly journals Normal age-related brain morphometric changes: nonuniformity across cortical thickness, surface area and gray matter volume?

2012 ◽  
Vol 33 (3) ◽  
pp. 617.e1-617.e9 ◽  
Author(s):  
Herve Lemaitre ◽  
Aaron L. Goldman ◽  
Fabio Sambataro ◽  
Beth A. Verchinski ◽  
Andreas Meyer-Lindenberg ◽  
...  
Keyword(s):  
Surface Area ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Matter Volume ◽  
Age Related

Analysis of structural brain MRI and multi-parameter classification for Alzheimer’s disease

2018 ◽  
Vol 63 (4) ◽  
pp. 427-437 ◽  
Author(s):  
Yingteng Zhang ◽  
Shenquan Liu
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Surface Area ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Roc Curves ◽  
Two Dimensional ◽  
Matter Volume ◽  
Parameter Combination

Abstract Incorporating with machine learning technology, neuroimaging markers which extracted from structural Magnetic Resonance Images (sMRI), can help distinguish Alzheimer’s Disease (AD) patients from Healthy Controls (HC). In the present study, we aim to investigate differences in atrophic regions between HC and AD and apply machine learning methods to classify these two groups. T1-weighted sMRI scans of 158 patients with AD and 145 age-matched HC were acquired from the ADNI database. Five kinds of parameters (i.e. cortical thickness, surface area, gray matter volume, curvature and sulcal depth) were obtained through the preprocessing steps. The recursive feature elimination (RFE) method for support vector machine (SVM) and leave-one-out cross validation (LOOCV) were applied to determine the optimal feature dimensions. Each kind of parameter was trained by SVM algorithm to acquire a classifier, which was used to classify HC and AD ultimately. Moreover, the ROC curves were depicted for testing the classifiers’ performance and the SVM classifiers of two-dimensional spaces took the top two important features as classification features for separating HC and AD to the maximum extent. The results showed that the decreased cortical thickness and gray matter volume dramatically exhibited the trend of atrophy. The key differences between AD and HC existed in the cortical thickness and gray matter volume of the entorhinal cortex and medial orbitofrontal cortex. In terms of classification results, an optimal accuracy of 90.76% was obtained via multi-parameter combination (i.e. cortical thickness, gray matter volume and surface area). Meanwhile, the receiver operating characteristic (ROC) curves and area under the curve (AUC) were also verified multi-parameter combination could reach a better classification performance (AUC=0.94) after the SVM-RFE method. The results could be well prove that multi-parameter combination could provide more useful classified features from multivariate anatomical structure than single parameter. In addition, as cortical thickness and multi-parameter combination contained more important classified information with fewer feature dimensions after feature selection, it could be optimum to separate HC from AD to take the top two important features of them to construct SVM classifiers in two-dimensional space. The proposed work is a promising approach suggesting an important role for machine-learning based diagnostic image analysis for clinical practice.

scholarly journals Effects of Meditation on Structural Changes of the Brain in Patients With Mild Cognitive Impairment or Alzheimer’s Disease Dementia

2021 ◽  
Vol 15 ◽  
Author(s):  
Madhukar Dwivedi ◽  
Neha Dubey ◽  
Aditya Jain Pansari ◽  
Raju Surampudi Bapi ◽  
Meghoranjani Das ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Brain Areas ◽  
Hippocampal Subfields ◽  
Matter Volume ◽  
The Right ◽  
The Brain

Previous cross-sectional studies reported positive effects of meditation on the brain areas related to attention and executive function in the healthy elderly population. Effects of long-term regular meditation in persons with mild cognitive impairment (MCI) and Alzheimer’s disease dementia (AD) have rarely been studied. In this study, we explored changes in cortical thickness and gray matter volume in meditation-naïve persons with MCI or mild AD after long-term meditation intervention. MCI or mild AD patients underwent detailed clinical and neuropsychological assessment and were assigned into meditation or non-meditation groups. High resolution T1-weighted magnetic resonance images (MRI) were acquired at baseline and after 6 months. Longitudinal symmetrized percentage changes (SPC) in cortical thickness and gray matter volume were estimated. Left caudal middle frontal, left rostral middle frontal, left superior parietal, right lateral orbitofrontal, and right superior frontal cortices showed changes in both cortical thickness and gray matter volume; the left paracentral cortex showed changes in cortical thickness; the left lateral occipital, left superior frontal, left banks of the superior temporal sulcus (bankssts), and left medial orbitofrontal cortices showed changes in gray matter volume. All these areas exhibited significantly higher SPC values in meditators as compared to non-meditators. Conversely, the left lateral occipital, and right posterior cingulate cortices showed significantly lower SPC values for cortical thickness in the meditators. In hippocampal subfields analysis, we observed significantly higher SPC in gray matter volume of the left CA1, molecular layer HP, and CA3 with a trend for increased gray matter volume in most other areas. No significant changes were found for the hippocampal subfields in the right hemisphere. Analysis of the subcortical structures revealed significantly increased volume in the right thalamus in the meditation group. The results of the study point out that long-term meditation practice in persons with MCI or mild AD leads to salutary changes in cortical thickness and gray matter volumes. Most of these changes were observed in the brain areas related to executive control and memory that are prominently at risk in neurodegenerative diseases.

Longitudinal assessment of subcortical gray matter volume, cortical thickness, and white matter integrity in HIV-positive patients

2016 ◽  
Vol 44 (5) ◽  
pp. 1262-1269 ◽  
Author(s):  
Diogo Goulart Corrêa ◽  
Nicolle Zimmermann ◽  
Gustavo Tukamoto ◽  
Thomas Doring ◽  
Nina Ventura ◽  
...  
Keyword(s):  
White Matter ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
White Matter Integrity ◽  
Hiv Positive ◽  
Longitudinal Assessment ◽  
Matter Volume

scholarly journals Cortical Thickness and Subcortical Gray Matter Volume in Pediatric Anxiety Disorders

2017 ◽  
Vol 42 (12) ◽  
pp. 2423-2433 ◽  
Author(s):  
Andrea L Gold ◽  
Elizabeth R Steuber ◽  
Lauren K White ◽  
Jennifer Pacheco ◽  
Jessica F Sachs ◽  
...  
Keyword(s):  
Anxiety Disorders ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Matter Volume ◽  
Pediatric Anxiety ◽  
Pediatric Anxiety Disorders

Mapping gray matter volume and cortical thickness in Alzheimer's disease

2010 ◽  
Author(s):  
Xiaojuan Guo ◽  
Ziyi Li ◽  
Kewei Chen ◽  
Li Yao ◽  
Zhiqun Wang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Matter Volume

scholarly journals Asymmetry Map of Human Brain in Young Adults

2020 ◽  
Author(s):  
Maryam Malekzadeh ◽  
Alireza Kashani
Keyword(s):  
Young Adults ◽  
White Matter ◽  
Human Brain ◽  
Surface Area ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Cortical Surface ◽  
Cortical Surface Area ◽  
Matter Volume ◽  
Cortical Regions

AbstractAlthough, asymmetry is a central organizational aspect of human brain, it has not been clearly described yet. Here, we have studied structural brain asymmetry in 1113 young adults using data obtained from Human Connectome Project. A significant rightward asymmetry in mean global cerebral cortical thickness, surface area and gray matter volume as well as volumes of cerebral white matter, cerebellar cortex and white matter, hippocampus, putamen, caudate nucleus, nucleus accumbens and amygdala was observed. Thalamus showed a leftward asymmetry. Regionally, most cerebral cortical regions show a significant rightward asymmetry in thickness. However, cortical surface area and gray matter volume are more evenly distributed between two hemispheres with almost half of the regions showing a leftward asymmetry. In addition, a strong correlation between cortical surface area and gray matter volume as well as their asymmetry indices was noted which results in concordant asymmetry patterns between cortical surface area and gray matter volume in most cortical regions.

scholarly journals Reduced gray matter volume and cortical thickness associated with traffic-related air pollution in a longitudinally studied pediatric cohort

PLoS ONE ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. e0228092 ◽  
Author(s):  
Travis Beckwith ◽  
Kim Cecil ◽  
Mekibib Altaye ◽  
Rachel Severs ◽  
Christopher Wolfe ◽  
...  
Keyword(s):  
Air Pollution ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Matter Volume
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