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The age of a subject can be estimated from the brain MR image by evaluating morphological changes in healthy aging. We consider using two-types of local features to estimate the age from T1-weighted images: handcrafted and automatically extracted features in this paper. The handcrafted brain local features are defined by volumes of brain tissues parcellated into 90 or 1,024 local regions defined by the automated anatomical labeling atlas. The automatically extracted features are obtained by using the convolutional neural network (CNN). This paper explores the difference between the handcrafted features and the automatically extracted features. Through a set of experiments using 1,099 T1-weighted images from a Japanese MR image database, we demonstrate the effectiveness of the proposed methods, analyze the effectiveness of each local region for age estimation and discuss its medical implication.

The aim of this study was to analyze correlations among the annual rate of gray matter volume change, age, gender, and cerebrovascular risk factors in 381 healthy community-dwelling subjects with a large age range by applying a longitudinal design over 6 years using brain magnetic resonance images (MRIs). Brain MRI data were processed with voxel-based morphometry using a custom template by applying diffeomorphic anatomical registration using the exponentiated lie algebra procedure. The annual rate of regional gray matter volume change showed significant positive correlations with age in several regions, including the bilateral temporal pole, caudate nucleus, ventral and dorsolateral prefrontal cortices, insula, hippocampus, and temporoparietal cortex, whereas significant negative correlations with age were observed in several regions including the bilateral cingulate gyri and anterior lobe of the cerebellum. Additionally, a significant age-by-gender interaction was found for the annual rate of regional gray matter volume change in the bilateral hippocampus. No significant correlations were observed between the annual rate of regional gray matter volume change and body mass index or systolic blood pressure. A significant positive correlation between the annual rate of gray matter volume change and age indicates that the region shows not linear but accelerated gray matter loss with age. Therefore, evaluating the annual rate of the gray matter volume change with age in healthy subjects is important in understanding how gray matter volume changes with aging in each brain region and in anticipating what cognitive functions are likely to show accelerated decline with aging., (Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.)

The aim of this study was to examine structural brain networks using regional gray matter volume, as well as to investigate changes in small-world and modular organization with normal aging. We constructed structural brain networks composed of 90 regions in young, middle, and old age groups. We randomly selected 350 healthy subjects for each group from a Japanese magnetic resonance image database. Structural brain networks in three age groups showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection cost. The small-world efficiency and node betweenness varied significantly and revealed a U- or inverted U-curve model tendency among three age groups. Results also demonstrated that structural brain networks exhibited a modular organization in which the connections between regions are much denser within modules than between them. The modular organization of structural brain networks was similar between the young and middle age groups, but quite different from the old group. In particular, the old group showed a notable decrease in the connector ratio and the intermodule connections. Combining the results of small-world efficiency, node betweenness and modular organization, we concluded that the brain network changed slightly, developing into a more distributed organization from young to middle age. The organization eventually altered greatly, shifting to a more localized organization in old age. Our findings provided quantitative insights into topological principles of structural brain networks and changes related to normal aging., (Copyright © 2011 Wiley Periodicals, Inc.)

Introduction: Whether the degree of white matter hyperintensities (WMHs) shows a significant correlation with the rate of global gray matter volume decline over a period following initial baseline measurement remains unclear. The purpose of the present study was to reveal the relationship between the degree of WMHs at baseline and the rate of global gray matter volume decline by applying a longitudinal design., Methods: Using a 6-year longitudinal design and magnetic resonance images of the brains of 160 healthy individuals aged over 50 years and living in the community, we analyzed the correlation between degree of WMHs using Fazekas scaling at baseline and rate of global gray matter volume decline 6 years later. To obtain the rate of global gray matter volume decline, we calculated global gray matter volume and intracranial volume at baseline and at follow-up using a fully automated method., Results: The annual percentage change in the gray matter ratio (GMR, APC(GMR)), in which GMR represents the percentage of gray matter volume in the intracranial volume, showed a significant positive correlation with the degree of deep WMHs and periventricular WMHs at baseline, after adjusting for age, gender, present history of hypertension, and diabetes mellitus., Conclusion: Our results suggest that degree of WMHs at baseline predicts the rate of gray matter volume decline 6 years later and that simple visual scaling of WMHs could contribute to predicting the rate of global gray matter volume decline.

The rate at which the volume of gray matter declines with normal aging, and whether gender or generational differences affect this rate, remain unclear. Using a longitudinal design over 6 years in 381 healthy community-dwelling individuals, we examined the rate of age-related loss in global gray matter volume, and how gender, generational and cerebrovascular risk factors affected this rate. We collected brain magnetic resonance images of the subjects, and calculated gray matter and intracranial volumes at baseline and follow-up using a fully automated technique. Using these volumes we then calculated the gray matter ratio (GMR), which measures gray matter volume as a percentage of the total intracranial volume. There were significant main effects of age, gender, and body mass index, and an age×gender interaction in the annual percentage change in the GMR (APC(GMR)). The APC(GMR) of younger women was lower than that in older women and men. Our results may help in understanding the mechanism(s) of normal brain aging, and in distinguishing neurodegenerative diseases from normal aging., (Copyright © 2009 Elsevier Inc. All rights reserved.)

This study applied volumetric analysis and voxel-based morphometry (VBM) of brain magnetic resonance (MR) images to assess whether correlations exist between global and regional gray/white matter volume and the cognitive functions of semantic memory and short-term memory, which are relatively well preserved with aging, using MR image data from 109 community-dwelling healthy elderly individuals. We used the Information and Digit Span subtests of the Wechsler Adult Intelligent Scale-Revised as measures of semantic memory and short-term memory, respectively. We found significant positive correlations between the gray matter ratio, the percentage of gray matter volume in the intracranial volume, and performance on the Digit Span subtest, and between the regional gray matter volumes of the bilateral anterior temporal lobes and performance on the Information subtest. No significant correlations between performance on the cognitive tests and white matter volume were found. Our results suggest that individual variability in specific cognitive functions that are relatively well preserved with aging is accounted for by the variability of gray matter volume in healthy elderly subjects., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Evaluating whole-brain or global gray matter volume decline rate is important in distinguishing neurodegenerative diseases from normal aging and in anticipating cognitive decline over a given period in non-demented subjects. Whether a significant negative correlation exists between baseline regional gray matter volume of several regions and global gray matter volume decline in the subsequent time period in healthy subjects has not yet been clarified. Therefore, we analyzed the correlation between baseline regional gray matter volumes and the rate of global gray matter volume decline in the period following baseline using magnetic resonance images of the brains of 381 healthy subjects by applying a longitudinal design over 6 years using voxel-based morphometry. As a result, the annual percentage change in gray matter ratio (GMR, APC(GMR)), in which GMR represents the percentage of gray matter volume in the intracranial volume, showed a significant negative correlation with the baseline regional gray matter volumes of the right posterior cingulate cortex/precuneus and the left hippocampus. Additionally, baseline regional gray matter volume of both the right PCC/precuneus and the left hippocampus significantly distinguished whether the APC(GMR) was above or below the mean of APC(GMR). Our results suggest that baseline regional gray matter volume predicts the rate of global gray matter volume decline in the subsequent period in healthy subjects. Our study may contribute to distinguishing neurodegenerative diseases from normal aging and to predicting cognitive decline., (Copyright © 2010 Elsevier Inc. All rights reserved.)

To determine the relationship between age and gray matter structure and how interactions between gender and hemisphere impact this relationship, we examined correlations between global or regional gray matter volume and age, including interactions of gender and hemisphere, using a general linear model with voxel-based and region-of-interest analyses. Brain magnetic resonance images were collected from 1460 healthy individuals aged 20-69 years; the images were linearly normalized and segmented and restored to native space for analysis of global gray matter volume. Linearly normalized images were then non-linearly normalized and smoothed for analysis of regional gray matter volume. Analysis of global gray matter volume revealed a significant negative correlation between gray matter ratio (gray matter volume divided by intracranial volume) and age in both genders, and a significant interaction effect of age × gender on the gray matter ratio. In analyzing regional gray matter volume, the gray matter volume of all regions showed significant main effects of age, and most regions, with the exception of several including the inferior parietal lobule, showed a significant age × gender interaction. Additionally, the inferior temporal gyrus showed a significant age × gender × hemisphere interaction. No regional volumes showed significant age × hemisphere interactions. Our study may contribute to clarifying the mechanism(s) of normal brain aging in each brain region.

Several studies using single photon emission tomography (SPECT) have shown changes in cerebral blood flow (CBF) with age, which were associated with partial volume effects by some authors. Some studies have also demonstrated gender-related differences in CBF. The present study aimed to examine age and gender effects on CBF SPECT images obtained using the 99mTc-ethyl cysteinate dimer and a SPECT scanner, before and after partial volume correction (PVC) using magnetic resonance (MR) imaging. Forty-four healthy subjects (29 males and 15 females; age range, 27-64 y; mean age, 50.0 +/- 9.8 y) participated. Each MR image was segmented to yield grey and white matter images and coregistered to a corresponding SPECT image, followed by convolution to approximate the SPECT spatial resolution. PVC-SPECT images were produced using the convoluted grey matter MR (GM-MR) and white matter MR images. The age and gender effects were assessed using SPM99. Decreases with age were detected in the anterolateral prefrontal cortex and in areas along the lateral sulcus and the lateral ventricle, bilaterally, in the GM-MR images and the SPECT images. In the PVC-SPECT images, decreases in CBF in the lateral prefrontal cortex lost their statistical significance. Decreases in CBF with age found along the lateral sulcus and the lateral ventricle, on the other hand, remained statistically significant, but observation of the spatially normalized MR images suggests that these findings are associated with the dilatation of the lateral sulcus and lateral ventricle, which was not completely compensated for by the spatial normalization procedure. Our present study demonstrated that age effects on CBF in healthy subjects could reflect morphological differences with age in grey matter.

The objectives of this study were to evaluate the correlations of the volumes of the gray matter and white matter with age, and the correlations of the tissue probabilities of the gray matter and white matter with age and several cerebrovascular risk factors. We obtained magnetic resonance (MR) images of the brain and clinical information from 769 normal Japanese subjects. We processed the MR images automatically by correcting for inter-individual differences in brain size and shape, and by segmenting the MR images into the gray matter and white matter. Volumetry of the brain revealed a significant negative correlation between the gray matter volume and age, which was not observed between white matter volume and age. Voxel-based morphometry showed that age, systolic blood pressure, and alcohol drinking correlated with the regional tissue probabilities of the gray matter and white matter.

A number of studies using single-photon emission tomography (SPET) have shown perfusion changes with age in several cortical and subcortical areas, which might distort the results of perfusion imaging studies of neuropsychiatric disorders. Technetium-99m labelled ethyl cysteinate dimer (ECD) and hexamethylpropylene amine oxime (HMPAO) are both used as markers of cerebral perfusion, but have different pharmacokinetics and retention patterns. The aim of this study was to determine whether age and gender effects on perfusion SPET differ depending on whether (99m)Tc-HMPAO or (99m)Tc-ECD is used. Forty-five subjects (20 male and 25 female, mean age 52.8+/-6.6 years) were assigned to (99m)Tc-HMPAO SPET (HMPAO group), and 39 subjects (24 male and 15 female, mean age 52.6+/-6.7 years) to (99m)Tc-ECD SPET (ECD group). SPET images were obtained about 10 min after intravenous injection of approximately 800 MBq (99m)Tc-HMPAO or (99m)Tc-ECD using the same SPET scanner. Three-dimensional volumetric magnetic resonance imaging was performed to as7sess morphological changes in the grey matter. All image processing and statistical analyses were performed using SPM99 software. An area in the right anterior frontal lobe showed an increase in perfusion with age only in the HMPAO group, whereas areas in the bilateral retrosplenial cortex showed decreases in perfusion with age only in the ECD group; neither group showed corresponding changes in the grey matter. The present study shows that different effects of age on perfusion are observed depending on whether (99m)Tc-HMPAO and (99m)Tc-ECD is used. This suggests that the results of perfusion SPET are differently confounded depending on the tracer used, and that perfusion SPET with these tracers has limitations when used in research on subtle perfusion changes.

The aim of this study was to investigate age-related changes in the topological organization of structural brain networks by applying a longitudinal design over 6 years. Structural brain networks were derived from measurements of regional gray matter volume and were constructed in age-specific groups from baseline and follow-up scans. The structural brain networks showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection costs. In the analysis of the global network properties, the local and global efficiency of the baseline scan were significantly lower compared to the follow-up scan. Moreover, the annual rate of change in local and global efficiency showed a positive and negative quadratic correlation with the baseline age, respectively; both curvilinear correlations peaked at approximately the age of 50. In the analysis of the regional nodal properties, significant negative correlations between the annual rate of change in nodal strength and the baseline age were found in the brain regions primarily involved in the visual and motor/control systems, whereas significant positive quadratic correlations were found in the brain regions predominately associated with the default-mode, attention, and memory systems. The results of the longitudinal study are consistent with the findings of our previous cross-sectional study: the structural brain networks develop into a fast distribution from young to middle age (approximately 50 years old) and eventually became a fast localization in the old age. Our findings elucidate the network topology of structural brain networks and its longitudinal changes, thus enhancing the understanding of the underlying physiology of normal aging in the human brain. [ABSTRACT FROM AUTHOR]