Keywords: Aging, Aging, CEST, NOE

Motivation: Demyelination and lipid degeneration occurs as the human brain ages.   Our motivation was to investigate the age-dependent variations of these lipids changes in subcortical gray matter regions using NOE_MTR in the brains of 15 subjects.

Goal(s): To determine the correlation of the human brain NOE_MTR metric with age.
 

Approach: We performed NOE MRI experiments on multiple subjects from ages (24Y-76Y) using NOE_MTR at 3T.

Results: The Spearman’s correlation coefficient indicates that NOE_MTR declines in several brain subregions with aging.

Impact: NOE_MTR can be used to track lipid changes in white and gray matter subregions of the aging brain.   

Keywords: Aging, Aging, thalamus

Motivation: Brain shrinkage does not happen to all areas uniformly and could be sex dependent.

Goal(s): We aimed to assess cross-sectionally the interactive effects of age and hypertension on the subcortical volumes and asymmetries in normal adult brains. 

Approach: Brain structural images were acquired in 147 normal volunteers at a 3T scanner.

Results: All volumes demonstrated negative correlation with age but only the thalamic volume in both sexes, and the putamen volume in women reached the threshold of statistical significance of P=0.007. The thalamic asymmetry was the only measure that showed positive correlation to hypertension in women.

Impact: Among seven subcortical structures examined, the thalamic volume demonstrated a negative association with age in normal adult brains. Further research is needed to correlate this finding with cognition.

Keywords: Aging, Brain

Motivation: Brain age models have not been well-tested in non-Caucasian populations or longitudinally.

Goal(s): We aimed to determine whether brain age models generalize to an Asian population and whether longitudinal changes in brain age associate with future cognition.

Approach: We applied a pretrained brain age model to Singaporean elderly and children, compared our results after finetuning the model, and examined cross-sectional and longitudinal associations with cognition.

Results: The model could be directly applied to elderly, but finetuning was necessary for children. The longitudinal change in brain age gap significantly associated with future executive function performance in both elderly and children.

Impact: We show that there is real potential for generalizing brain age models to diverse populations, and that the longitudinal change in brain age contains additional information about future executive function, compared to baseline brain age.

Keywords: Aging, Aging, Asymmetry

Motivation: The human brain demonstrates structural and functional asymmetries which have implications for ageing and the development of mental and neurological diseases. Age-relationships
of these asymmetries are largely unknown.

Goal(s): We aimed to map brain asymmetries from midlife to older ages and develop hemispheric
brain age (HBA) models, which consider apparent hemispheric differences.

Approach: We used structural and diffusion magnetic resonance imaging metrics (N=48,040, UK Biobank) to evaluate the age-relationship of brain asymmetry.

Results: Most metrics indicated asymmetry, which appears lower at higher age in white matter and
higher in grey matter. HBA reflects other brain ages and unique information of each hemisphere.

Impact: We present for the first time comprehensive analyses of brain asymmetries throughout midlife and older ages and establish a new conceptualisation of BrainAge. This ”hemispheric” BrainAge can serve as a marker of asymmetry by comparing left to right hemisphere-derived BrainAges.

Keywords: Aging, Aging, Longitudinal MRI

Motivation: Longitudinal MRI is used to quantify brain atrophy over time, yet more work is needed to understand factors that contribute these trajectories.

Goal(s): To use repeat anatomical MRI to predict subcortical volume changes at follow-up and test whether these data are more consistent in midlife adults than older adults.

Approach: We estimated subcortical MRI volumes in 100 midlife and 132 older adults and compared consistency between the two groups. 

Results: We found strong associations between initial and repeat MRI. The midlife group showed higher consistency in subcortical volume estimates than the older group.

Impact: We demonstrated that we could use baseline MRI estimates to predict subcortical anatomical change over 2.3 years within UK Biobank midlife and older populations, while the older adults showed lower consistency in MRI anatomical estimates than midlife adults.

Keywords: Aging, Quantitative Imaging, multi-scale, cortical morphometry, normative modelling

Motivation: Brains are fractal-like objects, with shape information distributed across length scales. Accurate and comprehensive descriptions of healthy ageing effects are needed to study and compare other processes such as neurological disorders.

Goal(s): We utilise fractal properties and multi-scale information to give a more thorough and accurate description of morphological changes due to healthy ageing.

Approach: We compute shape metrics as scale-dependent variables and infer ageing trajectories across the lifespan, contrasting scale-dependent and regional differences.

Results: Different length scales highlight different aspects of ageing effects, and regional differences in ageing trajectories are more pronounced at coarser scales.

Impact: Our multi-scale description of lifespan healthy ageing effects on cortical morphology reveals complementary information contained in different spatial scales and can be used as a normative model in future. Viewing morphometrics as functions of length scale reconceptualises quantitative morphometry.

Keywords: Aging, Aging

Motivation: This study probes the specific impact of white matter myelin integrity on processing speed in the aging brain, responding to the need for deeper insights into cognitive decline mechanisms.

Goal(s): Our primary objective is to elucidate the relationship between myelin integrity and longitudinal changes in processing speed.

Approach: Utilizing quantitative MRI, we performed a retrospective longitudinal analysis correlating myelin water fraction (MWF) values with processing speed measurements.

Results: Significant correlations were found between decreased myelin integrity and faster decline in processing speed over the study period, affirming myelin integrity as a key factor in cognitive aging.

Impact: This research spotlights the pivotal role of myelin integrity in cognitive aging, potentially shifting existing neuroprotective strategies. Clinicians may now consider myelin preservation in cognitive health assessments, while researchers explore myelin restoration as a viable intervention for age-related cognitive decline.

Keywords: Aging, Neuro, Neurological disorders

Motivation: Understanding brain age of healthy people and patients with neurological diseases is crucial for clinical application. 

Goal(s): To characterize people with advanced brain age and explore brain aging patterns across neurological disorders.

Approach: Through a predicted brain age model using deep learning, we investigated the correlations between advanced brain aging and age-related deterioration in healthy individuals, and explored the correlation with clinical variables across neurological disorders.

Results: Healthy individuals with advanced brain aging have higher white matter hyperintensity burdens and lower brain region volumes. Brain age increases in patients with neurological disorders and has more cognitive decline and physical disability.

Impact: The brain age model using deep learning enables identifying individuals at risk for advanced brain aging in the normal-aging population and shows advanced brain aging across neurological diseases, which can be a biomarker for cognitive impairment and/or physical disability.

Keywords: Aging, Aging, dw-mrs, diffusion, brain, microstructure, metabolite

Motivation: Healthy brain aging involves intricate changes in both brain structure and function, including alterations in cellular composition and microstructure across various regions. We focus on microstructural changes by studying normative age-trajectories in cerebral and cerebellar gray matter in human brain.

Goal(s): Investigating microstructural changes in cerebral and cerebellar gray matter in human brain and provide benchmarks for the normative age-trajectories of higher-order metabolite diffusion properties.

Approach: Using DW-MRS and diffusion modelling for characterizing microstructural changes 

Results: Our findings provide benchmarks for identifying anomalies in the diffusion properties of major brain metabolites, stemming from pathological mechanisms altering both the brain microstructure and cellular composition

Impact: This work investigates microstructural changes with aging in gray matter cerebral and cerebellar cortex in human brain DW-MRS. Moreover, it offers the first normative age-trajectories of metabolite diffusion characteristics, setting benchmark for detection and characterization of microstructural anomalies.

Keywords: Preclinical Image Analysis, Alzheimer's Disease, Asymptomatic Stage; Cognitive Decline; Progression Prediction;

Motivation: Predicting the conversion from cognitive normal to mild cognitive impairment (MCI) at the asymptomatic stage is challenging.

Goal(s): To investigate whether longitudinal alteration in brain structure can provide valuable information for normal-to-MCI conversion prediction.

Approach: We conducted a 7-year longitudinal study on 222 community-dwelling elderly and built a two-stage intelligent prediction model to establish the mapping relationship from the baseline to 7-year changes, using brain T1 MRI scans and comprehensive neuropsychological tests.

Results: The model, with forecasted 7-year changed features, achieved promising conversion predictions (accuracy=73.8%). Cortical thickness changes, particularly in the visual and default mode cortices, played a significant role in prediction.

Impact: Long-term (7-year) brain cortical changes could be predicted and further used to help disease progression prediction for community elderly. Leveraging pre-built predictive model, physicians can evaluate the progression risk at the preclinical phase, well before the onset of Alzheimer's disease.

Keywords: Aging, Brain, Motion, Artifacts, Diffusion

Motivation: Subject motion can cause  artifacts in MR images and biases in subsequent quantification. 

Goal(s): A thorough characterization of motion across multiple cohorts/consortiums has not been performed, particularly with diffusion MRI data. 

Approach: We use diffusion MRI data from 14,440 subjects from 10 consortiums (aged 0-100) to characterize (1) how much subjects move during scanning; (2) what kind of head motion is most common; (3) whether motion increases as acquisition proceeds; (4) if motion is associated with age; or (5) with cognitive decline. 

Results: Knowledge of the magnitude and direction of motion provides guidance for motion mitigation strategies and informed preprocessing strategies.  

Impact: Subject motion induces artifacts and biases in MR images. Characterizing motion magnitude and directions, as well as motion correlates, informs and improves motion mitigation strategies and image processing pipelines. 

Keywords: Aging, Aging, Human thalamus, Other diffusion techniques

Motivation: Volumetric and microstructural characterization of thalamic nuclei is currently meeting growing interest in neuroimaging. Thalamic nuclei microstructural features, especially, may be used as biomarkers to study changes in both normal aging and degenerative diseases.

Goal(s): Quantify age-related differences in volumetry and microstructure of thalamic nuclei

Approach: We used 3T structural MRI (volumetry) and Diffusion Kurtosis Imaging (microstructure)

Results: Our main result is that thalamic volumetric atrophy effects related to healthy aging are significant and stronger than those given by microstructure estimates. 

Impact: Macroscopic atrophy is more sensitive to healthy aging differences relative to microstructure effects derived from Diffusion Kurtosis Imaging. 

Keywords: Aging, Aging, fMRI, White matter, Resting state, Cognition

Motivation: Unraveling how age-related changes in brain structure and function affect cognitive functions.

Goal(s): To determine the mediation role of white matter functional metrics in cognitive decline with aging.

Approach: Employing fMRI, graph theory, and mediation analysis to assess how the effect of changes in WM BOLD activity with age influence or reflect cognitive performance.

Results: Identified significant white-matter mediators linking age to cognitive performance.

Impact: Contributes a fresh perspective to our understanding of the functional architecture of the aging brain.

Keywords: Aging, Aging

Motivation: MRF is a promising quantitative tool to acquire T1 and T2 values simultaneously. However, its regional variations with advancing age needs to be better eluciated.

Goal(s): To determine the age-dependent variations in MRF T1 and T2 relaxation maps, and to characterize the  quantitative properies of the brain tissue. 

Approach: MRF maps were acuiqred in 138 asymptomatic volunteers. Voxel-wise correlation analyses were performed, T1 and T2 values were extracted from various regions to further demonstrate their correlations with age.

Results: Both T1 and T2 values in extensive regions increased with age. But T2 drops in bilateral temporal poles, insular cortices, putamen, and corticospinal tract.

Impact: MRF was introduced as an in vivo quantitation tool for normative brain imaging. It shows great potential in quantifying differences in brain parenchyma related to age variations and precise tissue segmentation that can be applied in radiomics studies.

Keywords: Aging, Aging, Cohort study; Body mass index; Obesity; Neuroimaging; Mendelian randomization

Motivation: The causal relationship between BMI and brain health remains unclear.

Goal(s): This study aimed to demonstrate the effect of cumulative BMI on neuroimaging features in adults of different ages and verify the causal relationship.

Approach: This study was based on the KaiLuan Study that began in 2006. We also performed two-sample Mendelian randomization analysis using genetic data from 681,275 individuals. 

Results: For adults aged under 45 years but BMI > 26.2 kg/m²  corresponded to 12.0 years of brain aging. Genetic analysis indicated causal relationships among high BMI, smaller volume of the cerebral parenchyma, and higher fractional anisotropy in projection fibers. 

Impact: High BMI is causally associated with smaller brain volume and abnormal microstructural integrity in projection fibers, especially in young adults. These findings provide a basis for future brain health promotion and disease prevention strategies. 

Keywords: Aging, Aging, microstructure, µFA, tensor-valued encoding, auditory system, tractography, white matter

Motivation: Age-related hearing loss is widespread, but the impact of aging on the central auditory pathway's structure and function is poorly understood.

Goal(s): This study aims to characterise the microstructural signatures of aging in the acoustic radiations. 

Approach: Forty-five participants between 18-76 years underwent diffusion weighted MRI. Tractography was used to delineate each subject's acoustic radiations, and maps of diffusion MRI metrics and biophysical model parameters were computed. 

Results: Mean isotropic kurtosis and axonal volume were found to increase with age in the bilateral acoustic radiations. The increase in apparent axonal volume fraction contradicts previous studies and expectations of decreased fibre integrity with age. 

Impact: The aging-related microstructural changes to the central auditory pathway shown here may have functional consequences in terms of hearing ability and hearing rehabilitation strategies among the elderly. Future studies could incorporate electrophysiological measurements to assess this microstructure-function relationship.