ABSTRACT
In this study, we perform a comparative analysis of automated image segmentation of subcortical structures in the elderly brain. Manual segmentation is very time-consuming and automated methods are gaining importance as a clinical tool for diagnosis. The two most commonly used software libraries for brain segmentation -FreeSurfer and FSL- are put to work in a large dataset of 4,028 magnetic resonance imaging (MRI) scans collected for this study. We find a lack of linear correlation between the segmentation volume estimates obtained from FreeSurfer and FSL. On the other hand, FreeSurfer volume estimates tend to be larger thanFSL estimates of the areas putamen, thalamus, amygdala, caudate, pallidum, hippocampus, and accumbens. The characterization of the performance of brain segmentation algorithms in large datasets as the one presented here is a necessary step towards partially or fully automated end-to-end neuroimaging workflow both in clinical and research settings.
Subject(s)
Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Aged , Algorithms , Brain/diagnostic imaging , Brain/pathology , Humans , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Neuroimaging/methodsABSTRACT
The progressive aging of the population represents a challenge for society. In particular, a strong increase in the number of people over 90 is expected in the next two decades. As this phenomenon will lead to an increase in illness and age-related dependency, the study of long-lived people represents an opportunity to explore which lifestyle factors are associated with healthy aging and which with the emergence of age-related diseases, especially Alzheimer's type dementia. The project "Factors associated with healthy and pathologically aging in a sample of elderly people over 90 in the city of Madrid" (MADRID+90) brings together a multidisciplinary research team in neurodegenerative diseases that includes experts in epidemiology, neurology, neuropsychology, neuroimaging and computational neuroscience. In the first phase of the project, a stratified random sampling was carried out according to the census of the city of Madrid followed by a survey conducted on 191 people aged 90 and over. This survey gathered information on demographics, clinical data, lifestyles and cognitive status. Here, the main results of that survey are showed. The second phase of the project aims to characterize individual trajectories in the course of either healthy and pathological aging, from a group of 50 subjects over 90 who will undergo a comprehensive clinical examination comprised of neurological and cognitive testing, MRI and EEG. The ultimate goal of the project is to characterize the biophysical and clinical profiles of a population that tends to receive little attention in the literature. A better understanding of the rapidly increasing group of nonagenarians will also help to design new policies that minimize the impact and future social and economic consequences of rapidly aging societies.