In situ in vivo and ex vivo study of the aging human brain: towards creating an MRI and histology brain template averaging 100 cases

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The study of the normal aging brain is accomplished using brains that people donate to science after they die, which is called ex vivo study of the brain. The microscopic study of ex vivo brains allows to understand the structure of any given region, which is the basis of several neuroscientific research studies. However, we cannot study the brain of healthy living people (in vivo) using microscopy. One method to study the brain in vivo is magnetic resonance imaging (MRI) using powerful machines that provide very high image resolution (7 Tesla MRI scanners). The downside of using MRI alone is the lack of certainty of which cells are responsible for a given contrast (color) on the MRI. To solve this, we study first the brain ex vivo using MRI (in our proposed program we will use the brain of donors of the Anatomy Department of our university), and then microscopy. Finally, we can use previous (in vivo) MRI scans of donors, available through their medical files, to translate our ex vivo MRI findings, to in vivo MRI findings. Our research program will assess four different ways to conserve the brain inside the head for better MRI results and will compare those results against the most utilized way of conservation employed by brain banks, which remove the brains and force the MRI scanning of the brains outside the head (ex situ) inside plastic containers filled with fluid (special fluid that does not produce a color on the MRI scan). Scanning brains ex situ introduces deformations of the tissue that complicate its comparison with the corresponding histology slices and with in vivo scans. Our program proposes the deployment of standard procedures to conserve and scan brains ex vivo and in situ, improving the comparative study with histology of the specimens, and with scans of living participants. Our scans will be then used to create an average MRI ex vivo-in situ template with histological correlates, which will be open-source and available to the neuroscientific community.