Brain Images of Normal Subjects (BRAINS) Bank David Alexander Dickie Dr Dominic E. Job

Background Age and disease affect brain structure The effects are disparate Much MRI data are needed ~300 normal ageing (>60yrs) subjects “Atlases” of the aged brain are limited

Background Brain Images of Normal Subjects (BRAINS) bank >1000 normal sbjs >60yrs BRAINS models and atlases calculate distributions (not assume) Data requires much image processing Pilot ~200 normal, ~200 AD sjbs, 60-94 years

MR Image processing

Brain extraction

Brain extraction Brain Extraction Tool (BET) commonly used

Brain extraction Brain Extraction Tool (BET) commonly used

Template based brain extraction Advanced Normalization Tools (ANTS) http://www.picsl.upenn.edu/ANTS/ Uses diffeomorphic (super nonlinear) spatial normalisation

Image registration

ANTS diffeomorphic spatial normalisation

ANTS diffeomorphic spatial normalisation

ANTS diffeomorphic spatial normalisation But catastrophes still happen

ANTS diffeomorphic spatial normalisation ANTS takes ~1 hour per subject (computer) Still requires by slice checking ~10 minutes checking per subject 460 subjects took ~2.5 months Catastrophes still happen >1000 subjects in full-scale study

Data driven brain volume models Statistical models oft used in brain imaging The general linear model (GLM) Assume data generation and distribution Transformations lose natural data, have risks, complexity Image banks support data driven models

Brains are heteroscedastic

See, they’re different

Data driven vs. general models DDPM has ~65% less error

Data driven brain voxel models Statistical voxel based morphometry (VBM) The general linear model (GLM) Assumes data generation and distribution Transformations lose natural data, smoothing Image banks support data driven models

BRAINS atlases BRAINS MNI 152

Image registration

BRAINS atlases 1

BRAINS atlases Normal Alzheimer’s Red=95th

White matter lesions

White matter lesions Percentile 95 75 50 25 5 A

White matter lesions Percentile 95 75 50 25 5 A

Percentiles of grey matter density in a normal ageing and Alzheimer’s disease subject 5th 25th 50th 75th 95th Alzheimer’s disease has lowest percentiles of GM in MTL

Percentiles of grey matter density in a normal ageing and Alzheimer’s disease subject Bad OK Good Alzheimer’s disease has lowest percentiles of GM in MTL

Median percentile image of grey matter density in Alzheimer’s disease (n=49) and control (n=49) subjects Alzheimer’s Control Percentile 5th 25th 50th 75th 95th Alzheimer’s has lowest percentiles of GM across the cortex, specifically hippocampus.

BRAINS vs. VBM

BRAINS vs. VBM Needs data Less assumptions Anatomical resolution Specific anatomy Individuals Size of differences Simpler

SINAPSE SPIRIT, MRC, Tony Watson Thank you