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

2. 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

3. 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, years

4. MR Image processing

5. Brain extraction

6. Brain extraction
Brain Extraction Tool (BET) commonly used

7. Brain extraction
Brain Extraction Tool (BET) commonly used

8. Template based brain extraction
Advanced Normalization Tools (ANTS)
Uses diffeomorphic (super nonlinear) spatial normalisation

9. Image registration

10. ANTS diffeomorphic spatial normalisation

11. ANTS diffeomorphic spatial normalisation

12. ANTS diffeomorphic spatial normalisation
But catastrophes still happen

13. 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

14. 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

15. Brains are heteroscedastic

16. See, they’re different

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

19. 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

20. BRAINS atlases
BRAINS
MNI 152

21. Image registration

22. BRAINS atlases 1

23. BRAINS atlases
Normal
Alzheimer’s
Red=95th

26. White matter lesions

27. White matter lesions
Percentile 95 75 50 25 5 A

28. White matter lesions
Percentile 95 75 50 25 5 A

29. 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

30. 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

31. 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.

32. BRAINS vs. VBM

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

34. SINAPSE SPIRIT, MRC, Tony Watson
Thank you