brain images of normal subjects (brains) bank david alexander dickie dr dominic e. job

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 atlasesBRAINS

MNI 152

Image registration

1

0

BRAINS atlases

BRAINS atlases

Alzheimer’sNormal

Red=95th

White matter lesions

White matter lesions

95

75

50

25

5 A

Percentile

95

75

50

25

5 A

Percentile

White matter lesions

Percentiles of grey matter density in a normal ageing and Alzheimer’s disease subject

Alzheimer’sNormal

Alzheimer’s disease has lowest percentiles of GM in MTL

5th

95th

50th

25th

75th

Percentile

Bad

OK

Good

Percentiles of grey matter density in a normal ageing and Alzheimer’s disease subject

Alzheimer’sNormal

Alzheimer’s disease has lowest percentiles of GM in MTL

Alzheimer’s Control

5th

95th

50th

25th

75th

Percentile

Median percentile image of grey matter density in Alzheimer’s disease (n=49) and control (n=49) subjects

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