Disclosures/Conflicts Consulting: GE Healthcare Bayer Abbott Elan/Janssen Synarc Genentech Merck

Disclosures/Conflicts

Consulting:

GE Healthcare

Bayer

Abbott

Elan/Janssen

Synarc

Genentech

Merck

ADNI PET Achievements

Literature-defined prespecified ROIs

Statistically defined ROIs

Multivariate approaches to prediction of conversion/decline

Cross-sectional and longitudinal PIB studies

Biomarker comparisons (PIB-CSF)

Statistically Defined ROIs in AD and MCI for Longitudinal Progression

AD

MCI

12 month trial, 25% treatment effect (power = 0.8, =

0.05, 2-tailed)

61 AD patients/arm

217 MCI patients/arm

Chen et al, Neuroimage 2010

26 MCI patients with a higher HCI71 MCI patients with a lower HCI

21 MCI patients with a smaller hippo vol76 MCI patients with a larger hippo vol

20 MCI patients with both a higher HCI & smaller hippo vol

38 MCI patients with neither a higher HCI or smaller hippo vol

Chen et al, submitted

Enrollment in ADNI PiB Studies to June 2010(All Data Are Available On The LONI Website)

Baseline – 103 Subjects at 14 PET Sites• NL: 19, 78±5 y/o, MMSE 29±1• MCI: 65, 75±8 y/o, MMSE 27±2• AD: 19, 73±9 y/o, MMSE 22±3

1 Yr Longitudinal Studies – 80 Subjects• NL: 17/19 (89%)• MCI: 50/65 (77%)• AD: 13/19 (68%)

PiB Baseline Entry Times• 20 subjects at ADNI true baseline• 69 subjects at ADNI 12 months• 14 subjects at ADNI 24 months

3 Yr Longitudinal Studies – 2 Subjects

• NL: 2• MCI: 0• AD: 0

2 Yr Longitudinal Studies – 39 Subjects

• NL: 11• MCI: 26• AD: 2

Total 224 PiB Scans

Mathis, Univ Pittsburgh

Baseline PiB

Longitudinal PiB

9/19 Normals PiB+47/65 MCI PiB+17/19 AD PiB+

MCI Converters (1-2 years)

21/47 PiB+ 3/18 PiB-

Mathis, Univ Pittsburgh

Extent of Hypometabolism as a Predictor of MCI Conversion

Timing of conversion

associated with more

hypometabolic voxels

Foster, Univ Utah

L Angular Gyrus

R Angular Gyrus

R Inf Temporal

Gyrus

L Inf Temporal

Gyrus

Post Cingulate

Gyrus

ROI Generation

Identification of ROIs from voxelwise analyses in the literature

Peak voxels plotted in MNI coordinates, smoothed, thresholded

Jagust et al, Neurology 2009

Landau et al, Neurology 2010

FDG AVLT

Combined = 12 fold higher risk of conversion

Prediction of Cognitive Decline in Normal ADNI Participants

Define normal/abnormal cutoffs using external samples

Classification of each subject as normal/abnormal on each marker

Determine whether normal/abnormal status predicts cognitive change

Participants

92 cognitively normal ADNI participants (FDG-PET, structural MRI, and ApoE genotyping)

Mean followup 2.7 +/- 0.8 yrs

Age 75.8 +/- 4.8 yrsEducation 15.9 +/- 3.2 yrsFemale 39%ApoE4 carriers 23%MMSE 28.9 +/- 1.1

FDG-PET (UC Berkeley)

Alzheimer’s patients

N = 35Age = 67.2 +/- 10.4

57% Female

Normal older subjects

N = 39Age = 73.1 +/- 5.8

62% Female

Mean FDG ROI uptake (relative to cerebellum/vermis region)

Sensitivity = 90%Specificity = 93%

Hippocampal volumes (UCSF)

Alzheimer’s patients

N = 51Age = 78.6 +/- 8.5

43% Female

Normal older subjects

N = 53Age = 74.3 +/- 7.5

53% Female

Bilateral hippocampal volume (adjusted for total intracranial volume)

Sensitivity = 94%Specificity = 95%

Normals stratified into high/low memory

No association between high/low

performer status and status on any of the

normal/abnormal markers

Neither group showed significant ADAS-cog

change

Median split of normals into high/low performers based on baseline performance on the Auditory Verbal

Learning Test (free recall)

Auditory Verbal Learning Test

FDG-PET imaging

Baseline

Hippocampal volume

age, sex, education

ApoE4 carrier status

Parameter estimate p-value

1.31 +/- 0.58

ns

0.03

0.99 +/- 0.66 0.03

ADAS-cog decline

Statistical analyses – multivariateLow performers

Abnormal hipp volume and ApoE4 carriers 2.3 pts/yr decline relative to normal

Defining the Technical Sources of Variability in ADNI PET Data

What is the effect of changing scanners in a longitudinal study?

How variable are longitudinal measurements on different scanners?

How does instrument variation compare to site variation?

What is the effect of processing on variation?

Effects of Scanner Switch in a Longitudinal Study

Rate of FDG Change (in ROI)

Normals MCI AD

Stable Switch Switch SwitchStable Stable

Variability by Scanner

Normal MCI AD

SD of Rate of Change

HRRT

616

7

2

2

The Future: ADNI2 and GO

Cross-sectional and longitudinal studies of A deposition with AV-45

Comparison with other biomarkers in prediction/multivariate approaches

Comparison with other biomarkers as outcomes

Replication of statistical ROI approach using identical ROI

Further investigate sources of variability

AcknowledgementsSusan LandauBob KoeppeEric ReimanKewei ChenChet Mathis

The ADNI Executive Committee, Site Investigators, ParticipantsNational Institute on Aging/Neil Buckholtz

ISAB Alzheimer’s Association

Julie PriceNorman FosterDan BandyDanielle HarveyNorbert SchuffMike Weiner