disclosures/conflicts consulting: ge healthcare bayer abbott elan/janssen synarc genentech merck
Post on 19-Dec-2015
223 views
TRANSCRIPT
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