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Structural MRI as a Biomarker of Disease Progression in AD. Department of Diagnostic Radiology and MRI Research Lab. Presented by Clifford Jack, M.D. at the November 18, 2002 Peripheral and Central Nervous System Drugs Advisory Committee Meeting.

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structural mri as a biomarker of disease progression in ad

Structural MRI as a Biomarker of Disease Progression in AD

Department of Diagnostic Radiology

and MRI Research Lab

Presented by Clifford Jack, M.D.

at the November 18, 2002

Peripheral and Central Nervous System Drugs Advisory Committee Meeting

indirect measures of disease can be valid biomarkers of progression
provided a plausible biologic link exists between change in the marker and progression of the disease itself

changes in the marker are empirically proven to track with independent measures of progression

Indirect measures of disease can be valid biomarkers of progression
applicable mr measurements
Structural MRI (link=cell loss to atrophy)

MR Spectroscopy

Functional MRI

Proton Diffusion



Magnetization Transfer

Amyloid Plaque Imaging

Applicable MR Measurements
the rate of medial temporal lobe atrophy in typical aging and alzheimer s disease

The Rate of Medial Temporal Lobe Atrophy in Typical Aging and Alzheimer’s Disease

Neurology 1998;51:993-999

To determine the annualized rates of volume change of the hippocampus and temporal horn in cognitively normal elderly control subjects and individually matched AD patients

To test the hypothesis that these rates were different


Characterization Of Subjects

Controls(n=24) Cases (n=24)

Mean ± SD Mean ± SD

Age 81.04 ± 3.78 yrs 80.42 ± 4.02 yrs

Education 14.75 ± 2.51 yrs 13.21 ± 2.83 yrs

MMSE 28.79 ± 1.28 20.74 ± 4.60

DRS 137.38 ± 4.69 108.48 ± 14.35

Interval Between MRI 1.96 ± 0.75 yrs 1.89 ± 0.68 yrs


annual percent volume change
Controls (n=24) Cases (n-24) P-value*

Mean  SD Mean  SD

Hippocampal -1.61.4 -4.01.9 <0.001

Temporal Horn 6.27.69 14.28.5 0.002

*Rank sum test of difference between cases and controls

Annual Percent Volume Change
Reasonable 1st step: expected differences in rates between AD and controls were observed, but it did not prove that changes in imaging tracked with changes in independent measures of disease progression

Rates were approximately 2.5 times greater in AD than in individually age and gender matched control

rates of hippocampal atrophy in normal aging mild cognitive impairment and alzheimer s disease

Rates of Hippocampal Atrophy in Normal Aging, Mild Cognitive Impairment, and Alzheimer's Disease

Neurology, 2000;55:484-489

objective transition analysis
To test the hypothesis that change on imaging (rates of hippocampal atrophy) match clinical change

Use clinical transition (or lack of) as gold standard independent measures of progression

Objective:Transition Analysis
129 subjects from the ADRC/ADPR who met established criteria for normal controls, mild cognitive impairment (MCI), or probable AD at entry

Controls and MCI patients could either remain cognitively stable or could decline

MRI at initial & FU clinical assessment


Descriptive Information

Age at 1st MMSE Duration between

MRI baseline and followup

MRI in years

Normal-Stable 80.4 ± 6.4 28 ± 1.6 3.0 ± 0.5

(N=48) (62, 97) (23, 30) (2.0, 3.9)

Normal-Decliner 82.3 ± 5.8 28 ± 1.7 3.3 ± 0.4

(N=10) (76, 95) (25, 30) (2.7, 4.0)

MCI-Stable 77.9 ± 8.0 24 ± 1.9 2.9 ± 0.5

(N=25) (60, 92) (23, 30) (2.1, 4.0)

MCI-Decliner 77.3 ± 8.0 24 ± 3.2 2.9 ± 0.6

(N=18) (64, 94) (18, 30) (2.1, 3.9)

AD 73.8 ± 11.3 22 ± 4.3 2.9 ± 0.5

(N=28) (51, 93) (14, 29) (2.1, 3.9)

percent annual change in hippocampal volume by followup clinical group
Normal-Stable (N = 48) -1.7 ± 0.9

Normal-Decliner (N = 10) -2.8 ± 1.7

MCI-Stable (N = 25) -2.5 ± 1.5

MCI-Decliner (N = 18) -3.7 ± 1.5

AD (N = 28) -3.5 ± 1.8


Values in table represent mean ± SD (range)

Rates of hippocampal atrophy match the change in cognitive status (or lack of) over time in elderly persons who lie along the cognitive continuum from normal to MCI to AD

Validation of change in MRI volume as a biomarker of Dz progression

Are some techniques better measures of progression than others at different disease stages?

To compare the annualized rates of atrophy by technique among clinical groups (normal -stable, normal-converter, MCI -stable, MCI-converter, AD-slow progressor, and AD-fast progressor)

structures measured rates of change

Entorhinal Cortex (ERC)

Whole Brain


Structures Measured: Rates of Change

Whole Brain Ventricle


Normal Stable Mean -0.4 1.8 -1.5 -2.7

Normal Converter Mean -0.7 3.3 -3.1 -5.3

MCI Stable Mean -0.4 2.8 -1.8 -4.8

MCI Converter Mean -0.9 4.0 -4.0 -6.8

AD Slow Progressor Mean -1.3 4.2 -3.5 -7.2

AD Fast Progressor Mean -1.6 6.6 -5.2 -10.2

SDSD 0.8 2.3 3.0 4.7


(Mean1-Mean2) Whole Brain Ventricle


Normal Stable vs. 0.37 0.92 0.88 0.83 Normal Converter

MCI Stable vs 0.87 0.56 1.00 0.38

MCI Converter

AD Slow Progressor vs 0.25 0.72 0.42 0.41

AD Fast Progressor

Normal Stable vs 1.32 1.95 1.22 1.52

AD Fast Progressor

Structural MRI rates consistently follow expected correlations with clinical status and clinical transition = support for use as biomarker of Dz progression

Appears to be some stage specific Dx sensitivity

multi site studies

Objective: To assess the technical feasibility of using MRI measurements as a surrogate end point for disease progression in a therapeutic trial of Milamilene for AD

Multi-Site Studies
52 week controlled trial of Milameline, a muscarinic receptor agonist, N=450

therapeutic trial itself was not completed

MRI arm of the study was continued

192 subjects from 38 different centers underwent 2 MRI with 1 yr interval

hippocampal and temporal horn volume


Change from Baseline in

Behavioral/Cognitive and MRI Variables

Annual Raw Annual % Percent

Change Change Decliners

(N=192) (N=192)

ADAS-Cog 4.1 16.4 65.1

MMSE -1.9 -8.4 65.1

GDS 0 0.0 38.5

Total Hippocampal mm3 -221 -4.9 99.0

Total Temporal Horn Volume mm3 616 16.1 85.4

power calculations
Per arm for 50% effect size (rate reduction over 1 yr.)

ADAS-Cog 320

MMSE 241

hippocampal volume 21

temporal horn volume 54

Power Calculations
Technical feasibility documented

Decline over time was more consistently seen with imaging measures than behavioral/cognitive measures (p<0.001)

Power calculations: sample sizes imaging<< behavioral/cognitive

structural mri as a biomarker

Structural MRI as a Biomarker

In the absence of a positive therapeutic trial that incorporated imaging, the best available evidence supporting the validity of MRI as a biomarker of progression would be multiple natural history studies that consistently demonstrate concordant MRI and clinical changes

R01 AG11378

R01 AG19142

AG16574 ADRC

AG06786 ADPR

mayo adrc and adpr
Ronald C. Petersen, M.D., Ph.D. Dorla Burton

Ruth H. Cha, M.S. Dianne Fitch

Peter C. O’Brien, Ph.D. Nancy Haukom

Steven D. Edland, Ph.D. Kris Johnson

Robert Ivnik Ph.D. Martha Mandarino

Glenn E. Smith, Ph.D. Joan McCormick

Bradly F. Boeve, M.D. Sheryl Ness

Eric G. Tangalos, M.D. Kathy Wytaske David Knopman MD

Mayo ADRC and ADPR
milamilene parke davis


M. Slomkowski, Pharm.D.

S. Gracon, D.V.M.

T. M. Hoover, Ph.D.

mr lab
Maria Shiung Kejal Kantarci

Jeff Gunter

Yuecheng Xu

Mira Senkacova

Kelly Stewart

Marina Davtian