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

Applicable MR Measurements

• Structural MRI (link=cell loss to atrophy)• MR Spectroscopy • Functional MRI • Proton Diffusion• Perfusion• Relaxometry• Magnetization Transfer• Amyloid Plaque Imaging

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

Neurology 1998;51:993-999

Objectives

• 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

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 yrsStudies

Characterization Of Subjects

Annual Percent Volume Change

Controls (n=24) Cases (n-24) P-value* Mean SD Mean SD

Hippocampal -1.61.4 -4.01.9 <0.001Temporal Horn 6.27.69 14.28.5 0.002

*Rank sum test of difference between cases and controls

Conclusion

• 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

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

Methods

• 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

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)

Descriptive Information

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)

Conclusion

• 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

Rates of Atrophy by Technique and by Clinical Group

Objective

• 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

• Hippocampus• Entorhinal Cortex (ERC)• Whole Brain • Ventricle

Whole Brain Ventricle GROUP Ann% ch GMM GMM HF ERC

Normal Stable Mean -0.4-0.4 1.81.8 -1.5 -2.7 -1.5 -2.7

Normal Converter Mean -0.7-0.7 3.33.3 -3.1 -5.3 -3.1 -5.3

MCI Stable Mean -0.4-0.4 2.82.8 -1.8 -4.8 -1.8 -4.8

MCI Converter Mean -0.9-0.9 4.04.0 -4.0 -6.8 -4.0 -6.8

AD Slow Progressor Mean -1.3-1.3 4.24.2 -3.5 -7.2 -3.5 -7.2

AD Fast Progressor Mean -1.6-1.6 6.66.6 -5.2 -10.2 -5.2 -10.2SDSD 0.8 2.3 3.0 4.7

(Mean1-Mean2) Whole Brain Ventricle (SD1*SD1)+(SD2*SD2) GMM GMM HF ERC

Normal Stable vs. 0.37 0.92 0.88 0.83Normal Converter

MCI Stable vs 0.87 0.56 1.00 0.38MCI Converter

AD Slow Progressor vs 0.25 0.72 0.42 0.41AD Fast Progressor

Normal Stable vs 1.32 1.95 1.22 1.52AD Fast Progressor

Conclusions

• 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

• MilamileneMilamilene• ObjectiveObjective: 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

Methods

• 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

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

Change from Baseline in Behavioral/Cognitive and MRI Variables

Power Calculations

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

• ADAS-Cog 320• MMSE 241• hippocampal volume 21• temporal horn volume 54

Conclusions

• 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

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

Acknowledgments

• R01 AG11378• R01 AG19142• AG16574 ADRC• AG06786 ADPR

Mayo ADRC and ADPR

Ronald C. Petersen, M.D., Ph.D. Dorla BurtonRuth H. Cha, M.S. Dianne FitchPeter C. O’Brien, Ph.D. Nancy HaukomSteven D. Edland, Ph.D. Kris JohnsonRobert Ivnik Ph.D. Martha MandarinoGlenn E. Smith, Ph.D. Joan McCormickBradly F. Boeve, M.D. Sheryl NessEric G. Tangalos, M.D. Kathy Wytaske David Knopman MD

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 XuMira SenkacovaKelly StewartMarina Davtian