Variability of PET-PIB retention measurements due to different

scanner performance in multi-site trials

Jean-Claude Rwigema

Chet Mathis

Charles Laymon

Jonathan P.J. Carney

Tae Kim

University of Pittsburgh, Radiology

University of Pittsburgh, Medical School

Faculty

PIB (Pittsburgh Compound B)

• Amyloid- (A) plaque deposition is a pathological hallmark of

Alzheimer’s disease (AD)

• Pittsburgh compound-B (PIB) is a radiotracer used in positron

emission tomography (PET) that binds to amyloid plaques and is

a valuable tool in the development and evaluation of anti-

amyloid therapeutics.

Introduction

• Drug development requires large numbers of research subjects with

the concurrent need for large multi-site trials.

• AD longitudinal studies may be of long duration

• Different sites may run different software versions

• Software may be upgraded during a longitudinal study

Attenuation image U Mich ReconstructionU Pitt Reconstruction

Bone-like

Water Air

Emission image

Water with 18F

• Phantom data show that image reconstructions by U of Pitt and by U of Mich have differences. Differences are mainly attributable to differences in scatter correction implementation.

Reconstructions of Phantom Data acquired at the University of Michigan

• We investigate the variability in PET-based

measures of PIB retention due to site-to-site

differences in comparison to the variability

between individual test and retests in the same

scanner.

Aim

• Data was acquired at U Mich

• Each subject was scanned once, and rescanned for comparison

• Data was reconstructed at UPitt and UMich

• Each site operates the same model PET scanner (Siemens

HR+), but different versions of processing software (different

scatter corrections)

• Four subjects were evaluated (one control and three mild

cognitive impairment (MCI) subjects)

Methods

Structural Magnetic resonance (MR) Imaging

-1.5 T GE Signa using SPGR

- Skull-cropped images reoriented along AC-PC line

- Coregister MRI and PET

Positron Emission Tomography (PET) Imaging

- Dynamic [11C]PIB study (15 mCi, 90 min, 34 frames)

- MR-guided region definition (ROI)

- PIB retention was assessed using the PIB distribution volume ratio

(DVR) value determined via the Logan graphical analysis, using

cerebellum data as input

Methods

)(

)(

p

t

CPlasmainTracerofionConcentrat

CTissueinTracerofionConcentratDV

refDV

DVDVR

(DV in a receptor region)

(DV in a non-receptor containing region)

ROIs from MR Image

FRC (Frontal Cortex)

ACG (Anterior Cingulate)

CER (Cerebellum)

FRC (Frontal Cortex)

ACG (Anterior Cingulate)

CER (Cerebellum)

FRC

-0.2

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40 50 60 70 80 90

min

uCi/m

l

Control

MCI (AD)

MCI (Control)

ACG

-0.2

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40 50 60 70 80 90

min

uCi/m

l control

MCI (AD)

MCI (control)

Time Activity Curve from PETCER

-0.2

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40 50 60 70 80 90

min

uCi/m

l Control

MCI (AD)

MCI (Control)

DVR value obtained by Logan analysis

In steady-state, with graphical analysis

Where C(t) is the radioactivity measured by PET at time t in a specified ROI,CB is radiotracer concentration in the non-receptor region

int')()(

)(00

TC

CBdtDVR

TC

dttCTT

y = 2.6887x - 31.091

R2 = 0.9998

20

40

60

80

100

120

20 30 40 50 60

)(

)(0

TC

dttCT

)(/0

TCCBdtT

One example from mci004 ACG ROI

Outcome Measure (DVR)

P-value: MCI001 MCI002 MCI004

5.18E-15 0.511 4.23E-17

0.0

0.5

1.0

1.5

2.0

2.5

3.0

FRC ACG PRC PAR LTC OCC SMC MTC SWM PON

Control

MCI_002

MCI_001

MCI_004

ROI

DVR

Control

MCI (PIB+)

Parametric images of Logan DVR

Logan DVR

0.5

2.5

0.5

1

1.5

2

2.5

3

0.5 1 1.5 2 2.5 3

test

rete

st

con001

mci001

mci002

mci004

Comparison of DVR values for test vs. retest

The variability of test-rest (= test – retest / test) was 5.4 ± 2.7 % (Pitt) 5.4 ± 2.2 % (Mich)

R value

0.960.980.930.96

0.5

1

1.5

2

2.5

3

0.5 1 1.5 2 2.5 3

test

rete

st

con001

mci001

mci002

mci004

Pitt Mich

R value

0.960.980.970.96

0

0.5

1

1.5

2

2.5

3

0 0.5 1 1.5 2 2.5 3

Mich

Pit

t con1 (test)

con1 (retest)

mci1 (test)

mci1 (retest)

mci2 (test)

mci2 (retest)

mci4 (test)

mci4 (retest)

Reconstruction in

U of Pitt

Parametric images of Logan DVR

Reconstruction in

U of Mich

Logan DVR

0.5

2.5

R2 = 0.1579

R2 = 0.2598

R2 = 0.662

R2 = 0.6686

-4

-3

-2

-1

0

1

2

3

4

0.5 1 1.5 2 2.5 3

DVR

mci001 (test)

mci001 (retest)

mci004 (test)

mci004 (retest)

lnR

econ

. | U

Pit

t – U

Mic

h |

| tes

t – r

etes

t |

R2 = 3E-05 R2 = 0.0013

R2 = 0.007

R2 = 0.0233

-5

-4

-3

-2

-1

0

1

2

3

0.5 1 1.5 2 2.5 3

DVR

con001 (test)

con001 (retest)

mci002 (test)

mci002 (retest)

MCI (PIB+) Control and MCI (PIB-)

Recon/recon DVR variance was significantly higher than test/retest variance

in high PIB uptake areas (high DVR)

Variability vs. DVR

Summary

• PIB retention from two of MCI subjects showed PIB+ results, with

significant uptake distributed similarly to that found in subjects with

AD.

• One MCI subject showed PIB- behavior with relatively little PIB

uptake.

• The variability of test-retest was small.

• Recon/Recon DVR variance was significantly higher than test/retest

variance in high PIB uptake areas (high DVR) in PIB+ MCI, while

such variances were comparable in lower uptake areas in control

and PIB- MCI where PIB uptake was uniformly low.

Conclusion

Recon/recon variability depends on the degree of regional PIB retention with high levels of uptake showing greater recon/recon variability.

Acknowledgments

PET center

Chet Mathis, Ph.D.

Jonathan P.J. Carney, Ph.D.

Charles Laymon, Ph.D

Michele Bechtold

MNTP program

Seong-Gi Kim, Ph.D.

William Eddy, Ph.D.

Tomika Cohen

Rebecca Clark

Scatter Correction

• Simulation-based scatter correction:

- Analytical simulation: single-scatter

simulation: use transmission/emission for

calculating single coincidence rate

- Monte Carlo simulation: compute scatter

estimation from the fundamental physics of the

Compton scattering process

• Energy window approach: photons at energy

below sudden threshold must be scattered photons

• Energy window approach: photons at energy

below 511 keV must be scattered photons

• Convolution and deconvolution approach: the use of a scattering

“kernel” function to correct the sinogram via convolution-subtraction

or deconvolution

• Simulation-based scatter correction:

- Analytical simulation: single-scatter simulation

- Monte Carlo simulation: compute scatter estimation from the

fundamental physics of the Compton scattering process

Scatter Correction