Jean-Claude Rwigema

1. Variability of PET-PIB retention measurements due to different scanner performance in multi-site trials Tae Kim Faculty Chet Mathis Charles Laymon Jonathan P.J. Carney University of Pittsburgh, Radiology Jean-Claude Rwigema University of Pittsburgh, Medical School

2. 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.

3. 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

4. Reconstructions of Phantom Data acquired at the University of Michigan • 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. Bone-like Water Air Water with 18F U Pitt Reconstruction U Mich Reconstruction Attenuation image Emission image

5. Aim • 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.

6. Methods • 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)

7. (DV in a receptor region) (DV in a non-receptor containing region) 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

8. ROIs from MR Image FRC (Frontal Cortex) ACG (Anterior Cingulate) CER (Cerebellum)

9. Time Activity Curve from PET FRC (Frontal Cortex) ACG (Anterior Cingulate) CER (Cerebellum)

10. 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 One example from mci004 ACG ROI

11. Outcome Measure (DVR) DVR ROI MCI001 MCI002 MCI004 P-value: 5.18E-15 0.511 4.23E-17

12. Logan DVR 2.5 0.5 Parametric images of Logan DVR Control MCI (PIB+)

13. Comparison of DVR values for test vs. retest Mich Pitt R value R value 0.96 0.98 0.93 0.96 0.96 0.98 0.97 0.96 The variability of test-rest (= test – retest / test) was 5.4 ± 2.7 % (Pitt) 5.4 ± 2.2 % (Mich)

14. Logan DVR 2.5 0.5 Parametric images of Logan DVR Reconstruction in U of Pitt Reconstruction in U of Mich

15. Variability vs. DVR Control and MCI (PIB-) MCI (PIB+) Recon. | UPitt – UMich | | test – retest | ln Recon/recon DVR variance was significantly higher than test/retest variance in high PIB uptake areas (high DVR)

16. 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.

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

18. 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

19. Scatter Correction • Energy window approach: photons at energy below sudden threshold must be scattered photons • 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

20. Scatter Correction • 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 