QIBA PET Amyloid BC March 11, Agenda

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QIBA PET Amyloid BC March 11, 2016 - Agenda 1. QIBA Round 6 Funding a. Deadlines b. What projects can be funded, what cannot c. Discussion of projects Mechanical phantom and DRO Paul & John? Any Profile gaps left to fill with a project? 2. QIBA Round 5 Project awarded to Dawn: subject motion 3. Status of Profile feedback a. Next steps

Round 6 Funding Details Project proposal due April 15 th Send to RSNA Staff: qiba@rsna.org Funding cannot support human studies Note new focus - for all Round-6 projects: All projects must support the NIBIB contract objectives Support the completion/advancement of a Profile and/or conformance procedures/checklists. BC leadership are charged with approving preliminary projects. Final selection in July

Project Ideas Continue work on DRO and Phantom (Paul and John) Current knowledge gaps in Profile Tracer uptake time differential between measurement time points Acceptable level of difference Ronald Boellaard will develop a draft project Dr. Vanderhayden will support, perhaps radiopharm vendors? Conformance testing project Sites, scanner vendors, analysis vendors Reader variability project Scanner/reconstruction harmonization project Ex: PET/CT scanner model is changed, is there a way to harmonize the SUVR values between the old and new scanners?

PET Amyloid BC QIBA Round 5 Funding Analyses to Support Amyloid Imaging Profile Development: Quantify the Effect of Misalignment and Subject Motion

Anne M. Smith, PhD Technical Support Siemens Molecular Imaging Dawn Matthews Principal Investigator ADMdx Quantitative Imaging Biomarker Alliance - QIBA

Profile Gaps We Want to Fill With This Work Characterize the effect of patient motion on SUVRs How significant is movement between CT and PET acquisitions How significant is movement during PET acquisitions Make recommendations for how much is too much motion Does the distribution of an 18-F amyloid tracer matter (If time) Effect of PET image reconstruction algorithm on SUVRs Determine if significant differences for these algorithms Reconstructed voxel size 1 mm x 1 mm x 2 mm (zoom=2) Project Workhorse OSEM3D (2i24s, 5 mm Gaussian) OSEM3D + TOF (2i21s, 5 mm Gaussian) OSEM3D + PSF (3i24s, 5 mm Gaussian) OSEM3D + TOF +PSF (2i21s, 5 mm Gaussian)

PET/CT Scanner Siemens mct 4 Ring Scanner 22.1 cm axial FOV 70 cm transaxial FOV 4.1 nsec coincidence window 12% FWHM Energy Resolution 540 psec TOF 33% scatter fraction @ low act 10.2 cps/kbq Sensitivity NEMA Pt Source FWHM Resolution 400x400 (2mmx2mmx2mm) @1 cm @10 cm Transaxial 4.5 mm 5.2 mm Axial 4.7 mm 6.1 mm

PET/CT Amyloid Data Avid Florbetapir Clinical Trial at University of Tennessee Medical Center Selected three datasets with minimal motion/misalignment Healthy Control, amnestic MCI, early AD 10 mci of Florbetapir injected with 50 min uptake time 120 kvp 50 mas non-diagnostic quality CT acquired, with Care Dose Used for PET attenuation and scatter corrections 30 cm transaxial FOV Subject s head secured with a bean bag Vac bag PET data Single bed position 10 minute listmode acquisition Reconstruction 400x400 matrix Matched axial slices of CT volume Reconstructed voxel size 1 mm x 1 mm x 2 mm (zoom=2) Multiple recon algorithms/parameters used (previous slide)

Topogram Patient Prep & Scan Planning Healthy Control (HC) Female 75 years old 73 kg 55 min uptake Amnestic MCI (amci) Male 78 years old 80 kg 52 min uptake Early Alzheimer s (ead) Male 71 years old 84 kg 54 min uptake

Assess for Subject Motion and CT-PET Misalignment HC

Assess for Subject Motion and CT-PET Misalignment amci

Assess for Subject Motion and CT-PET Misalignment ead

Static PET/CT Images HC amci ead

Test scans - ADMdx HC amci ead

Dynamic PET Images 1 minute frames 0-5 min HC 5-10 min 0-5 min amci 5-10 min 0-5 min ead 5-10 min

Effect of Reconstruction Algorithm OSEM3D +TOF +PSF +TOF+PSF +AllPass HC ead

Remove Head Holder From mu-map HC amci ead

Simulate Patient Motion and CT-PET Misalignment Misalign mu-map Recon static PET Simulates movement between CT and PET Misalign mu-maps Recon dyn PETs Simulates movement during PET and between CT and PET

Subject motion example from late MCI to mild AD scans SPM corrections needed to re-align images, using a neurological or right-handed coordinate system Average across all frames, referenced to frame 1 of each scan However, depending upon the site and disease severity, subject motion can be as great as 1 to 2 cm and/or many degrees. Study motion typically spans a greater range with greater disease severity (e.g. moderate AD, FTD).

Subject motion example from 140 late MCI to mild AD scans SPM corrections needed to re-align images, using a neurological or right-handed coordinate system Maximum absolute translation or rotation per scan -3.47 to 6.31-6.71 to 5.81-3.61 to 2.50-2.06 to 4.52-3.27 to 6.81-3.10 to 5.17 Depending upon the site and disease severity, subject motion can be as great as 1 to 2 cm and/or many degrees. Study motion typically spans a greater range with greater disease severity (e.g. moderate AD, FTD).

Frame of Reference and Technical Details for Project z y x +z +y +x y +z rot +x rot y z +y rot Radiological or Left- Handed Coordinate System (0,0,0) is the Image Center x z Transverse Sagittal Coronal Technical Details of transformations and reconstructions x Reverse PET Recon Order of Forward Transformations 1. translations 2. z-axis rotation 3. y-axis rotation 4. x-axis rotation Final PET image Forward

Severe subject motion example (ADNI 1) 50-55 min. 55-60 min. Overlaid Motion during scan causes artifact due to: Sampling of blended/ incorrect tissue regions Attenuation over- or undercorrection due to misalignment with Tx scan Motion correction does not remove the embedded artifact, especially with severe movement Difference in position

Subject Motion: Impact on SUVR Scan of subject with minimal movement Target Region Reference region SUVR relatively constant throughout 50-70 minute time window Scan of subject with severe motion Target Region Reference region SUVR at 50-55 minutes = 1.5; SUVR at 60-65 minutes = 1.0, a 50% difference In cases of severe motion, motion correction does not remove embedded artifact

Misalignment Parameters simulate patient movement X trans (mm) Y trans (mm) Z trans (mm) X rot (deg) Y rot (deg) Z rot (deg) Baseline 0 0 0 0 0 0 Set 1 5 0 0 0 0 0 Set 2 0 5 0 0 0 0 Set 3 0 0 5 0 0 0 Set 4 0 0 0 5 0 0 Set 5 0 0 0 0 5 0 Set 6 0 0 0 0 0 5 Set 7 5 5 5 0 0 0 Set 8 0 0 0 5 5 5 Set 9 5 5 5 5 5 5...

Analysis methods (two approaches of several) ADNI (Jagust Lab) PET image motion corrected, frames averaged, intensity normalized, smoothed PET coregistered to MRI Gray matter ROIs defined using Freesurfer Signal intensity measured Cortical average = frontal, AC, PC, lateral temporal, lateral parietal SUVRs calculated o Ref regions: Whole cer, brainstem, subcortical white matter, composite Avid (not on label) PET preprocessed PET spatially warped to PET template Probabilistic template ROIs applied Signal intensity measured SUVRs calculated o Ref regions: Whole cer, pons, subcortical white matter ADNI_UCBERKELEY_AV45_Methods_12.03.15.pdf

Image Analysis For the Baseline and multiple Sets of images SUVRs calculated Will use ADMdx s PET Amyloid Analysis Package SUVR measures will be calculated = x 100%

QIBA Mission QIBA seeks to improve the value and practicality of quantitative imaging biomarkers by reducing variability across devices, patients, and time.