A Comparison of Partial Volume Correction Techniques for Measuring Change in Serial Amyloid PET SUVR

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Longitudinal PET studies in aging and Alzheimer's disease populations rely on accurate and precise measurements of change over time from serial PET scans. Various methods for partial volume correction (PVC) are commonly applied to such studies, but existing comparisons and validations of these PVC methods have focused on cross-sectional measurements. Rate of change measurements inherently have smaller magnitudes than cross-sectional measurements, so levels of noise amplification due to PVC must be smaller, and it is necessary to re-evaluate methods in this context. Here we compare the relative precision in longitudinal measurements from serial amyloid PET scans when using geometric transfer matrix (GTM) PVC versus the traditional two-compartment (Meltzer-style), three-compartment (Müller-Gärtner-style), and no-PVC approaches. We used two independent implementations of standardized uptake value ratio (SUVR) measurement and PVC (one in-house pipeline based on SPM12 and ANTs, and one using FreeSurfer 6.0). For each approach, we also tested longitudinal-specific variants. Overall, we found that measurements using GTM PVC had significantly worse relative precision (unexplained within-subject variability ≈4-8) than those using two-compartment, three-compartment, or no PVC (≈2-4). Longitudinally-stabilized approaches did not improve these properties. This data suggests that GTM PVC methods may be less suitable than traditional approaches when measuring within-person change over time in longitudinal amyloid PET.

Original languageEnglish (US)
Pages (from-to)181-195
Number of pages15
JournalJournal of Alzheimer's Disease
Volume67
Issue number1
DOIs
StatePublished - 2019

Keywords

  • Amyloid PET
  • Pittsburgh Compound B
  • SUVR
  • change over time
  • geometric transfer matrix
  • partial volume correction
  • precision

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health

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