Frontiers in Neuroimaging (Mar 2024)

Evaluation of partial volume correction and analysis of longitudinal [18F]GTP1 tau PET imaging in Alzheimer's disease using linear mixed-effects models

  • Sandra M. Sanabria Bohórquez,
  • Suzanne Baker,
  • Suzanne Baker,
  • Paul T. Manser,
  • Matteo Tonietto,
  • Christopher Galli,
  • Kristin R. Wildsmith,
  • Yixuan Zou,
  • Geoffrey A. Kerchner,
  • Robby Weimer,
  • Edmond Teng

DOI
https://doi.org/10.3389/fnimg.2024.1355402
Journal volume & issue
Vol. 3

Abstract

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PurposeWe evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [18F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM).MethodsWe applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden–level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates.ResultsThe VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability.ConclusionThe results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [18F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test–retest variability.Clinical trial registrationNCT02640092 and NCT03289143.

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