Accounting for white matter uptake improves between tracer agreement in amyloid PET

Abstract

INTRODUCTION : Amyloid positron emission tomography (PET) allows in vivo measurement of amyloid plaque deposition; however, different tracers lead to different results. We test the hypothesis that the variability in amyloid measurements is related to white matter retention, and accounting for this variability can improve agreements. METHODS : Data from the Centiloid project was downloaded and processed for four F18 tracer-to-Pittsburgh Compound B (PiB) pairs to obtain mean cortical standardized uptake value ratio (MCSUVR). Three approaches were examined to account for white matter contribution to the MCSUVR. Pearson's correlation was used to assess the between tracer agreements. Steiger's test was used to determine the significance of improvement. RESULTS : Accounting for white matter signal improves the agreement. The regional spread function partial volume correction (RSF PVC) method was most consistent in achieving statistically significant improvements (p < 0.05) for all four tracer pairs. DISCUSSION : Between-tracer agreement of amyloid measure can be improved by accounting for white matter signal. Further investigation is ongoing for additional improvement. HIGHLIGHTS • Analyzing head-to-head data for all four common F18-labeled tracers against Pittsburgh Compound B (PiB). • Evaluating three different techniques to correct for white matter signal. • Steiger's test to determine the significance of improvements. • White matter uptake contributes to the between-tracer measurement difference.

Description

Keywords

Amyloid, Harmonization, Positron emission tomography (PET), Regional spread function partial volume correction (RSF PVC), Pittsburgh Compound B (PiB)

Sustainable Development Goals

SDG-03: Good health and well-being

Citation

Chen, Y., Protas, H., Luo, J. et al. 2025, 'Accounting for white matter uptake improves between tracer agreement in amyloid PET', Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, vol. 17, no. 3, art. e70165, doi : 10.1002/dad2.70165.