Likelihood estimation of drug occupancy for brain PET studies

NeuroImage
Martin SchainR Todd Ogden

Abstract

Neuroimaging with PET is unique in its capability to measure in vivo the occupancy of a drug. The occupancy is typically obtained by conducting PET measurements before and after administration of the drug. For radioligands for which no reference region exists, however, the only established procedure to estimate the occupancy from these data is via linear regression analysis, forming the basis for the so-called Lassen plot. There are several reasons why simple linear regression analysis is not ideal for analyzing these data, including regression attenuation and correlated errors. Here, we propose the use of Likelihood Estimation of Occupancy (LEO) in such a situation. Similar to the Lassen plot, LEO uses the total distribution volume estimates at baseline and at block condition as input, but estimates the non-displaceable distribution volume (VND) and fractional occupancy (Δ) via direct maximum likelihood estimation (MLE). This study outlines the rationale for using MLE to estimate Δ and VND from PET data, and evaluates its performance in relation to the Lassen Plot via two separate simulation experiments. Finally, LEO and Lassen plot are applied to a PET dataset acquired with [11C]WAY-100635. LEO can exploit the covariance stru...Continue Reading

Citations

Jun 6, 2019·Annual Review of Biomedical Engineering·Jacob M Hooker, Richard E Carson
Mar 12, 2021·European Journal of Nuclear Medicine and Molecular Imaging·Catriona WimberleyPaolo Zanotti-Fregonara

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