Published in

SAGE Publications, Journal of Cerebral Blood Flow and Metabolism, 6(41), p. 1379-1389, 2020

DOI: 10.1177/0271678x20950486

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A local-neighborhood Lassen plot filter for creating occupancy and non-displaceable binding images

Journal article published in 2020 by Bart de Laat ORCID, Evan D. Morris
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

For radioligands without a reference region, the Lassen plot can be used to estimate receptor occupancy by an exogenous drug ([Formula: see text]). However, the Lassen plot is not well-suited for spatial variation in [Formula: see text]. To overcome this limitation, we introduce a Lassen plot filter, i.e. a Lassen plot applied to local neighborhoods in PET images. Image data were simulated with regional variation in [Formula: see text], [Formula: see text], both, or neither and analyzed using the change in binding potential ([Formula: see text]), the conventional Lassen plot, and the Lassen plot filter at the region of interest (ROI) and voxel level. All methods were also applied to a human [11C]flumazenil occupancy study using PF-06372865. This combination of a non-selective radioligand and selective drug should lead to varying [Formula: see text]provided the distribution of subtypes varies spatially. In contrast with [Formula: see text] and the conventional Lassen plot, ROI-level and voxel-level Lassen plot filter estimates remained unbiased in the presence of regional variation in [Formula: see text] or [Formula: see text]. In the [11C]flumazenil data-set, [Formula: see text] was shown to vary regionally in accordance with the distribution of binding sites for [11C]flumazenil and PF-06372865. We demonstrate that a local-neighborhood Lassen plot filter provides robust and unbiased estimates of [Formula: see text] and [Formula: see text] without the need for any user intervention.