Longitudinal mouse-PET imaging: a reliable method for estimating binding parameters without a reference region or blood sampling

Catriona Wimberley,Matteo Tonietto,Irène Buvat,Fawzi Boumezbeur,Viviane Bouilleret,Charles Truillet,Sylvie Chalon,Marie-Anne Peyronneau,Zuhal Gulhan,Raphael Boisgard,Duc Loc Nguyen

doi:10.1007/s00259-020-04755-5

Abstract

Longitudinal mouse PET imaging is becoming increasingly popular due to the large number of transgenic and disease models available but faces challenges. These challenges are related to the small size of the mouse brain and the limited spatial resolution of microPET scanners, along with the small blood volume making arterial blood sampling challenging and impossible for longitudinal studies. The ability to extract an input function directly from the image would be useful for quantification in longitudinal small animal studies where there is no true reference region available such as TSPO imaging.MethodsUsing dynamic, whole-body 18F-DPA-714 PET scans (60 min) in a mouse model of hippocampal sclerosis, we applied a factor analysis (FA) approach to extract an image-derived input function (IDIF). This mouse-specific IDIF was then used for 4D-resolution recovery and denoising (4D-RRD) that outputs a dynamic image with better spatial resolution and noise properties, and a map of the total volume of distribution (VT) was obtained using a basis function approach in a total of 9 mice with 4 longitudinal PET scans each. We also calculated percent injected dose (%ID) with and without 4D-RRD. The VT and %ID parameters were compared to quantified ex vivo autoradiography using regional correlations of the specific binding from autoradiography against VT and %ID parameters.ResultsThe peaks of the IDIFs were strongly correlated with the injected dose (Pearson R = 0.79). The regional correlations between the %ID estimates and autoradiography were R = 0.53 without 4D-RRD and 0.72 with 4D-RRD over all mice and scans. The regional correlations between the VT estimates and autoradiography were R = 0.66 without 4D-RRD and 0.79 with application of 4D-RRD over all mice and scans.ConclusionWe present a FA approach for IDIF extraction which is robust, reproducible and can be used in quantification methods for resolution recovery, denoising and parameter estimation. We demonstrated that the proposed quantification method yields parameter estimates closer to ex vivo measurements than semi-quantitative methods such as %ID and is immune to tracer binding in tissue unlike reference tissue methods. This approach allows for accurate quantification in longitudinal PET studies in mice while avoiding repeated blood sampling.

Highlights

Dedicated PET machines enable mouse imaging with the large number of transgenic mice and disease models available [1]
We propose a generic method for quantification of translocator protein (TSPO) PET scans in the mouse by taking the focus away from finding an appropriate reference or pseudo-reference region and using a data-driven approach instead, to extract a blood input function from the whole-body image of the mouse
Regional group averages for the PET measures of %ID or volume of distribution (VT) were correlated against the measured activity from the autoradiography slices for all animals at the different time points for 7 regions of interest (left and right cortex, hippocampus, thalamus and Figure 1 (2) shows the four different factors identified in the mouse PET image of the tracer studies

Summary

Introduction

Dedicated PET machines enable mouse imaging with the large number of transgenic mice and disease models available [1]. In longitudinal PET studies, the changes in receptor or protein expression can be small, which means that sophisticated quantification and physiological parameter estimation methods would be needed to identify such small variations. There is the possibility to use a reference region for compartmental modelling to estimate binding parameters. This is not the case for targets where there is no brain region without the target present, such as the translocator protein (TSPO). Due to the low-level basal expression of TSPO in healthy brain tissue, and because the pattern of over-expression is unknown in some disease states, using a reference region is suboptimal

Results

Discussion

Conclusion