Low activity [¹¹C]raclopride kinetic modeling in the mouse brain using the spatiotemporal kernel method

Abstract

Depending on the molar activity of the tracer, the maximal allowable injected activity in mouse brain PET studies can be extremely low in order to avoid receptor saturation. Therefore, a high level of noise can be present in the image. We investigate several dynamic PET reconstruction methods in reduced counts, or equivalently in reduced injected activity, data exemplified in [11C]raclopride BP ND and R 1 quantification using the simplified reference tissue model (SRTM). We compared independent frame reconstruction (IFR), post-reconstruction HYPR denoising (IFR + HYPR), direct reconstruction using the SRTM model (DIR-SRTM), and the spatial (KERS) and spatiotemporal kernel reconstruction (KERST). Additionally, HYPR denoising of the frames used as features for the calculation of the spatial kernel matrix, was investigated (KERS-HYPR and KERST-HYPR). In vivo data of 11 mice, was used to generate list-mode data for five reduced count levels corresponding to reductions by a factor 4, 8, 12, 16 and 32 (equivalently 2.07, 1.04, 0.691, 0.518, and 0.260 MBq). Correlation of regional BP ND and R 1 values (reduced versus full counts reconstructions) was high (r > 0.94) for all methods, with KERS-HYPR and KERST-HYPR reaching the highest correlation (r > 0.96). Among methods with regularization, DIR-SRTM showed the largest variability in BP ND (Bland–Altman SD from 3.0% to 12%), while IFR showed it for R 1 (5.1%–14.6%). KERST and KERST-HYPR were the only methods with Bland–Altman bias and SD below 5% for noise level up to a reduction factor of 16. At the voxel level, BP ND and R 1 correlation was gradually decreased with increasing noise, with the largest correlation (BP ND r > 0.88, R 1 r > 0.62) for KERS-HYPR and KERST-HYPR. The spatial and the spatiotemporal kernel methods performed similarly, while using only temporal regularization with direct reconstruction showed more variability. Although R1 values present noise, using the spatiotemporal kernel reconstruction, accurate estimates of binding potential could be obtained with mouse injected activities as low as 0.26–0.518 MBq. This is desirable in order to maintain the tracer kinetics principle in mouse studies.

Spatiotemporal Kernel Reconstruction for Linear Parametric Neurotransmitter PET Kinetic Modeling in Motion Correction Brain PET of Awake Rats

“…Due to the relatively large volume of the rat striatum structure (0.043 cm 3 single side), regional analysis performs well using IFR. However, for smaller structures, or for studies with lower activity injection, the spatiotemporal kernel method would show larger differences compared with independent frame reconstruction ( Miranda et al, 2021 ).…”

“…Temporal noise in the IFR voxel-wise TACs is detrimental for the lp-ntPET kinetic modeling since noise can be overfitted and wrongly interpreted as an activation in the TAC. Additional incorporation of HYPR denoising in calculation of the kernel matrix could further improve performance of the Kernel method ( Cheng et al, 2021 ; Miranda et al, 2021 ).…”

“…This method has been applied using the lp-ntPET kinetic model for noise reduction ( Angelis et al, 2019 ). Another reconstruction developed for noise reduction in dynamic PET is the kernel method ( Wang and Qi, 2015 ; Wang, 2019 ; Miranda et al, 2021 ). This method makes use of spatial and temporal correlations in the data to reduce noise in the iterative reconstruction ( Wang and Qi, 2015 ; Novosad and Reader, 2016 ; Wang, 2019 ).…”

Reconstruction of multi-animal PET acquisitions with anisotropically variant PSF

“…This same approach has been more recently implemented in GPU for a preclinical scanner by Miranda et al [30] with good results. Spatially variant PSFs improved spatial resolution and thus quantification in the whole FOV, enabling simultaneous scanning of multiple animals without compromising quantitative accuracy [31].…”