Short Acquisition Time PET Quantification Using MRI-Based Pharmacokinetic Parameter Synthesis

Abstract

Positron Emission Tomography (PET) with pharmacokinetic (PK) modelling is a quantitative molecular imaging technique, however the long data acquisition time is prohibitive in clinical practice. An approach has been proposed to incorporate blood flow information from Arterial Spin Labelling (ASL) Magnetic Resonance Imaging (MRI) into PET PK modelling to reduce the acquisition time. This requires the conversion of cerebral blood flow (CBF) maps, measured by ASL, into the relative tracer delivery parameter (R1) used in the PET PK model. This was performed regionally using linear regression between population R1 and ASL values. In this paper we propose a novel technique to synthesise R1 maps from ASL data using a database with both R1 and CBF maps. The local similarity between the candidate ASL image and those in the database is used to weight the propagation of R1 values to obtain the optimal patient specific R1 map. Structural MRI data is also included to provide information within common regions of artefact in ASL data. This methodology is compared to the linear regression technique using leave one out analysis on 32 subjects. The proposed method significantly improves regional R1 estimation (p < 0.001), reducing the error in the pharmacokinetic modelling. Furthermore, it allows this technique to be extended to a voxel level, increasing the clinical utility of the images.

Short Acquisition Time PET/MR Pharmacokinetic Modelling Using CNNs

“…Fixed R 1 methods. Two methods are used to derive R 1 from ASL-CBF: the linear regression (LR) method [1], and the image fusion (IF) method [7]. Both methods require a database of subjects with 60 mins of PET data and ASL.…”

“…For all three methods the estimation of BP N D was carried out as previously described [1,7]. Briefly, the reference region, C R is extrapolated to t = 0, at tracer injection, by scaling the mean population C R to the measured data using a linear least squares fit, then the derived R 1 value and the extrapolated C R are used in (1) to estimate k 2 and BP N D from the measured PET data.…”