ASL-incorporated Pharmacokinetic Modelling of PET Data With Reduced Acquisition Time: Application to Amyloid Imaging

Abstract

Pharmacokinetic analysis of Positron Emission Tomography (PET) data typically requires at least one hour of image acquisition, which poses a great disadvantage in clinical practice. In this work, we propose a novel approach for pharmacokinetic modelling with significantly reduced PET acquisition time, by incorporating the blood flow information from simultaneously acquired arterial spin labelling (ASL) magnetic resonance imaging (MRI). A relationship is established between blood flow, measured by ASL, and the transfer rate constant from plasma to tissue of the PET tracer, leading to modified PET kinetic models with ASL-derived flow information. Evaluation on clinical amyloid imaging data from an Alzheimer's disease (AD) study shows that the proposed approach with the simplified reference tissue model can achieve amyloid burden estimation from 30 min [ 18 F]florbetapir PET data and 5 min simultaneous ASL MR data, which is comparable with the estimation from 60 min PET data (mean error=−0.03). Conversely, standardised uptake value ratio (SUVR), the alternative measure from the data showed a positive bias in areas of higher amyloid burden (mean error=0.07). Abstract. Pharmacokinetic analysis of Positron Emission Tomography (PET) data typically requires at least one hour of image acquisition, which poses a great disadvantage in clinical practice. In this work, we propose a novel approach for pharmacokinetic modelling with significantly reduced PET acquisition time, by incorporating the blood flow information from simultaneously acquired arterial spin labelling (ASL) magnetic resonance imaging (MRI). A relationship is established between blood flow, measured by ASL, and the transfer rate constant from plasma to tissue of the PET tracer, leading to modified PET kinetic models with ASL-derived flow information. Evaluation on clinical amyloid imaging data from an Alzheimer's disease study shows that the proposed approach with the simplified reference tissue model can achieve amyloid burden estimation from 30-min [18 F]florbetapir PET data and 5-min simultaneous ASL MR data, which is comparable with the estimation from 60-min PET data (mean error= −0.03). Conversely, standardised uptake value ratio (SUVR), the alternative measure from the data showed a positive bias in areas of higher amyloid burden (mean error= 0.07).

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

“…In this paper we present a novel methodology to synthesise PET tracer delivery, R 1 , maps from a database of ASL-CBF and T1 images to significantly improve the quantification of PET data using a clinically feasible acquisition time. The results were compared to a technique proposed in [2], where R 1 values were derived directly from the ASL data by linear regression of a population of subjects with ASL-CBF and R 1 maps. For regional analysis, the proposed synthesised R 1 estimation performed significantly better than the ASL regression method, and the performance in the estimation of BP N D following PK modelling on 30:60 minutes of PET data was also significantly better.…”

“…When the PET acquisition time is reduced to t ∈ [t s , t e ], C R (t) for t ∈ [0, t s ] must be estimated. This is performed as in [2], where a set of subjects with C R (t) for t ∈ [0, t e ] are used to generate a mean population C R (t), which is then scaled to the available C R (t) t ∈ [t s , t e ] to estimate a subject specific…”

“…The methodology was evaluated in 32 subjects participating in a study of ageing/preclinical AD where the tracer target was amyloid-β, as quantified by the binding potential (BP N D ). Our approach gives a significantly improved estimation of R 1 on both regional and voxel-wise scales compared to [2]. This translates into significantly lower errors in BP N D estimates, such that amyloid burden can be accurately quantified using a single 30 minute PET/MRI acquisition.…”

“…A framework to perform PK modelling on 30 minutes of PET data by incorporating blood flow information from simultaneously acquired MRI was proposed in [2]. This approach halves the acquisition time by assuming that the relationship between cerebral blood flow (CBF) measured using arterial spin labelling (ASL) MRI and the PET tracer delivery parameter R 1 can be approximated using a global linear regression derived from regional average values.…”

Short Acquisition Time PET/MR Pharmacokinetic Modelling Using CNNs

“…This may take 60 mins or more which is not clinically feasible, due to patient discomfort, scanner availability, and increased motion. A framework which reduces the PET acquisition time by incorporating simultaneously acquired arterial spin labelled (ASL) MRI data into the PK model has been proposed [1]. This involves three steps; conversion of ASL cerebral blood flow (CBF) maps into the relative PET tracer delivery parameter (R 1 ), extrapolation of the PET input function (C R ) to account for the missing time-points, and PK model fitting to the measured PET data using fixed R 1 and extrapolated C R .…”