TY - JOUR
T1 - Short acquisition time PET quantification using MRI-based pharmacokinetic parameter synthesis
AU - Scott, Catherine J.
AU - Jiao, Jieqing
AU - Cardoso, M. Jorge
AU - Melbourne, Andrew
AU - De Vita, Enrico
AU - Thomas, David L.
AU - Burgos, Ninon
AU - Markiewicz, Pawel
AU - Schott, Jonathan M.
AU - Hutton, Brian F.
AU - Ourselin, Sébastien
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85029542894&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-66185-8_83
DO - 10.1007/978-3-319-66185-8_83
M3 - Conference paper
AN - SCOPUS:85029542894
SN - 0302-9743
VL - 10434 LNCS
SP - 737
EP - 744
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017
Y2 - 11 September 2017 through 13 September 2017
ER -