Validation of a combined image derived input function and venous sampling approach for the quantification of [18F]GE-179 PET binding in the brain
Marian Galovic,
Kjell Erlandsson,
Tim D. Fryer,
Young T. Hong,
Roido Manavaki,
Hasan Sari,
Sarah Chetcuti,
Benjamin A. Thomas,
Martin Fisher,
Selena Sephton,
Roberto Canales,
Joseph J Russell,
Kerstin Sander,
Erik Årstad,
Franklin I. Aigbirhio,
Ashley M. Groves,
John S. Duncan,
Kris Thielemans,
Brian F. Hutton,
Jonathan P. Coles,
Matthias J. Koepp
Affiliations
Marian Galovic
Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Chalfont Centre for Epilepsy, UK
Kjell Erlandsson
Institute of Nuclear Medicine, University College London, London, UK
Tim D. Fryer
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
Young T. Hong
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
Roido Manavaki
Department of Radiology, University of Cambridge, Cambridge, UK
Hasan Sari
Institute of Nuclear Medicine, University College London, London, UK; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
Sarah Chetcuti
Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK
Benjamin A. Thomas
Institute of Nuclear Medicine, University College London, London, UK
Martin Fisher
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
Selena Sephton
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
Roberto Canales
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
Joseph J Russell
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
Kerstin Sander
Centre for Radiopharmaceutical Chemistry, University College London, London, UK
Erik Årstad
Centre for Radiopharmaceutical Chemistry, University College London, London, UK
Franklin I. Aigbirhio
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
Ashley M. Groves
Institute of Nuclear Medicine, University College London, London, UK
John S. Duncan
Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Chalfont Centre for Epilepsy, UK
Kris Thielemans
Institute of Nuclear Medicine, University College London, London, UK
Brian F. Hutton
Institute of Nuclear Medicine, University College London, London, UK
Jonathan P. Coles
Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK
Matthias J. Koepp
Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Chalfont Centre for Epilepsy, UK; Corresponding author at: Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.
Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing [18F]GE-179 brain PET imaging of the NMDA receptor. Arterial and venous PF and PWB ratio estimates determined from 7 patients with traumatic brain injury (TBI) were also compared to assess the potential effect of medication. There was high agreement between areas under the curves of the estimates of PF (r = 0.99, p<0.001), PWB ratio (r = 0.93, p<0.001), and the PIF (r = 0.92, p<0.001) as well as total distribution volume (VT) in 11 regions across the brain (r = 0.95, p<0.001). IDIF+venous VT had a mean bias of −1.7% and a comparable regional coefficient of variation (arterial: 21.3 ± 2.5%, IDIF+venous: 21.5 ± 2.0%). Simplification of the IDIF+venous method to use only one venous sample provided less accurate VT estimates (mean bias 9.9%; r = 0.71, p<0.001). A version of the method that avoids the need for blood sampling by combining the IDIF with population-based PF and PWB ratio estimates systematically underestimated VT (mean bias −20.9%), and produced VT estimates with a poor correlation to those obtained using arterial data (r = 0.45, p<0.001). Arterial and venous blood data from 7 TBI patients showed high correlations for PF (r = 0.92, p = 0.003) and PWB ratio (r = 0.93, p = 0.003). In conclusion, the IDIF+venous method with five venous samples provides a viable alternative to arterial sampling for quantification of [18F]GE-179 VT.
