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

NeuroImage (Aug 2021)

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.

Journal volume & issue: Vol. 237
p. 118194

Abstract

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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.

Published in NeuroImage

ISSN: 1053-8119 (Print); 1095-9572 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
Website: https://www.journals.elsevier.com/neuroimage

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