Abstract:
Population-based input function (PBF) methods provide a less-invasive approach to the quantification of dynamic positron emission tomography (PET) images. PBF methods req...Show MoreMetadata
Abstract:
Population-based input function (PBF) methods provide a less-invasive approach to the quantification of dynamic positron emission tomography (PET) images. PBF methods require the a priori creation of an input function template from a group of subjects who underwent full arterial blood sampling with the same radiotracer. The template is then calibrated using one or two blood samples from the subject under analysis. In this study we propose to generate the PBF template from a group of 8 subjects using a non-linear mixed effect approach and a new input function model. We validated our PBF approach using an independent[18F] FDG dataset of 25 subjects acquired in a different PET center. Results showed a high correlation (> 0.98) and low bias (mean percentage error=1.0 ± 3.1%) between the voxel-wise estimates of [18F] FDG net uptake rate (Ki) obtained with the measured input function and those obtained with the proposed PBF, supporting its use for the quantification of [18F] FDG images acquired in different PET centers.
Date of Conference: 08-11 April 2019
Date Added to IEEE Xplore: 11 July 2019
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ICM, PitiSorbonne Universités, Sorbonne Universités, UPMC Paris 06, Brain and Spine Institute, Inserm U1127, CNRS U7225, Paris, France
Molecular Imaging and Neuropathology Division, New York State Psychiatric Institute, New York, NY, USA
Department of Information Engineering, University of Padova, Padova, Italy
Geriatric Psychiatry Division, New York State Psychiatric Institute, New York, NY, USA
Molecular Imaging and Neuropathology Division, New York State Psychiatric Institute, New York, NY, USA
ICM, PitiSorbonne Universités, Sorbonne Universités, UPMC Paris 06, Brain and Spine Institute, Inserm U1127, CNRS U7225, Paris, France
ICM, PitiSorbonne Universités, Sorbonne Universités, UPMC Paris 06, Brain and Spine Institute, Inserm U1127, CNRS U7225, Paris, France
Contents ICM, PitiSorbonne Universités, Sorbonne Universités, UPMC Paris 06, Brain and Spine Institute, Inserm U1127, CNRS U7225, Paris, France
Molecular Imaging and Neuropathology Division, New York State Psychiatric Institute, New York, NY, USA
Department of Information Engineering, University of Padova, Padova, Italy
Geriatric Psychiatry Division, New York State Psychiatric Institute, New York, NY, USA
Molecular Imaging and Neuropathology Division, New York State Psychiatric Institute, New York, NY, USA
ICM, PitiSorbonne Universités, Sorbonne Universités, UPMC Paris 06, Brain and Spine Institute, Inserm U1127, CNRS U7225, Paris, France
ICM, PitiSorbonne Universités, Sorbonne Universités, UPMC Paris 06, Brain and Spine Institute, Inserm U1127, CNRS U7225, Paris, France
