TY - GEN
T1 - Modeling venous plasma samples in [18F] FDG PET studies
T2 - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
AU - Volpi, Tommaso
AU - Lee, John J.
AU - Silvestri, Erica
AU - Durbin, Tony
AU - Corbetta, Maurizio
AU - Goyal, Manu S.
AU - Vlassenko, Andrei G.
AU - Bertoldo, Alessandra
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The gold-standard approach to quantifying dynamic PET images relies on using invasive measures of the arterial plasma tracer concentration. An attractive alternative is to employ an image-derived input function (IDIF), corrected for spillover effects and rescaled with venous plasma samples. However, venous samples are not always available for every participant. In this work, we used the nonlinear mixed-effects modeling approach to develop a model which infers venous tracer kinetics by using venous samples obtained from a population of healthy individuals and integrating subject-specific covariates. Population parameters (fixed effects), their between-subject variability (random effects), and the effects of covariates were estimated. The selected model will allow to reliably infer venous tracer kinetics in subjects with missing measurements. Clinical relevance - The derived model will be relevant for fully noninvasive dynamic FDG PET quantification using image-derived input functions in both healthy and patient populations when hemodynamics is not impaired.
AB - The gold-standard approach to quantifying dynamic PET images relies on using invasive measures of the arterial plasma tracer concentration. An attractive alternative is to employ an image-derived input function (IDIF), corrected for spillover effects and rescaled with venous plasma samples. However, venous samples are not always available for every participant. In this work, we used the nonlinear mixed-effects modeling approach to develop a model which infers venous tracer kinetics by using venous samples obtained from a population of healthy individuals and integrating subject-specific covariates. Population parameters (fixed effects), their between-subject variability (random effects), and the effects of covariates were estimated. The selected model will allow to reliably infer venous tracer kinetics in subjects with missing measurements. Clinical relevance - The derived model will be relevant for fully noninvasive dynamic FDG PET quantification using image-derived input functions in both healthy and patient populations when hemodynamics is not impaired.
UR - http://www.scopus.com/inward/record.url?scp=85138128486&partnerID=8YFLogxK
U2 - 10.1109/EMBC48229.2022.9871429
DO - 10.1109/EMBC48229.2022.9871429
M3 - Conference contribution
C2 - 36086500
AN - SCOPUS:85138128486
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 4704
EP - 4707
BT - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 July 2022 through 15 July 2022
ER -