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Model Corrected Blood Input Function to Compute Cerebral FDG Uptake Rates From Dynamic Total-Body PET Images of Rats in vivo

Recently, we developed a three-compartment dual-output model that incorporates spillover (SP) and partial volume (PV) corrections to simultaneously estimate the kinetic parameters and model-corrected blood input function (MCIF) from dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomograp...

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Autores principales: Massey, James C., Seshadri, Vikram, Paul, Soumen, Mińczuk, Krzysztof, Molinos, Cesar, Li, Jie, Kundu, Bijoy K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058193/
https://www.ncbi.nlm.nih.gov/pubmed/33898476
http://dx.doi.org/10.3389/fmed.2021.618645
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author Massey, James C.
Seshadri, Vikram
Paul, Soumen
Mińczuk, Krzysztof
Molinos, Cesar
Li, Jie
Kundu, Bijoy K.
author_facet Massey, James C.
Seshadri, Vikram
Paul, Soumen
Mińczuk, Krzysztof
Molinos, Cesar
Li, Jie
Kundu, Bijoy K.
author_sort Massey, James C.
collection PubMed
description Recently, we developed a three-compartment dual-output model that incorporates spillover (SP) and partial volume (PV) corrections to simultaneously estimate the kinetic parameters and model-corrected blood input function (MCIF) from dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (FDG PET) images of mouse heart in vivo. In this study, we further optimized this model and utilized the estimated MCIF to compute cerebral FDG uptake rates, K(i), from dynamic total-body FDG PET images of control Wistar–Kyoto (WKY) rats and compared to those derived from arterial blood sampling in vivo. Dynamic FDG PET scans of WKY rats (n = 5), fasted for 6 h, were performed using the Albira Si Trimodal PET/SPECT/CT imager for 60 min. Arterial blood samples were collected for the entire imaging duration and then fitted to a seven-parameter function. The 60-min list mode PET data, corrected for attenuation, scatter, randoms, and decay, were reconstructed into 23 time bins. A 15-parameter dual-output model with SP and PV corrections was optimized with two cost functions to compute MCIF. A four-parameter compartment model was then used to compute cerebral Ki. The computed area under the curve (AUC) and K(i) were compared to that derived from arterial blood samples. Experimental and computed AUCs were 1,893.53 ± 195.39 kBq min/cc and 1,792.65 ± 155.84 kBq min/cc, respectively (p = 0.76). Bland–Altman analysis of experimental vs. computed K(i) for 35 cerebral regions in WKY rats revealed a mean difference of 0.0029 min(−1) (~13.5%). Direct (AUC) and indirect (Ki) comparisons of model computations with arterial blood sampling were performed in WKY rats. AUC and the downstream cerebral FDG uptake rates compared well with that obtained using arterial blood samples. Experimental vs. computed cerebral K(i) for the four super regions including cerebellum, frontal cortex, hippocampus, and striatum indicated no significant differences.
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spelling pubmed-80581932021-04-22 Model Corrected Blood Input Function to Compute Cerebral FDG Uptake Rates From Dynamic Total-Body PET Images of Rats in vivo Massey, James C. Seshadri, Vikram Paul, Soumen Mińczuk, Krzysztof Molinos, Cesar Li, Jie Kundu, Bijoy K. Front Med (Lausanne) Medicine Recently, we developed a three-compartment dual-output model that incorporates spillover (SP) and partial volume (PV) corrections to simultaneously estimate the kinetic parameters and model-corrected blood input function (MCIF) from dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (FDG PET) images of mouse heart in vivo. In this study, we further optimized this model and utilized the estimated MCIF to compute cerebral FDG uptake rates, K(i), from dynamic total-body FDG PET images of control Wistar–Kyoto (WKY) rats and compared to those derived from arterial blood sampling in vivo. Dynamic FDG PET scans of WKY rats (n = 5), fasted for 6 h, were performed using the Albira Si Trimodal PET/SPECT/CT imager for 60 min. Arterial blood samples were collected for the entire imaging duration and then fitted to a seven-parameter function. The 60-min list mode PET data, corrected for attenuation, scatter, randoms, and decay, were reconstructed into 23 time bins. A 15-parameter dual-output model with SP and PV corrections was optimized with two cost functions to compute MCIF. A four-parameter compartment model was then used to compute cerebral Ki. The computed area under the curve (AUC) and K(i) were compared to that derived from arterial blood samples. Experimental and computed AUCs were 1,893.53 ± 195.39 kBq min/cc and 1,792.65 ± 155.84 kBq min/cc, respectively (p = 0.76). Bland–Altman analysis of experimental vs. computed K(i) for 35 cerebral regions in WKY rats revealed a mean difference of 0.0029 min(−1) (~13.5%). Direct (AUC) and indirect (Ki) comparisons of model computations with arterial blood sampling were performed in WKY rats. AUC and the downstream cerebral FDG uptake rates compared well with that obtained using arterial blood samples. Experimental vs. computed cerebral K(i) for the four super regions including cerebellum, frontal cortex, hippocampus, and striatum indicated no significant differences. Frontiers Media S.A. 2021-04-07 /pmc/articles/PMC8058193/ /pubmed/33898476 http://dx.doi.org/10.3389/fmed.2021.618645 Text en Copyright © 2021 Massey, Seshadri, Paul, Mińczuk, Molinos, Li and Kundu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Massey, James C.
Seshadri, Vikram
Paul, Soumen
Mińczuk, Krzysztof
Molinos, Cesar
Li, Jie
Kundu, Bijoy K.
Model Corrected Blood Input Function to Compute Cerebral FDG Uptake Rates From Dynamic Total-Body PET Images of Rats in vivo
title Model Corrected Blood Input Function to Compute Cerebral FDG Uptake Rates From Dynamic Total-Body PET Images of Rats in vivo
title_full Model Corrected Blood Input Function to Compute Cerebral FDG Uptake Rates From Dynamic Total-Body PET Images of Rats in vivo
title_fullStr Model Corrected Blood Input Function to Compute Cerebral FDG Uptake Rates From Dynamic Total-Body PET Images of Rats in vivo
title_full_unstemmed Model Corrected Blood Input Function to Compute Cerebral FDG Uptake Rates From Dynamic Total-Body PET Images of Rats in vivo
title_short Model Corrected Blood Input Function to Compute Cerebral FDG Uptake Rates From Dynamic Total-Body PET Images of Rats in vivo
title_sort model corrected blood input function to compute cerebral fdg uptake rates from dynamic total-body pet images of rats in vivo
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058193/
https://www.ncbi.nlm.nih.gov/pubmed/33898476
http://dx.doi.org/10.3389/fmed.2021.618645
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