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Optimization of time frame binning for FDOPA uptake quantification in glioma

INTRODUCTION: 3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine (FDOPA) uptake quantification in glioma assessment can be distorted using a non-optimal time frame binning of time-activity curves (TAC). Under-sampling or over-sampling dynamic PET images induces significant variations on kinetic parameters...

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Autores principales: Girard, Antoine, Saint-Jalmes, Hervé, Chaboub, Nibras, Le Reste, Pierre-Jean, Metais, Alice, Devillers, Anne, Le Jeune, Florence, Palard-Novello, Xavier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7176128/
https://www.ncbi.nlm.nih.gov/pubmed/32320440
http://dx.doi.org/10.1371/journal.pone.0232141
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author Girard, Antoine
Saint-Jalmes, Hervé
Chaboub, Nibras
Le Reste, Pierre-Jean
Metais, Alice
Devillers, Anne
Le Jeune, Florence
Palard-Novello, Xavier
author_facet Girard, Antoine
Saint-Jalmes, Hervé
Chaboub, Nibras
Le Reste, Pierre-Jean
Metais, Alice
Devillers, Anne
Le Jeune, Florence
Palard-Novello, Xavier
author_sort Girard, Antoine
collection PubMed
description INTRODUCTION: 3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine (FDOPA) uptake quantification in glioma assessment can be distorted using a non-optimal time frame binning of time-activity curves (TAC). Under-sampling or over-sampling dynamic PET images induces significant variations on kinetic parameters quantification. We aimed to optimize temporal time frame binning for dynamic FDOPA PET imaging. METHODS: Fourteen patients with 33 tumoral TAC with biopsy-proven gliomas were analysed. The mean SUVmax tumor-to-brain ratio (TBRmax) were compared at 20 min and 35 min post-injection (p.i). Five different time frame samplings within 20 min were compared: 11x10sec-6x15sec-5x20sec-3x300sec; 8x15sec– 2x30sec– 2x60sec– 3x300sec; 6x20sec– 8x60sec– 2x300sec; 10x30sec– 3x300sec and 4x45sec– 3x90sec– 5x150sec. The reversible single-tissue compartment model with blood volume parameter (VB) was selected using the Akaike information criterion. K1 values extracted from 1024 noisy simulated TAC using Monte Carlo method from the 5 different time samplings were compared to a target K1 value as the objective, which is the average of the K1 values extracted from the 33 lesions using an imaging-derived input function for each patient. RESULTS: The mean TBRmax was significantly higher at 20 min p.i. than at 35 min p.i (respectively 1.4 +/- 0.8 and 1.2 +/- 0.6; p <0.001). The target K1 value was 0.161 mL/ccm/min. The 8x15sec– 2x30sec– 2x60sec– 3x300sec time sampling was the optimal time frame binning. K1 values extracted using this optimal time frame binning were significantly different with K1 values extracted from the other time frame samplings, except with K1 values obtained using the 11x10sec– 6x15sec –5x20sec-3x300sec time frame binning. CONCLUSIONS: This optimal sampling schedule design (8x15sec– 2x30sec– 2x60sec– 3x300sec) could be used to minimize bias in quantification of FDOPA uptake in glioma using kinetic analysis.
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spelling pubmed-71761282020-05-12 Optimization of time frame binning for FDOPA uptake quantification in glioma Girard, Antoine Saint-Jalmes, Hervé Chaboub, Nibras Le Reste, Pierre-Jean Metais, Alice Devillers, Anne Le Jeune, Florence Palard-Novello, Xavier PLoS One Research Article INTRODUCTION: 3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine (FDOPA) uptake quantification in glioma assessment can be distorted using a non-optimal time frame binning of time-activity curves (TAC). Under-sampling or over-sampling dynamic PET images induces significant variations on kinetic parameters quantification. We aimed to optimize temporal time frame binning for dynamic FDOPA PET imaging. METHODS: Fourteen patients with 33 tumoral TAC with biopsy-proven gliomas were analysed. The mean SUVmax tumor-to-brain ratio (TBRmax) were compared at 20 min and 35 min post-injection (p.i). Five different time frame samplings within 20 min were compared: 11x10sec-6x15sec-5x20sec-3x300sec; 8x15sec– 2x30sec– 2x60sec– 3x300sec; 6x20sec– 8x60sec– 2x300sec; 10x30sec– 3x300sec and 4x45sec– 3x90sec– 5x150sec. The reversible single-tissue compartment model with blood volume parameter (VB) was selected using the Akaike information criterion. K1 values extracted from 1024 noisy simulated TAC using Monte Carlo method from the 5 different time samplings were compared to a target K1 value as the objective, which is the average of the K1 values extracted from the 33 lesions using an imaging-derived input function for each patient. RESULTS: The mean TBRmax was significantly higher at 20 min p.i. than at 35 min p.i (respectively 1.4 +/- 0.8 and 1.2 +/- 0.6; p <0.001). The target K1 value was 0.161 mL/ccm/min. The 8x15sec– 2x30sec– 2x60sec– 3x300sec time sampling was the optimal time frame binning. K1 values extracted using this optimal time frame binning were significantly different with K1 values extracted from the other time frame samplings, except with K1 values obtained using the 11x10sec– 6x15sec –5x20sec-3x300sec time frame binning. CONCLUSIONS: This optimal sampling schedule design (8x15sec– 2x30sec– 2x60sec– 3x300sec) could be used to minimize bias in quantification of FDOPA uptake in glioma using kinetic analysis. Public Library of Science 2020-04-22 /pmc/articles/PMC7176128/ /pubmed/32320440 http://dx.doi.org/10.1371/journal.pone.0232141 Text en © 2020 Girard et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Girard, Antoine
Saint-Jalmes, Hervé
Chaboub, Nibras
Le Reste, Pierre-Jean
Metais, Alice
Devillers, Anne
Le Jeune, Florence
Palard-Novello, Xavier
Optimization of time frame binning for FDOPA uptake quantification in glioma
title Optimization of time frame binning for FDOPA uptake quantification in glioma
title_full Optimization of time frame binning for FDOPA uptake quantification in glioma
title_fullStr Optimization of time frame binning for FDOPA uptake quantification in glioma
title_full_unstemmed Optimization of time frame binning for FDOPA uptake quantification in glioma
title_short Optimization of time frame binning for FDOPA uptake quantification in glioma
title_sort optimization of time frame binning for fdopa uptake quantification in glioma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7176128/
https://www.ncbi.nlm.nih.gov/pubmed/32320440
http://dx.doi.org/10.1371/journal.pone.0232141
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