Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer

Purpose: To test a short 2-[18F]Fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET dynamic acquisition protocol to calculate Ki using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC).Methods: 24 patients with NSCLC who underwent standard dynamic 2-[18F]FDG acquisitions (...

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Autores principales:	Luca Indovina, Valentina Scolozzi, Amedeo Capotosti, Stelvio Sestini, Silvia Taralli, Davide Cusumano, Romina Grazia Giancipoli, Gabriele Ciasca, Giuseppe Cardillo, Maria Lucia Calcagni
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	PET dynamic acquisition Patlak graphical analysis non-small-cell lung cancer influx rate constant 2-[18F]Fluoro-2-deoxy-D-glucose Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/d9ab405d1dd240d7a3e0c13d0799c6dc
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spelling	oai:doaj.org-article:d9ab405d1dd240d7a3e0c13d0799c6dc2021-11-22T05:25:15ZShort 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer2296-858X10.3389/fmed.2021.725387https://doaj.org/article/d9ab405d1dd240d7a3e0c13d0799c6dc2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmed.2021.725387/fullhttps://doaj.org/toc/2296-858XPurpose: To test a short 2-[18F]Fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET dynamic acquisition protocol to calculate Ki using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC).Methods: 24 patients with NSCLC who underwent standard dynamic 2-[18F]FDG acquisitions (60 min) were randomly divided into two groups. In group 1 (n = 10), a population-based image-derived input function (pIDIF) was built using a monoexponential trend (10–60 min), and a leave-one-out cross-validation (LOOCV) method was performed to validate the pIDIF model. In group 2 (n = 14), Ki was obtained by standard regional Patlak plot analysis using IDIF (0–60 min) and tissue response (10–60 min) curves from the volume of interests (VOIs) placed on descending thoracic aorta and tumor tissue, respectively. Moreover, with our method, the Patlak analysis was performed to obtain Ki,s using IDIFFitted curve obtained from PET counts (0–10 min) followed by monoexponential coefficients of pIDIF (10–60 min) and tissue response curve obtained from PET counts at 10 min and between 40 and 60 min, simulating two short dynamic acquisitions. Both IDIF and IDIFFitted curves were modeled to assume the value of 2-[18F]FDG plasma activity measured in the venous blood sampling performed at 45 min in each patient. Spearman's rank correlation, coefficient of determination, and Passing–Bablok regression were used for the comparison between Ki and Ki,s. Finally, Ki,s was obtained with our method in a separate group of patients (group 3, n = 8) that perform two short dynamic acquisitions.Results: Population-based image-derived input function (10–60 min) was modeled with a monoexponential curve with the following fitted parameters obtained in group 1: a = 9.684, b = 16.410, and c = 0.068 min−1. The LOOCV error was 0.4%. In patients of group 2, the mean values of Ki and Ki,s were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively (R2 = 0.9970). The Passing–Bablok regression for comparison between Ki and Ki,s showed a slope of 0.992 (95% CI: 0.94–1.06) and intercept value of −0.0003 (95% CI: −0.0033–0.0011).Conclusions: Despite several practical limitations, like the need to position the patient twice and to perform two CT scans, our method contemplates two short 2-[18F]FDG dynamic acquisitions, a population-based input function model, and a late venous blood sample to obtain robust and personalized input function and tissue response curves and to provide reliable regional Ki estimation.Luca IndovinaValentina ScolozziAmedeo CapotostiStelvio SestiniSilvia TaralliDavide CusumanoRomina Grazia GiancipoliGabriele CiascaGabriele CiascaGiuseppe CardilloMaria Lucia CalcagniMaria Lucia CalcagniFrontiers Media S.A.articlePET dynamic acquisitionPatlak graphical analysisnon-small-cell lung cancerinflux rate constant2-[18F]Fluoro-2-deoxy-D-glucoseMedicine (General)R5-920ENFrontiers in Medicine, Vol 8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	PET dynamic acquisition Patlak graphical analysis non-small-cell lung cancer influx rate constant 2-[18F]Fluoro-2-deoxy-D-glucose Medicine (General) R5-920
spellingShingle	PET dynamic acquisition Patlak graphical analysis non-small-cell lung cancer influx rate constant 2-[18F]Fluoro-2-deoxy-D-glucose Medicine (General) R5-920 Luca Indovina Valentina Scolozzi Amedeo Capotosti Stelvio Sestini Silvia Taralli Davide Cusumano Romina Grazia Giancipoli Gabriele Ciasca Gabriele Ciasca Giuseppe Cardillo Maria Lucia Calcagni Maria Lucia Calcagni Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer
description	Purpose: To test a short 2-[18F]Fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET dynamic acquisition protocol to calculate Ki using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC).Methods: 24 patients with NSCLC who underwent standard dynamic 2-[18F]FDG acquisitions (60 min) were randomly divided into two groups. In group 1 (n = 10), a population-based image-derived input function (pIDIF) was built using a monoexponential trend (10–60 min), and a leave-one-out cross-validation (LOOCV) method was performed to validate the pIDIF model. In group 2 (n = 14), Ki was obtained by standard regional Patlak plot analysis using IDIF (0–60 min) and tissue response (10–60 min) curves from the volume of interests (VOIs) placed on descending thoracic aorta and tumor tissue, respectively. Moreover, with our method, the Patlak analysis was performed to obtain Ki,s using IDIFFitted curve obtained from PET counts (0–10 min) followed by monoexponential coefficients of pIDIF (10–60 min) and tissue response curve obtained from PET counts at 10 min and between 40 and 60 min, simulating two short dynamic acquisitions. Both IDIF and IDIFFitted curves were modeled to assume the value of 2-[18F]FDG plasma activity measured in the venous blood sampling performed at 45 min in each patient. Spearman's rank correlation, coefficient of determination, and Passing–Bablok regression were used for the comparison between Ki and Ki,s. Finally, Ki,s was obtained with our method in a separate group of patients (group 3, n = 8) that perform two short dynamic acquisitions.Results: Population-based image-derived input function (10–60 min) was modeled with a monoexponential curve with the following fitted parameters obtained in group 1: a = 9.684, b = 16.410, and c = 0.068 min−1. The LOOCV error was 0.4%. In patients of group 2, the mean values of Ki and Ki,s were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively (R2 = 0.9970). The Passing–Bablok regression for comparison between Ki and Ki,s showed a slope of 0.992 (95% CI: 0.94–1.06) and intercept value of −0.0003 (95% CI: −0.0033–0.0011).Conclusions: Despite several practical limitations, like the need to position the patient twice and to perform two CT scans, our method contemplates two short 2-[18F]FDG dynamic acquisitions, a population-based input function model, and a late venous blood sample to obtain robust and personalized input function and tissue response curves and to provide reliable regional Ki estimation.
format	article
author	Luca Indovina Valentina Scolozzi Amedeo Capotosti Stelvio Sestini Silvia Taralli Davide Cusumano Romina Grazia Giancipoli Gabriele Ciasca Gabriele Ciasca Giuseppe Cardillo Maria Lucia Calcagni Maria Lucia Calcagni
author_facet	Luca Indovina Valentina Scolozzi Amedeo Capotosti Stelvio Sestini Silvia Taralli Davide Cusumano Romina Grazia Giancipoli Gabriele Ciasca Gabriele Ciasca Giuseppe Cardillo Maria Lucia Calcagni Maria Lucia Calcagni
author_sort	Luca Indovina
title	Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer
title_short	Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer
title_full	Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer
title_fullStr	Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer
title_full_unstemmed	Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer
title_sort	short 2-[18f]fluoro-2-deoxy-d-glucose pet dynamic acquisition protocol to evaluate the influx rate constant by regional patlak graphical analysis in patients with non-small-cell lung cancer
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/d9ab405d1dd240d7a3e0c13d0799c6dc
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Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer

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