Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function

Abstract The purpose of this study was to investigate the influence of arterial input function (AIF) selection on the quantification of vertebral perfusion using axial dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In this study, axial DCE-MRI was performed on 2 vertebrae in each of...

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Autores principales:	Yi-Jui Liu, Hou-Ting Yang, Melissa Min-Szu Yao, Shao-Chieh Lin, Der-Yang Cho, Wu-Chung Shen, Chun-Jung Juan, Wing P. Chan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/73aa328b2a2b40bfafb93affe625b151
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spelling	oai:doaj.org-article:73aa328b2a2b40bfafb93affe625b1512021-12-02T14:06:11ZQuantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function10.1038/s41598-021-82300-62045-2322https://doaj.org/article/73aa328b2a2b40bfafb93affe625b1512021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82300-6https://doaj.org/toc/2045-2322Abstract The purpose of this study was to investigate the influence of arterial input function (AIF) selection on the quantification of vertebral perfusion using axial dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In this study, axial DCE-MRI was performed on 2 vertebrae in each of eight healthy volunteers (mean age, 36.9 years; 5 men) using a 1.5-T scanner. The pharmacokinetic parameters K trans , v e , and v p , derived using a Tofts model on axial DCE-MRI of the lumbar vertebrae, were evaluated using various AIFs: the population-based aortic AIF (AIF_PA), a patient-specific aortic AIF (AIF_A) and a patient-specific segmental arterial AIF (AIF_SA). Additionally, peaks and delay times were changed to simulate the effects of various AIFs on the calculation of perfusion parameters. Nonparametric analyses including the Wilcoxon signed rank test and the Kruskal–Wallis test with a Dunn–Bonferroni post hoc analysis were performed. In simulation, K trans and v e increased as the peak in the AIF decreased, but v p increased when delay time in the AIF increased. In humans, the estimated K trans and v e were significantly smaller using AIF_A compared to AIF_SA no matter the computation style (pixel-wise or region-of-interest based). Both these perfusion parameters were significantly greater using AIF_SA compared to AIF_A.Yi-Jui LiuHou-Ting YangMelissa Min-Szu YaoShao-Chieh LinDer-Yang ChoWu-Chung ShenChun-Jung JuanWing P. ChanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yi-Jui Liu Hou-Ting Yang Melissa Min-Szu Yao Shao-Chieh Lin Der-Yang Cho Wu-Chung Shen Chun-Jung Juan Wing P. Chan Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function
description	Abstract The purpose of this study was to investigate the influence of arterial input function (AIF) selection on the quantification of vertebral perfusion using axial dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In this study, axial DCE-MRI was performed on 2 vertebrae in each of eight healthy volunteers (mean age, 36.9 years; 5 men) using a 1.5-T scanner. The pharmacokinetic parameters K trans , v e , and v p , derived using a Tofts model on axial DCE-MRI of the lumbar vertebrae, were evaluated using various AIFs: the population-based aortic AIF (AIF_PA), a patient-specific aortic AIF (AIF_A) and a patient-specific segmental arterial AIF (AIF_SA). Additionally, peaks and delay times were changed to simulate the effects of various AIFs on the calculation of perfusion parameters. Nonparametric analyses including the Wilcoxon signed rank test and the Kruskal–Wallis test with a Dunn–Bonferroni post hoc analysis were performed. In simulation, K trans and v e increased as the peak in the AIF decreased, but v p increased when delay time in the AIF increased. In humans, the estimated K trans and v e were significantly smaller using AIF_A compared to AIF_SA no matter the computation style (pixel-wise or region-of-interest based). Both these perfusion parameters were significantly greater using AIF_SA compared to AIF_A.
format	article
author	Yi-Jui Liu Hou-Ting Yang Melissa Min-Szu Yao Shao-Chieh Lin Der-Yang Cho Wu-Chung Shen Chun-Jung Juan Wing P. Chan
author_facet	Yi-Jui Liu Hou-Ting Yang Melissa Min-Szu Yao Shao-Chieh Lin Der-Yang Cho Wu-Chung Shen Chun-Jung Juan Wing P. Chan
author_sort	Yi-Jui Liu
title	Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function
title_short	Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function
title_full	Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function
title_fullStr	Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function
title_full_unstemmed	Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function
title_sort	quantifying lumbar vertebral perfusion by a tofts model on dce-mri using segmental versus aortic arterial input function
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/73aa328b2a2b40bfafb93affe625b151
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Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function

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