Influence of amplitude‐related perfusion parameters in the parotid glands by non‐fat‐saturated dynamic contrast‐enhanced magnetic resonance imaging

Chiu, Su-Chin; Cheng, Chih-Jen; Chang, Hing‐Chiu; Chung, Hsiao‐Wen; Chiu, Hui-Chu; Liu, Yi-Jui; Hsu, Hsian-He; Juan, Chun-Jung

doi:10.1118/1.4943798

Cited by 2 publications

(3 citation statements)

References 41 publications

(55 reference statements)

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“…We strictly followed the ethical principle to recruit the smallest number of healthy participants (to receive gadolinium-required DCE-MRI) possible while maintaining optimal power for statistical analysis. We similarly chose a minimal sample of participant for a previous study 20 . This limitation was remedied by data augmentation: we chose two vertebrae from each participant, resulting in a pool of 16 vertebrae to examine.…”

Section: Discussionmentioning

confidence: 99%

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

Liu

Yao

Lin

et al. 2021

Sci Rep

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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 Ktrans, ve, and vp, 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, Ktrans and ve increased as the peak in the AIF decreased, but vp increased when delay time in the AIF increased. In humans, the estimated Ktrans and ve 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.

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Section: Discussionmentioning

confidence: 99%

“…A total of eight healthy volunteers (mean age 36.9 years; range 23-64 years; 5 male) were enrolled in this prospective study. Enrollment was limited to eight to minimize risks associated with the intravenous injection of gadolinium-based contrast agent, as mentioned elsewhere 20 .…”

Section: Methodsmentioning

confidence: 99%

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

Liu

Yao

Lin

et al. 2021

Sci Rep

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“…Therefore, the influence of fat on the ADC measurement on SS-EP-DWI is usually neglected. Reduced extravascular and extracellular space has been considered to be one of the causes of alternation of tissue perfusion [ 47 ]. Results of microscopic examination of our phantom study clearly demonstrate the gradual reduction of space outside the fat droplets and glass beads parallel to the increased amount of fat droplets and glass beads step by step.…”

Section: Discussionmentioning

confidence: 99%

Understanding ADC variation by fat content effect using a dual-function MRI phantom

Liu,

Tsai,

et al. 2024

Eur Radiol Exp

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Background A dual-function phantom designed to quantify the apparent diffusion coefficient (ADC) in different fat contents (FCs) and glass bead densities (GBDs) to simulate the human tissues has not been documented yet. We propose a dual-function phantom to quantify the FC and to measure the ADC at different FCs and different GBDs. Methods A fat-containing diffusion phantom comprised by 30 glass-bead-containing fat-water emulsions consisting of six different FCs (0, 10, 20, 30, 40, and 50%) multiplied by five different GBDs (0, 0.1, 0.25, 0.5, and 1.0 g/50 mL). The FC and ADC were measured by the “iterative decomposition of water and fat with echo asymmetry and least squares estimation-IQ,” IDEAL-IQ, and single-shot echo-planar diffusion-weighted imaging, SS-EP-DWI, sequences, respectively. Linear regression analysis was used to evaluate the relationship among the fat fraction (FF) measured by IDEAL-IQ, GBD, and ADC. Results The ADC was significantly, negatively, and linearly associated with the FF (the linear slope ranged from -0.005 to -0.017, R2 = 0.925 to 0.986, all p < 0.001). The slope of the linear relationship between the ADC and the FF, however, varied among different GBDs (the higher the GBD, the lower the slope). ADCs among emulsions across different GBDs and FFs were overlapped. Emulsions with low GBDs plus high FFs shared a same lower ADC range with those with median or high GBDs plus median or lower FFs. Conclusions A novel dual-function phantom simulating the human tissues allowed to quantify the influence of FC and GBD on ADC. Relevance statement The study developed an innovative dual-function MRI phantom to explore the impact of FC on ADC variation that can affect clinical results. The results revealed the superimposed effect on FF and GBD density on ADC measurements. Key points • A dual-function phantom made of glass bead density (GBD) and fat fraction (FF) emulsion has been developed. • Apparent diffusion coefficient (ADC) values are determined by GBD and FF. • The dual-function phantom showed the mutual ADC addition between FF and GBD. Graphical Abstract

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Influence of amplitude‐related perfusion parameters in the parotid glands by non‐fat‐saturated dynamic contrast‐enhanced magnetic resonance imaging

Abstract: On NFS DCE-MRI, quantification of parotid perfusion is adversely affected by the presence of fat signals for all amplitude-related parameters. The influence could be reduced on FS scans.

Cited by 2 publications

References 41 publications

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

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

Understanding ADC variation by fat content effect using a dual-function MRI phantom

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