Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging

Mehrtash, Alireza; Gupta, Sandeep; Shanbhag, Dattesh; Miller, James V.; Kapur, Tina; Fennessy, Fiona M.; Kikinis, Ron; Fedorov, Andriy

doi:10.1117/1.jmi.3.1.014503

Cited by 11 publications

(13 citation statements)

References 40 publications

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“…However, determining the AIF remains technically challenging because of the location of the upstream, slice orientation, partial volume, and flow artifacts. Studies have shown that AIF can have a large effect on the accuracy of computed pharmacokinetic parameters [32][33][34] . Theoretically, a local AIF sampled at the inlet to the target tissue should be selected.…”

Section: Discussionmentioning

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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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%

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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“…; Mehrtash et al. ; Paling et al. )) measures the time delay for arterial blood to travel to the capillaries of the tissue from a major upstream artery, such as the popliteal artery, and directly reflects blood transit velocity and/or the route through upstream arteries and arterioles.…”

Section: Introductionmentioning

confidence: 99%

Exercise-stimulated arterial transit time in calf muscles measured by dynamic contrast-enhanced magnetic resonance imaging

et al. 2019

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The primary goal of this study was to evaluate arterial transit time (ATT) in exercise‐stimulated calf muscles as a promising indicator of muscle function. Following plantar flexion, ATT was measured by dynamic contrast‐enhanced (DCE) MRI in young and elderly healthy subjects and patients with peripheral artery disease (PAD). In the young healthy subjects, gastrocnemius ATT decreased significantly (P < 0.01) from 4.3 ± 1.5 to 2.4 ± 0.4 sec when exercise load increased from 4 lbs to 16 lbs. For the same load of 4 lbs, gastrocnemius ATT was lower in the elderly healthy subjects (3.2 ± 1.1 sec; P = 0.08) and in the PAD patients (2.4 ± 1.2 sec; P = 0.02) than in the young healthy subjects. While the sensitivity of the exercise‐stimulated ATT is diagnostically useful, it poses a challenge for arterial spin labeling (ASL), a noncontrast MRI method for measuring muscle perfusion. As a secondary goal of this study, we assessed the impact of ATT on ASL‐measured perfusion with ASL data of multiple post labeling delays (PLDs) acquired from a healthy subject. Perfusion varied substantially with PLD in the activated gastrocnemius, which can be attributed to the ATT variability as verified by a simulation. In conclusion, muscle ATT is sensitive to exercise intensity, and it potentially reflects the functional impact of aging and PAD on calf muscles. For precise measurement of exercise‐stimulated muscle perfusion, it is recommended that ATT be considered when quantifying muscle ASL data.

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“…Estimating the time delay between the arrival of the CA in the upstream artery and the tissue of interest accurately is an important step to obtain correct parameters from pharmacokinetic modelling of DCE-MRI data (Mehrtash et al, 2016). One way to reliably obtain the delay is to take the time difference between the estimates of the BATs of the TCC and of the AIF, respectively (Kershaw and Buckley, 2006).…”

Section: Discussionmentioning

confidence: 99%

Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models

et al. 2019

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Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify perfusion and vascular permeability. In most cases a bolus arrival time (BAT) delay exists between the arterial input function (AIF) and the contrast agent arrival in the tissue of interest which needs to be estimated. Existing methods for BAT estimation are tailored to tissue concentration curves which have a fast upslope to the peak as frequently observed in patient data. However, they may give poor results for curves that do not have this characteristic shape such as tissue concentration curves of small animals. In this paper, we propose a novel method for BAT estimation of signals that do not have a fast upslope to their peak. The model is based on splines which are able to adapt to a large variety of concentration curves. Furthermore, the method estimates BATs on a continuous time scale. All relevant model parameters are automatically determined by generalized cross validation. We use simulated concentration curves of small animal and patient settings to assess the accuracy and robustness of our approach. The proposed method outperforms a state-of-theart method for small animal data and it gives competitive results for patient data. Finally, it is tested on in vivo acquired rat data where accuracy of BAT estimation was also improved upon the state-of-the-art method. The results indicate that the proposed method is suitable for accurate BAT estimation of DCE-MRI data, especially for small animals. arXiv:1811.10672v1 [physics.med-ph] 26 Nov 2018 t N t 1 (u (k) (τ )) 2 dτ. It has been shown that an interpolating spline is a piecewise function consisting of polynomials of maximum degree 2k − 1 on [t n , t n+1 ], for n = 1, . . . , N − 1, such that all derivatives up to order 2k − 2 coincide at the interface nodes t n . As we work with noisy data, we are interested in approximation rather than in interpolation.

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Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging

Cited by 11 publications

References 40 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

Exercise-stimulated arterial transit time in calf muscles measured by dynamic contrast-enhanced magnetic resonance imaging

Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models

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