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

Abstract

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.

Estimation of pharmacokinetic parameters from DCE‐MRI by extracting long and short time‐dependent features using an LSTM network

“…The version of the extended Tofts model and direct model fitting used in this study are described briefly. In our implementation, a contrast bolus arrival time (BAT), for each tissue voxel is considered for the accurate PK parameter estimation 22,23 . The implemented extended Tofts model is written as: where is the CA concentration in the tissue voxel, is the CA concentration in the arterial blood (or AIF), is the transfer rate constant of the CA that diffuses from the blood vessel to the interstitial space, is the rate constant of the CA efflux from the interstitial space to the blood plasma, and Hct is the small vessel hematocrit.…”

“…In our implementation, a contrast bolus arrival time (BAT), s BAT ðrÞ for each tissue voxel is considered for the accurate PK parameter estimation. 22,23 The implemented extended Tofts model is written as:…”

Concurrent measurement of perfusion parameters related to small blood vessels and cerebrospinal fluid circulation in the human brain using dynamic dual‐spin‐echo perfusion MRI

“…In addition, T onset and T return were also estimated with a spline model developed in previous studies. 38 The long-TE images in the proposed approach and cDSC scans were further analyzed using in-house Matlab code, from which ΔS/S, T onset , and TTP were computed using the same procedure as in our previous study. 16 Briefly, T onset was defined as the time when significant signal change (20% of the peak ΔS/S) is detected in the dynamic TSE scans after Gd injection.…”

“…T onset and T return were defined as the time when ∆S/S rises above or drops below 20% of the peak ∆S/S, respectively. In addition, T onset and T return were also estimated with a spline model developed in previous studies 38 …”

“…[Gd] in the CSF after TTP (i.e., peak Gd concentration) was computed as outlined above and in the supporting information. In addition, similar to the short‐TE data, T onset was also estimated using the same spline model, which was designed for time courses with relatively slow dynamic signal changes 38 …”