Estimation of tissue perfusion by dynamic contrast-enhanced imaging: simulation-based evaluation of the steepest slope method

Brix, Gunnar; Zwick, Stefan; Griebel, Juergen; Fink, Christian; Kießling, Fabian

doi:10.1007/s00330-010-1787-6

Cited by 38 publications

(43 citation statements)

References 28 publications

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“…One‐region uptake models can be fitted using standard non‐linear fitting algorithms or by a linearized method as in the Patlak model (Equation ). An alternative algorithm is known as the maximum‐slope or steepest slope technique :

K = \frac{\max \{\frac{d C}{d t} (t)\}}{\max \{c_{normala} (t)\}}

…”

Section: Constrained Modelsmentioning

confidence: 99%

Classic models for dynamic contrast‐enhanced MRI

2013

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Dynamic contrast-enhanced MRI (DCE-MRI) is a functional MRI method where T1 -weighted MR images are acquired dynamically after bolus injection of a contrast agent. The data can be interpreted in terms of physiological tissue characteristics by applying the principles of tracer-kinetic modelling. In the brain, DCE-MRI enables measurement of cerebral blood flow (CBF), cerebral blood volume (CBV), blood-brain barrier (BBB) permeability-surface area product (PS) and the volume of the interstitium (ve ). These parameters can be combined to form others such as the volume-transfer constant K(trans) , the extraction fraction E and the contrast-agent mean transit times through the intra- and extravascular spaces. A first generation of tracer-kinetic models for DCE-MRI was developed in the early 1990s and has become a standard in many applications. Subsequent improvements in DCE-MRI data quality have driven the development of a second generation of more complex models. They are increasingly used, but it is not always clear how they relate to the models of the first generation or to the model-free deconvolution methods for tissues with intact BBB. This lack of understanding is leading to increasing confusion on when to use which model and how to interpret the parameters. The purpose of this review is to clarify the relation between models of the first and second generations and between model-based and model-free methods. All quantities are defined using a generic terminology to ensure the widest possible scope and to reveal the link between applications in the brain and in other organs.

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K = \frac{\max \{\frac{d C}{d t} (t)\}}{\max \{c_{normala} (t)\}}

…”

Section: Constrained Modelsmentioning

confidence: 99%

Classic models for dynamic contrast‐enhanced MRI

2013

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“…One of the reasons of the inaccuracy is that the steepest slope model does not account for the outflow of the contrast, with errors becoming larger in highly perfused tissues. According to simulations in Brix et al underestimation of perfusion values obtained by the steepest slope method were under 16% or 23%, depending on the noise level and sampling frequency and a true perfusion being less than 0.5 mL/mL/min. Above this limit, the bias increases markedly to more than 30% at true perfusion of 1 mL/mL/min.…”

Section: Discussionmentioning

confidence: 98%

Placental perfusion in uterine ischemia model as evaluated by dynamic contrast enhanced MRI

Drobyshevsky¹,

Prasad

2015

Magnetic Resonance Imaging

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Background To validate DCE MRI method of placental perfusion estimation and to demonstrate application of the method in a rabbit model of fetal antenatal hypoxia-ischemia. Methods Placental perfusion was estimated by dynamic contrast imaging with bolus injection of Gd-DTPA in 3 Tesla GE magnet in a rabbit model of placental ischemia–reperfusion in rabbit dams at embryonic day 25 gestation age. Placental perfusion was measured using steepest slope method on DCE MRI before and after intermittent 40 min uterine ischemia. Antioxidants (n = 2 dams, 9 placentas imaged) or vehicle (n = 5 dams, 23 placenta imaged) were given systemically in a separate group of dams during reperfusion–reoxygenation. Placental perfusion was also measured in two dams from the antioxidant group (10 placentas) and two dams from the control group (12 placentas) by fluorescent microspheres method. Results While placental perfusion estimates between fluorescent microspheres and DCE MRI were significantly correlated (R2 = 0.85; P < 0.01), there was approximately 33% systematic underestimation by the latter technique. DCE MRI showed a significant decrease in maternal placental perfusion in reperfusion–reoxygenation phase in the saline, 0.44 ± 0.06 mL/min/g (P = 0.012, t-test), but not in the antioxidant group, 0.62 ± 0.06 mL/min/g, relative to preocclusion values (0.77 ± 0.07 and 0.84 ± 0.12 mL/min/g, correspondingly). Conclusion Underestimation of true perfusion in placenta by steepest slope DCE MRI is significant and the error appears to be systematic.

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“…Even in case no contrast agent is present, noise present in the data still leads to a measurable slope, which in turn leads to an overestimation of the perfusion. Likewise, the steepest slope model is also known to underestimate perfusion in case of a high perfusion situation if the sampling of data points is too low [20].…”

Section: Discussionmentioning

confidence: 98%

Automatic differentiation of placental perfusion compartments by time-to-peak analysis in mice

et al. 2015

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Estimation of tissue perfusion by dynamic contrast-enhanced imaging: simulation-based evaluation of the steepest slope method

Abstract: The steepest slope method allows absolute quantification of tissue perfusion in a computationally simple and numerically robust manner. The achievable degree of accuracy and precision is considered to be adequate for most clinical applications.

Cited by 38 publications

References 28 publications

Classic models for dynamic contrast‐enhanced MRI

Classic models for dynamic contrast‐enhanced MRI

Placental perfusion in uterine ischemia model as evaluated by dynamic contrast enhanced MRI

Automatic differentiation of placental perfusion compartments by time-to-peak analysis in mice

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