Effects of arterial input function selection on kinetic parameters in brain dynamic contrast-enhanced MRI |
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| Affiliation: | 1. Department of Radiology, University Hospital Bonn, Sigmund-Freud-Strasse 25, 53127 Bonn, Germany;2. Philips Healthcare, Röntgenstrasse 22, 22335 Hamburg, Germany;3. IMBIE (Statistics Department), University Hospital Bonn, Sigmund-Freud-Strasse 25, 53127 Bonn, Germany;1. Aging Research Center (ARC), Karolinska Institute and Stockholm University, Sweden;2. MRI Research Center, Karolinska University Hospital, Sweden;1. Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA 30329, United States;2. Department of Anesthesiology, Emory University School of Medicine, Atlanta, GA 30322, United States;3. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, United States;4. Department of Drug Discovery Biomedical Sciences, Medical University of South Carolina, Charleston, SC 29425, United States;5. JT Pharmaceuticals Inc., Mt. Pleasant, SC 29464, United States;6. Center for Visual and Neurocognitive Rehabilitation, Atlanta VA Medical Center, Decatur, GA 30033, United States;7. Division of Neuropharmacology and Neurologic Diseases, Yerkes National Primate Research Center, Emory University, Atlanta, GA 30329, United States;1. Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA;2. Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA;3. Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA;4. Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA;5. Department of Physics, Vanderbilt University, Nashville, TN, USA;6. Department of Cancer Biology, Vanderbilt University, Nashville, TN, USA;1. Joint Department of Medical Imaging, University Health Network, University of Toronto, 610 University Ave, 3-957, Toronto ON M5G, Canada;2. Joint Department of Medical Imaging, University Health Network, 700 University Ave, Toronto ON M5G, Canada;3. Siemens Healthcare Limited, London, ON, Canada |
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| Abstract: | PurposeKinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) were suggested as a possible instrument for multi-parametric lesion characterization, but have not found their way into clinical practice yet due to inconsistent results. The quantification is heavily influenced by the definition of an appropriate arterial input functions (AIF). Regarding brain tumor DCE-MRI, there are currently several co-existing methods to determine the AIF frequently including different brain vessels as sources. This study quantitatively and qualitatively analyzes the impact of AIF source selection on kinetic parameters derived from commonly selected AIF source vessels compared to a population-based AIF model.Material and methods74 patients with brain lesions underwent 3D DCE-MRI. Kinetic parameters [transfer constants of contrast agent efflux and reflux Ktrans and kep and, their ratio, ve, that is used to measure extravascular-extracellular volume fraction and plasma volume fraction vp] were determined using extended Tofts model in 821 ROI from 4 AIF sources [the internal carotid artery (ICA), the closest artery to the lesion, the superior sagittal sinus (SSS), the population-based Parker model]. The effect of AIF source alteration on kinetic parameters was evaluated by tissue type selective intra-class correlation (ICC) and capacity to differentiate gliomas by WHO grade [area under the curve analysis (AUC)].ResultsArterial AIF more often led to implausible ve > 100% values (p < 0.0001). AIF source alteration rendered different absolute kinetic parameters (p < 0.0001), except for kep. ICC between kinetic parameters of different AIF sources and tissues were variable (0.08–0.87) and only consistent > 0.5 between arterial AIF derived kinetic parameters. Differentiation between WHO III and II glioma was exclusively possible with vp derived from an AIF in the SSS (p = 0.03; AUC 0.74).ConclusionThe AIF source has a significant impact on absolute kinetic parameters in DCE-MRI, which limits the comparability of kinetic parameters derived from different AIF sources. The effect is also tissue-dependent. The SSS appears to be the best choice for AIF source vessel selection in brain tumor DCE-MRI as it exclusively allowed for WHO grades II/III and III/IV glioma distinction (by vp) and showed the least number of implausible ve values. |
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