C. Yang, W. M. Stadler, M. Medved, G. S. Karczmar University of Chicago, Chicago, IL, United States Introduction: Accurate estimation of the arterial input function (AIF) is essential for quantitative analysis of DCE-MRI data. We have previously demonstrated that a common AIF can be estimated from the contrast agent concentration versus time curves (Ct(t)) in two reference tissues with differen...

Elias Kellner, Irina Mader, Daniel Nico Splitthoff, Marco Reisert, Katharina Förster, Thao Nguyen-Thanh, Peter Gall, and Valerij G. Kiselev Department of Radiology, Medical Physics, University Medical Center Freiburg, D-79106 Freiburg, Germany, Section of Neuroradiology, Neurocenter of the Freiburg University Hospital, D-79106 Freiburg, Germany, Department of Cardiovascular Surgery, Albert-Ludw...

Institute of Neuroscience and Medicine – 4, Forschungszentrum Juelich GmbH, Germany This work focuses on the study of simultaneous dynamic MR-PET acquisition in brain tumour patients. MR-based perfusion-weighted imaging (PWI) and PET [18F]-FET are dynamic methods, which allow to evaluate tumour metabolism in a quantitative way. In both methods, arterial input function (AIF) is necessary for qua...

Quantification of cerebral blood flow (CBF) using dynamic-susceptibility contrast MRI relies on the deconvolution of the arterial input function (AIF), which is commonly estimated from the signal changes in a major artery. However, it has been shown that the presence of bolus delay/dispersion between the artery and the tissue of interest can be a significant source of error. These effects could...

X. Li, E. Welch, A. Chakravarthy, I. Mayer, M. Kelley, I. Meszoely, J. Means-Powell, J. C. Gore, and T. E. Yankeelov Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States, Institute of Imaging Science, Nashville, TN, United States, Philips Healthcare, Nashville, TN, United States, Radiation Oncology, Vanderbilt University, Medical Oncology, Vanderbilt Universi...

Background Quantitative myocardial perfusion imaging requires correct measurement of arterial Gd concentration as the input function (AIF). An underestimation of AIF Gd concentration will lead to overestimation of myocardial blood flow (MBF). One source of this underestimation is the T2* effect due to high Gd concentration in the AIF measurement. Despite the short echo time (0.65 ms) used in th...

BACKGROUND AND PURPOSE The arterial input function (AIF) is critical in determining hemodynamic parameters quantitatively with bolus-tracking MRI. We studied the effect of varying the location of measurement of AIF on the volume of hypoperfusion. We compared the volumes of hypoperfusion obtained with different AIFs with the final ischemic lesion volume. METHODS We included 13 patients with ac...

Uncertainty in arterial input function (AIF) estimation is one of the major errors in the quantification of dynamic contrast-enhanced MRI. A blind source separation algorithm was proposed to determine the AIF by selecting the voxel time course with maximum purity, which represents a minimal contamination from partial volume effects. Simulations were performed to assess the partial volume effect...

Introduction: Dynamic Contrast Enhanced (DCE) MRI and pharmacokinetic modeling have shown promise for imaging tumours based on tissue vascularity [1]. The volume transfer function between the plasma and interstitial space, K, can be determined based on measurements of contrast agent concentration time-courses in these spaces [2]. The results of DCE-MRI are believed to have clinical significance...