Sangjune Laurence Lee¹, Warren Foltz¹, Brandon Driscoll¹, Ali Fatemi¹, Cynthia Menard¹, Catherine Coolens¹, and Caroline Chung^1
1Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada

Determining the arterial input function (AIF) is critical for the accuracy of kinetic modeling of DCE MRI measures. However, the magnitude signal derived AIF suffers from in-flow, slice profile, and T2* effects. Phase signal has been shown to be an alternative method of acquiring the AIF data. Here, we evaluate the accuracy of AIFs derived from the magnitude and phase signal in a dynamic flow phantom, providing a controlled, gold-standard framework. The phase-derived AIF approached actual peak Gd-DTPA concentrations within all imaging slices and at tested flow rates up to 7.5 mL/s, while the magnitude-derived AIF was grossly attenuated.

Mihaela Rata¹, David Collins¹, James Darcy¹, Christina Messiou¹, Nina Tunariu¹, Martin Leach¹, Nandita Desouza¹, and Matthew Orton^1
1MRI Unit, CR-UK and EPSRC Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden Hospital, Sutton, United Kingdom

Dynamic contrast enhanced MRI requires an estimate/measurement of the arterial input function (AIF) to derive pharmacokinetic parameters. This study investigated a cohort of 21 patients, evaluating the usefulness of measured patient specific AIF’s as derived from pre-bolus compared with a population-based averaged AIF. The variation of extracted AIF’s was explored over 3 vertical segments of the aorta in order to define the most reproducible region. The reproducibility of the pharmacokinetic parameter Ktrans was measured using various AIF’s. The results suggest no improvement of the study reproducibility when using the individual AIF derived from coronal pre-bolus data.

Andrea Holt¹, Edoardo Pasca¹, Stijn W. Heijmink², Jelle Teertstra², Sara H. Muller², and Uulke A. van der Heide^1
1Department of Radiation Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, Netherlands, ²Department of Radiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, Netherlands

In prostate cancer patients, we studied the effect of overall contrast agent injection time on the form of the arterial input function and on the outcome of pharmaco-kinetic analysis in healthy tissue. We found that below an overall injection time of 10 s no further sharpening of the first pass peak is observed.

Jennifer Moroz¹, Andrew Yung¹, Piotr Kozlowski¹, and Stefan Reinsberg^1
1Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada

Quantitative DCE-MRI analysis requires an accurate measure of the arterial input function (AIF). The AIF should have a high temporal resolution and be acquired for each experiment. However, AIF acquisition in mice is challenging because of their small size and rapid heart rates. This work demonstrates that a high temporal resolution AIF may be determined from a series of projection scans using phase data. An AIF in a mouse tail, having a temporal resolution of 100 ms, was successfully measured. The results suggest that rapid AIF acquisition in a mouse is possible and it may be interleaved with DCE experiments.

Tobias Heye¹, Matthew Davenport², Jeff Horvath¹, Sebastian Feuerlein¹, Steven Breault¹, Mustafa Bashir¹, Elmar M. Merkle¹, and Daniel T. Boll^1
1Department of Radiology, Duke University Medical Center, Durham, NC, United States, ²Department of Radiology, University of Michigan Health System, Ann Arbor, MI, United States

Although many factors contributing to overall measurement error have been identified, the effect of commercially available DCE-MRI post-processing solutions on quantitative (Ktrans, kep, ve) and semi-quantitative (iAUGC) pharmacokinetic parameters has yet to be defined. This study assessed the reproducibility of pharmacokinetic parameters between various commercially available post-processing solutions for DCE-MRI (Tissue4D^TM, Siemens, Germany; DynaCAD^TM, Invivo, USA; Aegis^TM, Sentinelle Medical, Canada; CADvue^TM; iCAD, Inc., USA). There is substantial variability (25.1-74.1% coefficient of variation) for DCE-MRI pharmacokinetic parameters across commercially available DCE-MRI post-processing solutions. If DCE-MRI is to succeed as a widely incorporated biomarker, the industry must agree on a post-processing standard.

Hassan Bagher-Ebadian^1,2, Siamak P Nejad-Davarani^1,3, Rajan Jain⁴, Douglas Noll³, Quan Jiang¹, Ali Syed Arbab⁴, Tom Mikkelsen⁵, and James R Ewing^1,2
1Neurology, Henry Ford Hospital, Detroit, Michigan, United States, ²Physics, Oakland University, Rochester, Michigan, United States, ³Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States, ⁴Radiology, Henry Ford Hospital, Detroit, Michigan, United States,⁵Neurosurgery, Henry Ford Hospital, Detroit, Michigan, United States

DCE-pharmacokinetic models rely on the construction of an observation equation which demands conversion of the measured signal intensity (SI) profile into an indicator concentration time-course. Recent studies have proposed that the normalized SI [(St-S0)/S0] be used instead of the longitudinal-relaxation-rate change (ΔR1) in DCE-MRI permeability analyses. However, we know of no assessment of the agreement in the estimated permeability parameters using different measures of concentrations (SI-ΔR1). The goal of this study is to evaluate the use of SI, as opposed to ΔR1, in the estimation of permeability parameters in DCE-T1-3D-Spoiled-Gradient-Echo studies in the brains of ten treatment-naïve patients with glioblastoma.

Anders Garpebring¹, Patrik Brynolfsson¹, Jun Yu², Ronnie Wirestam³, Adam Johansson¹, Thomas Asklund⁴, and Mikael Karlsson^1
1Dept. of Radiation Sciences, Umeå University, Umeå, Sweden, ²Centre of Biostatistics, Swedish University of Agricultural Sciences, Umeå, Sweden,³Dept. of Medical Radiation Physics, Lund University, Lund, ⁴Division of Oncology, Dept. of Radiation Sciences, Umeå University, Umeå, Sweden

In dynamic contrast-enhanced MRI, errors propagate in a highly non-trivial way from a number of sources of uncertainty to the parametric maps. A method for uncertainty estimation, based on multivariate linear error propagation, was developed and evaluated. Comparison with Monte Carlo simulations showed good agreement for uncertainties introduced by noise in the dynamic signal, noise in baseline signal, noise in baseline T1, and amplitude errors in the arterial input function. The feasibility of spatially resolved maps of uncertainty subdivided by origin was also demonstrated on in vivo data.

Wenchao Cai¹, Feiyu Li¹, Jing Wang², Jue Zhang^2,3, Xiaoying Wang^1,2, and Xuexiang Jiang^1
1Department of Radiology, Peking University First Hospital, Beijing, Beijing, China, ²Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, Beijing, China, ³College of Engineering, Peking University, Beijing, Beijing, China

Introduction:Arterial spin labeling (ASL) MRI has the advantage of no administration of the extrinsic tracer which are capable of absolutely quantitatively measuring the microvascular perfusion characteristics of tissue. Purpose: To explore the correlation between the BF from ASL and kinetic parameters from DCE-MRI in patients with prostate cancer.Methods: Six patients with pathologically confirmed prostate cancer were recruited in this study to take the PASL pulse sequence and DCE MR examinations. Results:Significant positive correlations between BF value and Ktrans, Kep were observed in all four TI (p < 0.05, Spearman¡¯s correlation analysis). However, no significant correlation between BF and Ve was found. Conclusion:The arterial spin labeling sequence with no contrast medium allows extraction of blood flow information specific to the angiogenic process of prostate.

Wieland H Sommer¹, Marco Armbruster¹, Steven Sourbron¹, Maximilian F Reiser¹, and Christoph Zech^1
1Department of Clinical Radiology, University of Munich, Großhadern Hospital, Munich, Bavaria, Germany

A dynamic contrast enhanced MRI protocol for the liver was established in neuroendocrine tumors with liver metastases. To find the clinical value of DCE-MRI parameters, these were correlated with FDG-PET-CT parameters and clinical parameters. We found that the arterial plasma flow highly correlates with SUV vales from PET-CT and therefore can monitor the metabolism of the metastases. Other parameters correlated with tumor markers or clinical outcome parameters.