Dynamic Contrast-Enhanced MRI: Methods & Applications
Click on to view the abstract pdf. Click on to view the recorded presentation.
Tuesday 8 May 2012
Plenary Hall  13:30 - 15:30 Moderators: Josephine Naish, Steven P. Sourbron

13:30 0235.   Introduction
Steven P. Sourbron
 
13:42 0236.   
Comparison of Arterial Input Functions by Magnitude and Phase Signal Measurement in Dynamic Contrast Enhancement MRI using a Dynamic Flow Phantom
Sangjune Laurence Lee1, Warren Foltz1, Brandon Driscoll1, Ali Fatemi1, Cynthia Menard1, Catherine Coolens1, and Caroline Chung1
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.

 
13:54 0237.   Evaluation of reproducibility of measured arterial input functions and DCE-MRI derived model estimates obtained using either pre-bolus individual AIF’s or population derived AIF’s
Mihaela Rata1, David Collins1, James Darcy1, Christina Messiou1, Nina Tunariu1, Martin Leach1, Nandita Desouza1, and Matthew Orton1
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.

 
14:06 0238.   
The impact of overall injection time on the arterial input function and pharmaco-kinetic analysis using the Tofts model in DCE-MRI for prostate cancer patients
Andrea Holt1, Edoardo Pasca1, Stijn W. Heijmink2, Jelle Teertstra2, Sara H. Muller2, and Uulke A. van der Heide1
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.

 
14:18 0239.   Estimation of the Arterial Input Function in a Mouse Tail from the Signal Phase of Projection Profiles
Jennifer Moroz1, Andrew Yung1, Piotr Kozlowski1, and Stefan Reinsberg1
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.

 
14:30 0240.   
Reproducibility of Dynamic Contrast-Enhanced MRI Perfusion Parameters on various Computer Aided Diagnosis Workstations: Taking a Peek into the Black Box.
Tobias Heye1, Matthew Davenport2, Jeff Horvath1, Sebastian Feuerlein1, Steven Breault1, Mustafa Bashir1, Elmar M. Merkle1, and Daniel T. Boll1
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 (Tissue4DTM, Siemens, Germany; DynaCADTM, Invivo, USA; AegisTM, Sentinelle Medical, Canada; CADvueTM; 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.

 
14:42 0241.   Comparison of Signal Intensity and Standard Techniques for Estimation of Pharmacokinetic Parameters in DCE-T1 Studies of Glioblastoma: Using Model Selection
Hassan Bagher-Ebadian1,2, Siamak P Nejad-Davarani1,3, Rajan Jain4, Douglas Noll3, Quan Jiang1, Ali Syed Arbab4, Tom Mikkelsen5, and James R Ewing1,2
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.

 
14:54 0242.   Uncertainty Maps in Dynamic Contrast-Enhanced MRI
Anders Garpebring1, Patrik Brynolfsson1, Jun Yu2, Ronnie Wirestam3, Adam Johansson1, Thomas Asklund4, and Mikael Karlsson1
1Dept. of Radiation Sciences, Umeċ University, Umeċ, Sweden, 2Centre of Biostatistics, Swedish University of Agricultural Sciences, Umeċ, Sweden,3Dept. of Medical Radiation Physics, Lund University, Lund, 4Division of Oncology, Dept. of Radiation Sciences, Umeċ University, Umeċ, 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.

 
15:06 0243.   The Comparison of Arterial Spin Labeling Perfusion MRI and DCE-MRI in Patients with Prostate Cancer
Wenchao Cai1, Feiyu Li1, Jing Wang2, Jue Zhang2,3, Xiaoying Wang1,2, and Xuexiang Jiang1
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, SpearmanĦŻs 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.

 
15:18 0244.   
Predictive value of MRI - perfusion parameters in patients with liver metastases
Wieland H Sommer1, Marco Armbruster1, Steven Sourbron1, Maximilian F Reiser1, and Christoph Zech1
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.