Joint Annual Meeting ISMRM-ESMRMB 2014 10-16 May 2014 Milan, Italy

SCIENTIFIC SESSION
Perfusion & Permeability: Contrast Agent Methods

 
Wednesday 14 May 2014
Red 1 & 2  10:00 - 12:00 Moderators: Michaeal S. Ingrisch, Ph.D., Ronnie Wirestram, Ph.D.

10:00 0522.   
Simplified model for Gd-EOB-DTPA DCE-MRI liver function analysis
Mikael F. Forsgren1,2, Jose L. Ulloa3, and Paul D. Hockings4,5
1Wolfram MathCore AB, Linköping, Sweden, and Center for Medical Image Science and Visualization(CMIV), Linköping University, Linköping, Sweden,2Dept. of Medical and Health Sciences, Linköping University, Dept. of Radiation Physics, UHL County Council of Östergötland, Linköping, Sweden,3Bioxydyn Ltd., Manchester, United Kingdom, 4Drug Safety and Metabolism, AstraZeneca AB, Mölndal, Sweden, 5MedTech West, Chalmers University of Technology, Gothenburg, Sweden

 
Dynamic contrast-enhanced MRI seems promising for non-invasive quantification of liver function. Recently a model based method for the quantification was published, and herein we tested if the number of parameters could be reduced by linearizing the efflux into the bile (MRP2), and still maintain sufficient separation between normal and reduced liver function. This model reduction was tested on rats treated with a chemokine receptor antagonist that reduces liver function. We found that the uptake of contrast was unaffected by the model reduction of the efflux, and that the reduced model was significantly able to separate between normal and reduced function.

 
10:12 0523.   
Reducing respiratory motion artifacts in fast 2D dynamic contrast enhanced MRI in liver using structural similarity
E.G.W. ter Voert1, L. Heijmen2, C.J.A. Punt3, J.H.W. de Wilt4, H.W.M. van Laarhoven2,3, and A. Heerschap1
1Radiology, Radboud University Medical Centre, Nijmegen, Gelderland, Netherlands, 2Medical Oncology, Radboud University Medical Centre, Nijmegen, Gelderland, Netherlands, 3Medical Oncology, Academic Medical Center, University of Amsterdam, Amsterdam, Noord-Holland, Netherlands, 4Surgery, Radboud University Medical Centre, Nijmegen, Gelderland, Netherlands

 
Reproducibility of dynamic contrast enhanced MRI (DCE-MRI) in tumors in the liver is hampered by respiratory and cardiac motion. The aim of this study was to implement and apply a structural similarity algorithm (SSIM) in the post-processing of high-temporal-resolution 2D DCE-MRI data to correct for movement artifacts. The implemented SSIM algorithm compares the images from the dynamic series with reference images and based on the returned index values it rejects motion corrupted time points. The application of SSIM was tested in 15 patients and it substantially improved the reproducibility of the DCE-MRI pharmacokinetic modeling (Tofts model) parameter Ktrans in the liver.

 
10:24 0524.   In vivo T2* effect on pharmacokinetic parameter estimation using reference tissue arterial input function at 7T
Jin Zhang1, Melanie Freed1, Kerryanne Winters1, and Sungheon Kim1
1Radiology, New York University, New York, New York, United States

 
The influence of T2* on lesion signal intensity and arterial input function at high field can induce systemic errors in pharmacokinetic parameter estimation. When the arterial input function is estimated from reference tissue, the T2* effect on parameter estimation may be relatively smaller than when it is directly measured. In this study, we investigate the influence of a Gd-based contrast agent on the T2* of tumor at 7T and its effect on kinetic model analysis. Our preliminary results show no significant difference between pharmacokinetic model parameters from T2*-corrected and non-corrected data when a reference tissue arterial input function is used.

 
10:36 0525.   
Measurement Sequence for Quantitative Phase-Based Arterial Input Function for Bolus Tracking Perfusion Imaging
Elias Kellner1, Irina Mader2, and Valerij G Kiselev1
1Medical Physics, University Medical Cener Freiburg, Freiburg, Germany, 2Section of Neuroradiology, Neurocenter, University Medical Center Freiburg, Freiburg, Germany

 
In this work, we examine the feasibility of measuring quantitative phase-based arterial input functions and venous output functions in an additional slice at the carotid arteries and examine the optimal location for the measurement.

 
10:48 0526.   
Measurement of a High-Temporal Resolution Arterial Input Function from MR Projections: Extension to Radial Acquisition to Compensate for Local Tissue Enhancement
Jen Moroz1, Piotr Kozlowski2,3, and Stefan A Reinsberg1
1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, 2Radiology, UBC, University of British Columbia, BC, Canada, 3UBC MRI Research Centre, University of British Columbia, BC, Canada

 
The arterial input function is an important input parameter for modelling DCE-MRI data. However, it is difficult to measure accurately in mice. A projection-based method can significantly improve the temporal resolution of the AIF, but may be biased due to local tissue enhancement. This simulation study extends the Cartesian projection-based method to a radial approach: Each projection serves as a single time-point measure of the AIF, but is also used to reconstruct a radial image to assess background tissue enhancement. The results show that an AIF, measured from single projections, can be corrected from a time-series of radial images to remove the bias caused from local tissue enhancement.

 
11:00 0527.   
Automated correction method allowing phase-based detection of contrast enhancement in DCE-MRI
Ellis Beld1, Frank F.J. Simonis1, Johannes G. Korporaal1, Uulke A. van der Heide2, and Cornelis A.T. van den Berg1
1Radiotherapy, UMC Utrecht, Utrecht, Netherlands, 2Radiotherapy, Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital (NKI-AVL), Amsterdam, Netherlands

 
Phase-sensitive MR procedures are affected by spatially and temporally varying B0 inhomogeneities. A higher order background phase correction, to compensate for these inhomogeneities, was used for phase-based measurement of the arterial input function (AIF) in dynamic contrast-enhanced (DCE) MRI. The background phase was calculated inwards from the subcutaneous fat layer, using a near-harmonic 2D reconstruction. Besides measurement of the AIF, the background corrected phase data enables detection of contrast induced phase modulation in tissues.

 
11:12 0528.   Phase-based contrast agent quantification using statistical modelling
Patrik Brynolfsson1 and Anders Garpebring1,2
1Radiation Sciences, Umeå University, Umeå, Sweden, 2CJ Gorter Center for high field MRI, Leiden University Medical Center, Leiden, Zuid-Holland, Netherlands

 
A novel method for contrast agent (CA) quantification is proposed. Phase changes linearly with CA concentration, but is hard to use due to the ill-posed inversion from phase-change to CA concentration. We regularize the inversion with magnitude data in a statistical approach and evaluate the result on simulated DCE-MRI exams. For tissues with high CA concentration the novel method performed better than using magnitude information only, for low CA concentrations the methods were equivalent. The next step is to test the method on in-vivo data where many challenges still remain, such as phase-drift.

 
11:24 0529.   Analysis of multiparametric microvascular MRI in tumor patients using a model-based cluster approach.
Julien Bouvier1, Nicolas Coquery1, Sylvie Grand2, Thomas Perret1, David Chechin3, Irene Tropres1, Alexandre Krainik1, and Emmanuel L Barbier1
1U836, INSERM, Grenoble, France, France, 2Department of neuroradiology and MRI, CHU de Grenoble, France, France, 3Philips Healthcare, Suresnes, France, France

 
In clinical monitoring of brain tumors, Perfusion Weighted Imaging (PWI) contributes to tumor grading and to assess the response to treatment. Beyond tumor perfusion, tumor hypoxia determines the response of various therapeutic approaches including radiotherapy. All these parameters may be mapped with MRI. However, the integration of several MRI maps is difficult. This wealth of information is however difficult to interpret. Moreover, there are tight physiological links between these parameters. It should thus be possible to define clusters of pixels with similar physiological characteristics. In this study, multiparametric MRI data collected on tumor patient were analyzed with a model-based cluster approach.

 
11:36 0530.   Vascular Fingerprinting in Rat Brain Tumors
Benjamin Lemasson1,2, Nicolas Pannetier3,4, Régine Farion1,2, Emmanuel Barbier1,2, Norbert Schuff3,4, Michael Moseley5, Greg Zaharchuk5, and Thomas Christen5
1U836, Iserm, Grenoble, France, 2Grenoble Institut des Neurosciences, Université Joseph Fourier, Grenoble, France, 3Va medical center, Centre for neurodegenerative des eases, San Francisco, CA, United States, 4University of California San Francisco, Department of Radiology and Biomedical Imaging, San Francisco, CA, United States, 5Stanford University, Department of Radiology, Stanford, CA, United States

 
In this study, we tested the ‘vascular fingerprinting’ approach in 8 rats bearing brain tumors. This recent method compares in vivo MR signal time evolutions to a dictionary of curves obtained with numerical simulations and creates maps of microvascular characteristics. We obtained good correlations with more conventional MR methods: steady-state susceptibility contrast imaging for blood volume mapping, Vessel Size Imaging and multiparametric quantitative BOLD imaging for blood oxygen saturation measurements. In two rats, high spatial resolution maps were obtained and compared to pimonidazole staining, a histological marker of tissue hypoxia.

 
11:48 0531.   Validation of a multiple-echo DSC-MRI approach with T1 and T2* leakage correction for brain tumor perfusion imaging
Ashley M Stokes1,2, Natenael Semmineh1,3, and C. Chad Quarles1,2
1Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States, 2Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, United States, 3Physics and Astronomy, Vanderbilt University, Nashville, TN, United States

 
Contrast agent (CA) leakage in tumors can lead to incorrect hemodynamic measures in DSC-MRI; therefore, DSC Capital Greek DeltaR2* signals must be leakage corrected to provide accurate CBF and CBV. We propose removing T2* leakage effects in T1-insensitive dual-echo Capital Greek DeltaR2* by estimating the extravascular CA relaxivity using the transverse relaxivity at tracer equilibrium (TRATE). In rat glioma, we compared the uncorrected CBV and CBF to corrected values using the Weisskoff and TRATE corrections; these were further compared to MION reference values. The Weisskoff and TRATE corrections led to CBVs that were closer to the MION values, but both underestimated CBF.