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Traditional Posters: Diffusion & Perfusion - ismrm

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1767. Simultaneous Measurements of Arterial Transit Times and Water Exchange Rates<br />

by <strong>Diffusion</strong>-Weighted ASL<br />

Keith S. St. Lawrence 1,2 , Jodi Miller 1 , Jiongjiong Wang 3<br />

1 Imaging, Lawson Health Research Institute, London, ON, Canada; 2 Medical Biophysics, University of Western<br />

Ontario, London, ON, Canada; 3 Radiology, University of Pennsylvania, Philadelphia, PA, United States<br />

The arterial transit time (τa) and the exchange rate of water (kw) across the blood-brain barrier were determined using diffusionweighted<br />

arterial spin labelling (ASL) with multiple post-labelling delay times. τa was determined using bipolar gradients to suppress<br />

the arterial signal (i.e., the FEAST method) and kw was determined using bipolar gradients strong enough to suppress all vascular<br />

signals and a kinetic model to characterize water exchange across the BBB. Averaged over four volunteers, kw was 119 min-1 in grey<br />

matter and τa was 1.26 s. From repeat measurements, the intra-subject coefficient of variation of kw was 12%.<br />

1768. Flow-Weighted Arterial Transit Time Mapping of the Human Brain<br />

Toralf Mildner 1 , Stefan Hetzer 1 , Wolfgang Driesel 1 , Karsten Müller 1 , Harald E. Möller 1<br />

1 NMR unit, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Saxony, Germany<br />

Mapping of Arterial Transit times by Intravascular Signal SElection (MATISSE) was performed with and without a mild flowweighting<br />

(FW). The arterial transit times, δa , of the flow-weighted data were increased on average by about 700 ms and the signal<br />

amplitudes roughly were halved. Flow-through signals, i. e. signals of arterial vessels permeating the voxel, are removed almost<br />

completely, although the MATISSE signal still is expected to be of vascular origin. The fact that δa with mild FW was found to be<br />

easily larger than 2 s might be important for the quantification of CBF in standard dual-coil CASL experiments.<br />

1769. Arterial Transit Delay Measurement Using Pseudo-Continuous ASL with Variable<br />

TR and Interleaved Post-Labeling Delays<br />

Kun Lu 1 , Thomas T. Liu 1 , Youngkyoo Jung 1<br />

1 Center for Functional MRI, UCSD, La Jolla, CA, United States<br />

Conventional arterial transit delay measurements consist of a series of separate ASL experiments acquired at several different postlabeling<br />

delays. Such measurements are usually time-consuming and can be formidable overheads for ASL studies. The time<br />

requirement also makes the measurements highly sensitive to motion. This study presents a simple yet effective modification of the<br />

conventional method for measuring transit delay with shorter scan time and less motion sensitivity. Such a method could be beneficial<br />

to all ASL studies.<br />

1770. Eliminating the Partition Coefficient from ASL <strong>Perfusion</strong> Quantification with a<br />

Homogeneous Contrast Reference Image<br />

Weiying Dai 1 , Philip M. Robson 1 , Ajit Shankaranarayanan 2 , David C. Alsop 1<br />

1 Radiology, Beth Israel Deaconess Medical Center,Harvard Medical School, Boston, MA, United States;<br />

2 Global Applied Science Laboratory, GE Healthcare, Menlo Park, CA, United States<br />

Conventional ASL perfusion quantification requires division by a proton density reference image and assumes a uniform brain-blood<br />

partition coefficient. The brain-blood partition coefficient is not constant, however, and may especially differ in areas of pathology. In<br />

cortical regions where CSF, white matter and gray matter may all be mixed within a voxel, division by the proton density image can<br />

also add nonlinear systematic errors. Here we propose using an optimized inversion preparation to generate an image whose intensity<br />

is essentially independent of tissue type. This highly homogeneous image can replace the proton density image and makes the<br />

assumption of a brain-blood partition coefficient unnecessary. In-vivo results demonstrate that such homogeneous contrast is<br />

achievable and can be used to improve the pixel-by-pixel perfusion measurement.<br />

1771. Potential Tracking of Oxygen Consumption Using Arterial Spin Labeling<br />

Susceptibility Imaging<br />

Johannes Gregori 1,2 , Norbert Schuff 3,4 , Matthias Günther 1,5<br />

1 Institute for Medical Image Computing, Fraunhofer MEVIS, Bremen, Germany; 2 Neurology,<br />

Universitätsmedizin Mannheim, Heidelberg University, Mannheim, Germany; 3 Radiology & Biomedical<br />

Imaging, University of San Francisco, San Francisco, CA, United States; 4 Center for Imaging of<br />

Neurodegenerate Diseases (CIND), VA Medical Center, San Francisco, CA, United States; 5 mediri GmbH,<br />

Heidelberg, Germany<br />

We present ASL time series measurements with spin/gradient double echo spiral 3D-GRASE readout to quantify R2' of the ASL<br />

difference signal. R2' can give information about blood oxygenation and blood volume, while ASL time series are used to investigate<br />

perfusion dynamics. Using the combination of both techniques, we can measure the changes of R2' over different inflow times and<br />

discuss the physiological underlyings.<br />

1772. Improving the Stability of T2 Measurements in ASL Experiments<br />

Johanna Kramme 1,2 , Johannes Gregori 1,2 , Matthias Günther 2,3<br />

1 Division of Neurology, University Hospital Mannheim of the University of Heidelberg, Mannheim, Germany;<br />

2 Fraunhofer MEVIS-Institute for Medical Image Computing, Bremen, Germany; 3 Faculty for Physics and<br />

Electrical Engineering, University Bremen, Bremen, Germany<br />

To increase sensitivity and reduce physiological noise in ASL T2 measurements a single shot 3D-GRASE approach was developed.<br />

Compared to sequential acquisition of the different echo times significant reduction in scan time and physiological noise can be<br />

achieved. To improve T2 calculations the inflow time TI of each data set has to be corrected for each echo time. Based on the TE

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