Thomas W Okell* ¹, Wouter Teeuwisse* ^2,3, Michael A Chappell^1,4, and Matthias J.P. van Osch^2,3
1FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, United Kingdom, ²dept. of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, Netherlands, ³Leiden Institute for Brain and Cognition, Leiden, Netherlands, ⁴IBME, Department of Engineering Sciences, University of Oxford, Oxford, United Kingdom

Combined with cerebral blood flow (CBF) and bolus arrival time maps, flow territory mapping delivers a profound insight into the patient’s hemodynamics. In this study, time encoded pCASL is extended with vessel encoding gradients to acquire CBF, bolus arrival time and flow territory maps with a single scan. Results are compared to those of dedicated CBF and flow territory pCASL scans, demonstrating that the post labeling delay in standard pCASL, which is normally idle time, can be utilized to generate both vascular territory and bolus arrival time maps without adversely affecting CBF quantification.

Paula Croal¹, Emma Hall¹, Penny Gowland¹, and Susan Francis^1
1Sir Peter Mansfield Imaging Centre, Department of Physics & Astronomy, The University of Nottingham, Nottingham, Nottinghamshire, United Kingdom

Simultaneous CBF/BOLD acquisition is important for calibration of the BOLD signal and to investigate cerebrovascular reactivity. However, such sequences commonly rely on single phase ASL, which assumes a constant transit time and so can be problematic under high flow environments where transit time changes may occur (e.g. hypercapnia). We present a multiphase sequence for simultaneous CBF/BOLD acquisition termed Lock-Locker Double Acquisition Background Suppressed (LL-DABS) and compare this to single-phase CBF/BOLD acquisition. We demonstrate that LL-DABS significantly increases CBF measured under hypercapnia (P = 0.04), while BOLD sensitivity is maintained, and show this has significant implications for CMRO2 measurements.

Jia Guo¹, Richard B. Buxton¹, and Eric C. Wong^1,2
1Radiology, UC San Diego, La Jolla, California, United States, ²Psychiatry, UC San Diego, La Jolla, California, United States

The Turbo-QUASAR strategy proposed by Petersen and colleagues to improve the temporal signal-to-noise (tSNR) of arterial spin labeling (ASL) experiments works optimally when the temporal width of the tagged boluses matches the inter-pulse spacing. However, this cannot be accomplished using a conventional labeling slab because the feeding arteries will generally have different velocities and geometries. In order to remedy this, we propose a novel labeling strategy by creating a wedge-shaped (WS) inversion slab using additional in-plane gradients with minimal reduction in its adiabaticity. The WS inversion pulse may potentially be used to control and match the bolus temporal width in different feeding arteries, maximizing the tSNR in fast Pulsed ASL measurements.

Yi Wang¹, Steen Moeller², Xiufeng Li², An T Vu², Kate Krasileva¹, Kamil Ugurbil², Essa Yacoub², and Danny JJ Wang^1
1Neurology, UCLA, Los Angeles, CA, United States, ²Center of Magnetic Resonance Research, University of Minnesota, MN, United States

Multiband imaging has recently been attempted for arterial spin labeled perfusion MRI using EPI readout. It was found that MB-EPI can reduce T1 relaxation of the label, improve image coverage and resolution with little penalty in SNR. However, EPI still suffers from geometric distortion and signal dropout from field inhomogeneity effects especially at high fields. Here we present a novel scheme for achieving high fidelity distortion-free quantitative perfusion imaging by combining pCASL with MB-Turbo-FLASH readout at both 3 and 7T. We demonstrated the feasibility for whole brain distortion-free quantitative mapping of cerebral blood flow at high and ultrahigh magnetic fields.

Markus Boland¹, Rüdiger Stirnberg¹, Daniel Brenner¹, and Tony Stöcker^1,2
1German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany, ²Department of Physics and Astronomy, University of Bonn, Germany

A single-shot 3D-EPI PCASL sequence with background suppression and variable flip angle excitations was implemented and compared to PCASL with 3D-GRASE readout. With 3D-EPI we observed reduced blurring in slice direction and similar SNR compared to single-shot 3D-GRASE. Therefore the method might be a good candidate for functional ASL applications. For static CBF quantification at 3 mm isometric resolution the use of variable flip angles showed significant increase of SNR and CNR for the 3D-EPI, however, a segmented 3D-GRASE acquisition still provides about 15% higher SNR and CNR in the same acquisition time.

Marta Vidorreta¹, Ze Wang^2,3, Yulin V. Chang^1,4, María A. Fernández-Seara⁵, and John A. Detre^1
1Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States, ²Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province, China, ³Departments of Radiology and Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, United States, ⁴Department of Radiology, University of Pennsylvania, Pennsylvania, United States, ⁵Functional Neuroimaging Laboratory, CIMA, University of Navarra, Navarra, Spain

Recent technical developments have increased the SNR of ASL perfusion data, enabling whole-brain, high-resolution ASL imaging by combining pseudo-continuous labeling, background suppression and 3D segmented readouts. However, segmented acquisitions are sub-optimal for studying dynamic perfusion changes. This work proposes the use of a twofold accelerated 3D RARE Stack-Of-Spirals readout to enable single-shot, high-SNR, whole-brain ASL imaging with a nominal voxel resolution of 3.75mm isotropic. Results in 6 volunteers during the performance of a motor-photic task show an increase in GM-WM contrast with no associated SNR penalty and no loss in activation sensitivity, likely due to the increased perfusion signal level and decreased through-plane blurring achieved by the shortening of readout time.

Michael Helle¹, Peter Koken¹, and Julien Sénégas^1
1Philips Research, Hamburg, Germany

Arterial Spin Labeling (ASL) relies on the subtraction of several pairs of label and control images in order to cancel out signal from static tissue and to generate perfusion-weighted images. This makes ASL sensitive to motion which can result in image blurring and subtraction artifacts. In this study, subject motion is addressed by performing tracker scans within the labeling delay of a conventional pseudo-continuous ASL sequence and by adapting the orientation of the image volume if necessary.

Benjamin Knowles¹, Federico von Samson-Himmelstjerna^2,3, Matthias Guenther^2,4, and Maxim Zaitsev^1
1Medical Physics, University Medical Centre, Freiburg, Germany, ²Fraunhofer Mevis, Bremen, Germany, ³Charité Medical University, Center for Stroke Research, Berlin, Germany, ⁴University of Bremen, Germany

Arterial spin labelling (ASL) is a non-invasive method to measure blood perfusion. One limitation to ASL is that motion is highly corruptive, and leads to errors in perfusion-weighted images. This is especially problematic for 3D. In this study, the effectiveness of prospective motion correction (PMC) with an optical camera for artefact reduction in a pseudocontinuous ASL sequence with a 3D GRASE readout is investigated. Data are acquired using single-shot and segmented techniques. Segmented readouts are found to be strongly improved with PMC, even for compliant subjects. For single-shot, an intra-readout correction may still be required.

Eleanor S K Berry¹, Peter Jezzard¹, and Thomas W Okell^1
1FMRIB centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

Vessel-encoded pseudo-continuous arterial spin labeling (VEPCASL) can trace the flow patterns of individual feeding arteries in the brain. Unipolar VEPCASL produces a sinusoidal-like variation in inversion efficiency across the plane where blood is labeled. In the presence of a B0-induced frequency offset the inversion efficiency remains constant but its spatial position is shifted. If unaccounted for this can lead to reduced SNR and errors in the separation of signals from different arteries. Here we present a method that incorporates a correction for off-resonance at the vessel locations into a method for optimizing the encoding schemes for multiple vessels.

Pablo García-Polo^1,2, Adrian Martín^3,4, Virginia Mato⁵, Alicia Quirós⁶, Fernando Zelaya⁷, and Juan Antonio Hernandez-Tamames^5
1A. A. Martinos Center for Biomedical Imaging, Mass. General Hospital, M+Visión Advanced Fellowship, Charlestown, Massachusetts, United States, ²Centre for Biomedical Technology - Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid, Spain, ³Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States, ⁴3Applied Mathematics, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain, ⁵Department of Electrical Technology, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain, ⁶Cardiology, Hospital Clínico San Carlos, Madrid, Spain,⁷Department of Neuroimaging, King's College London, London, United Kingdom

Arterial Spin Labeling (ASL) is increasingly used in clinical studies of cerebral perfusion and has shown its validity in measuring perfusion changes in several neurodegenerative diseases. The main disadvantage of this technique is the limited spatial resolution needed to have a good SNR and the Partial volume effect (PVE) consequence of the large voxels employed. To correct this PVE effect and extract clean perfusion maps of only one single tissue (GM, WM or CSF), we propose an improvement of Asllani’s 2D linear regression method, with a 3D weighted least squares algorithm, including weighting matrices for distance and CBF measurement reliability.

Li Zhao¹, Samuel W Fielden², Xue Feng², Max Wintermark³, John P Mugler III⁴, Josef Pfeuffer⁵, and Craig H Meyer^2,4
1Radiology, Beth Israel Deaconess Medical Center & Harvard Medical School, Boston, MA, United States, ²Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, ³Radiology, Stanford University, Stanford, CA, United States, ⁴Radiology, University of Virginia, Charlottesville, VA, United States, ⁵Application Development, Siemens Healthcare, Erlangen, Germany

Dynamic arterial spin labeling (ASL) permits the tracking of a tagged blood bolus and reveals rich dynamic perfusion information. However, the inherent low SNR makes the acquisition of dynamic ASL data sets time-consuming and the resulting parameter maps unreliable. Using single-shot 3D stack-of-spirals acquisition and model-based image reconstruction, we demonstrate fast and robust dynamic ASL acquired in 20 seconds per perfusion phase, with high quality perfusion images and accurate parameter quantification.

Federico C A von Samson-Himmelstjerna^1,2, Michael A Chappell³, Jan Sobesky², and Matthias Günther^1
1Fraunhofer MEVIS, Bremen, Bremen, Germany, ²Center for Stroke Research (CSB), Charité University Medicine Berlin, Berlin, Berlin, Germany, ³Institute of Biomedical Engineering & FMRIB Centre, University of Oxford, Oxforshire, United Kingdom

A new signal model for time-encoded ASL-data in combination with Bayesian inference is proposed. It allows gaining kinetic perfusion information like cerebral blood flow and arterial transit time without subtraction and/or addition of images, even from incomplete or corrupted datasets. The model was tested in vivo using a 7x8 Walsh-Hadamard matrix for encoding the bolus. The resultant maps were then compared to reference maps from a classical multi-TI measurement. A very good agreement, even for data from an incomplete dataset was found. This makes the approach especially suited for clinical setups where data corruption e.g. by motion is common.

Pan Su¹, Deng Mao¹, Peiying Liu¹, Yang Li¹, Babu G. Welch², and Hanzhang Lu^1
1Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, United States, ²Department of Neurological Surgery, The University of Texas Southwestern Medical Center, Dallas, Texas, United States

Conventional Arterial Spin Labeling (ASL) sequence is limited to the scheme of control/label pairing pulse and long post-labeling delay, which is an inefficient method to measure cerebral perfusion. Based on the ‘all in one’ scan concept of the Magnetic Resonance Fingerprinting (MRF), we developed an ASL sequence that does not use post-labeling delay or control/label pairing to jointly measure cerebral blood flow (CBF), arterial transit time and T1. Preliminary scan result in healthy volunteers and in vascular disease patient showed promises of this novel technique.

Xiang He¹, Thang Le², Hoi-Chung Leung², Parsey Ramin³, and Mark Schweitzer^1
1Department of Radiology, Stony Brook University, Stony Brook, New York, United States, ²Department of Psychology, Stony Brook University, New York, United States, ³Department of Psychiatry, Stony Brook University, New York, United States

The diffusion sensitivity of ASL perfusion quantification with 3D-GRASE readout is investigated on human volunteer subjects. The results demonstrated a robust under-estimation on gray matter perfusion and significant over-estimation on white matter perfusion, especially in sub-cortical white matter. The diffusion sensitivity of intravascular ASL water signal is proposed as the root cause of the observed artifacts. This study suggests that high segmentation factor acquisition scheme, i.e. 6 or 8 shot (3PR× 2PE or 4PAR× 2PE), should be applied in GRASE or RARE readout to reduce the diffusion artifacts.

Megan Johnston¹ and Youngkyoo Jung^1,2
1Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States, ²Radiology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States

Multi-TI ASL with Variable bolus and TR ASL uses variable post-labeling delays to enable simultaneous arterial transit time and cerebral blood flow estimation. Time efficiency is improved by shortening TR for shorter TI times. Shortened labeling bolus durations allow for shortened TI times which enables for T1 and M0 estimation from the same raw data, fitting to the saturation recovery equation. Resulting blood flow and transit time maps fit the perfusion model better in the gray matter than Hadamard Encoded ASL and Look-Locker ASL with a larger percentage of voxels having a significant fit to the kinetic model.