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Qijia Shen¹, Mark Chiew^1,2,3, Wenchuan Wu¹, and Thomas Okell^1
1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, ²Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, ³Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada

Keywords: Arterial spin labelling, Arterial spin labelling

4D combined angiographic, structural and perfusion radial imaging using arterial spin labelling (CASPRIA) provides a tool to simultaneously acquire information about brain structure and blood flow. However, the radial trajectory used limits the resolution and SNR, especially when the data is highly undersampled. In this work, an optimised 3D cone trajectory is presented with 3D golden means rotation to improve sampling at the k-space periphery whilst maintaining flexibility in spatiotemporal resolution. A locally low rank reconstruction was used to leverage spatiotemporal correlations and improve image quality. In vivo results showed considerable improvements in resolution and SNR over the radial approach.

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Yuriko Suzuki¹, Ioannis Koktzoglou^2,3, Peter Jezzard¹, and Thomas Okell^1
1Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, ²Department of Radiology, NorthShore University HealthSystem, Evanston, IL, United States, ³Pritzker School of Medicine, University of Chicago, Chicago, IL, United States

Keywords: Arterial spin labelling, Blood vessels, MRA

The non-invasive nature of Arterial Spin Labeling (ASL) technique makes ASL-based intracranial dynamic MR angiography (MRA) a potential alternative to diagnostic X-ray digital subtraction angiography. In elderly and diseased patients with slower blood flow, however, the vessel visualization of distal peripheral arteries tends to be poor, as the repeatedly applied RF excitation pulses decrease ASL blood signal rapidly. In this study, we address such a limitation by using multiple 2D slice acquisition to reduce the saturation of arterial blood signal. Additionally, to avoid losing vessel conspicuity and sharpness with 2D slice acquisition, we apply a  super-resolution convolutional neural network method.

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Yining He¹ and Lirong Yan^1,2
1Radiology, Northwestern University, Chicago, IL, United States, ²Neurology, University of Southern California, Los Angeles, CA, United States

Keywords: Arterial spin labelling, Perfusion

This study proposed a weakly supervised learning algorithm for vascular territorial mapping with rVE-ASL. The territory maps generated by the proposed deep learning (DL) method was compared with the territories from the conventional rVE-ASL method by visual inspection and F1 score. Our initial results showed that the DL method outperformed the conventional rVE-ASL method in the vascular territory mapping with improved detection of VA territory. The DL method also provided reliable vascular territorial maps with reduced numbers of encodings, significantly reducing rVE-ASL scan time.  These findings suggest that DL could be an effective approach for vascular territorial mapping of rVE-ASL.

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Fardad M Serry¹, Hsu-Lei Lee¹, Shihan Qiu^1,2, Yibin Xie¹, Fei Han^1,3, Hui Han¹, and Anthony G Christodoulou^1,2
1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ²Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, ³Siemens Medical Solutions, Los Angeles, CA, United States

Keywords: Arterial spin labelling, Arterial spin labelling, multitasking, Look-Locker, B1+, spin history, T1, blood, brain, IR-FLASH, inversion efficiency, white matter, gray matter

We hypothesized that the Look-Locker (LL) effect can label arterial spins without the need for subtraction between different inversion schemes. We developed a multiple-flip-angle, non-selective-inversion MR multitasking brain scan to produce co-registered T1, B1+, and perfusion-weighted maps. Flow-sensitive LL fitting homogenized B1+ maps and produced flow maps combining features of time-of-flight angiography images and PCASL perfusion-weighted images. GM/WM flow ratios were similar to PCASL and the literature range.

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Shota Ishida¹, Yasuhiro Fujiwara², Naoyuki Takei³, Yuki Matta⁴, Masayuki Kanamoto⁴, Hirohiko Kimura^5,6, and Tetsuya Tsujikawa^7
1Department of Radiological Technology, Faculty of medical sciences, Kyoto College of Medical Science, Nantan, Japan, ²Department of Medical Image Sciences, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan, ³GE Healthcare, Hino, Japan, ⁴Radiological center, University of Fukui Hospital, Eiheiji, Japan, ⁵Faculty of Medical Sciences, University of Fukui, Eiheiji, Japan, ⁶Radiology section, National Health Insurance Echizen-cho Ota Hospital, Unyu, Japan, ⁷Department of Radiology, Faculty of Medical Sciences, University of Fukui, Eiheiji, Japan

Keywords: Arterial spin labelling, Arterial spin labelling

A simulation-based supervised neural network was developed for simple and robust parameter estimation from multi-delay DANTE-prepared arterial spin labeling (ASL). The network was trained using 15 million simulation data points. Accuracy and precision were compared between the proposed and conventional methods. The neural-network-based estimation presented higher accuracy and precision than the conventional method that used table lookup. A higher noise immunity was also observed with the proposed method. A simulation-based supervised neural network simplifies the estimation process of multiparametric ASL. The estimation performance of cerebral blood flow and arterial cerebral blood volume was particularly improved by the proposed method.

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David Joseph Frey¹, Jeffrey A. Fessler², Douglas C. Noll¹, and Luis Hernandez-Garcia^1
1Radiology, University of Michigan, Ann Arbor, MI, United States, ²Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, United States

Keywords: Arterial spin labelling, New Trajectories & Spatial Encoding Methods

We investigate the performance of a new and efficient k-space sampling scheme that presents several advantages for velocity selective ASL imaging by rotating 2D spirals about the kx and ky axis. This paper compares the new readout to a traditional Stack-of-spirals readout by evaluating SNR for perfusion weighted images and the accuracy of z-scores for ASL FMRI experiments.

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Colette Clare Milbourn¹ and Nicholas Paul Blockley^1
1School of Life Sciences, University of Nottingham, Nottingham, United Kingdom

Keywords: Arterial spin labelling, Arterial spin labelling

New clinical tools are needed for the diagnosis and prognosis of cerebrovascular diseases. Cerebrovascular Reactivity (CVR) is a potential marker for brain health and can be induced using stressors to the brain like a hypercapnia challenge and quantitatively mapped using pseudocontinuous Arterial Spin Labelling (pCASL). However, measurements of CVR using pCASL have been shown to vary depending on the parameters of the unbalanced pCASL preparation scheme used. In this study the effect of a diminished B1 at the labelling plane and changes in B0 during hyperventilation were investigated as the origin of this discrepancy.

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Ingmar S. Sorgenfrei¹, Koen Baas², Stefan Spann¹, Martin Uecker¹, and Rudolf Stollberger^1
1Institute of Biomedical Imaging, TU Graz, Graz, Austria, ²Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands

Keywords: Arterial spin labelling, Brain

Time-encoded Arterial Spin Labeling (teASL) enables time-efficient acquisition of multiple averages of multiple post-labeling-delay (PLD) perfusion-weighted images (PWIs). We developed a dedicated teASL reconstruction that employs Infimal Convolution of Total Generalized Variation (ICTGV) regularization directly on the PWIs. Using simulated and healthy volunteer data, the ICTGV reconstruction produced inherently denoised images and improved cerebral blood flow and arterial transit time maps compared to a SENSE reconstruction. Also, for an 8-fold accelerated in-vivo dataset, the ICTGV reconstruction still produced reasonable PWIs, which the SENSE reconstruction could not. Therefore, ICTGV reconstruction is promising for teASL and allows high acceleration with inherent denoising.

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Jia Guo^1
1Bioengineering, University of California Riverside, Riverside, CA, United States

Keywords: Arterial spin labelling, Brain

Background suppression (BS) was optimized for dual-module velocity-selective arterials spin labeling (dm-VSASL) using VS inversion (dm-VSI). Compared with the Siemens product pulsed ASL (PASL) and pseudo-continuous ASL (PCASL) labeling, dm-VSI with optimized BS produced significantly higher temporal SNR; and a better suppression of the temporal noise from background tissues was observed with dm-VSI labeling by analyzing the temporal noise level with respect to the BS level. Further investigation is needed to verify and understand these findings to take full advantage of the improved SNR performance of dm-VSASL.

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Xingfeng Shao¹, Zixuan Liu¹, Qinyang Shou¹, Kay Jann¹, and Danny JJ Wang^1
1Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States

Keywords: Arterial spin labelling, Perfusion, test and retest reliability, multi-delay ASL

The goal of this study is to evaluate the quantification accuracy and measurement reliability of single- and multi-PLD pCASL via both simulation and in-vivo test and retest data.  CBF calculated by single-delay ASL achieved highest test and retest reliability as compared to 5-PLD ASL. However, CBF values may be under-estimated due to prolonged ATT. 5-PLD ASL can be used to quantify ATT and CBF simultaneously with slightly reduced test and retest reliability. Model-fitting approach is more preferrable than the weighted-delay approach in terms of both quantification error and reliability.

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Qinyang Shou¹, Xingfeng Shao¹, Kimberly Felix², Rudolf Stollberger³, Megan M Herting², and Danny JJ Wang^1
1Laboratory of Functional MRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States, ²Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, ³Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria

Keywords: Arterial spin labelling, Brain

We developed an accelerated multi-delay 3D pCASL scheme with high-resolution (iso-2mm), CAIPI acceleration and TGV reconstruction to achieve a ~9-minute protocol with 5 delays with 8 averages per delay. We tested the feasibility of this protocol on 19 pediatric subjects and found the proposed imaging protocol with TGV constrained reconstruction can improve the test-retest reliability of high-resolution 3D pCASL perfusion imaging in typically developing children compared to a standard segmented acquisition.

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Qijia Shen¹, Mark Chiew^2,3,4, Wenchuan Wu⁴, and Thomas Okell^4
1University of Oxford, Oxford, United Kingdom, ²Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, ³Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, ⁴Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

Keywords: Arterial spin labelling, Arterial spin labelling

4D combined angiography and perfusion using radial imaging and arterial spin labelling (CAPRIA) allows dynamic angiograms to be reconstructed. However, the current approach uses a relatively long temporal window to ensure sufficient k-space coverage within each frame, resulting in abrupt changes between adjacent frames, and additional artefacts. In this work, we use a kinetic model of the angiographic signal to constrain the reconstruction of highly undersampled data. A subspace reconstruction was developed for compressed representation of signal during reconstruction for computational efficiency. In-vivo results showed smoother variation of the angiographic signal in the temporal dimension compared to the original approach.

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Thomas Liu^1,2,3,4, Eric Wong^1,2,3, Divya Bolar^1,2, Conan Chen^1,2,5, and Ryan Barnes^1,5
1Center for fMRI, University of California San Diego, La Jolla, CA, United States, ²Department of Radiology, UCSD, La Jolla, CA, United States, ³Department of Psychiatry, UCSD, La Jolla, CA, United States, ⁴Department of Bioengineering, UCSD, La Jolla, CA, United States, ⁵Department of Electrical and Computer Engineering, UCSD, La Jolla, CA, United States

Keywords: Arterial spin labelling, Arterial spin labelling

A mathematical model is presented that describes the arterial delivery function and cerebral blood volume components in velocity-selective arterial spin labeling. The model incorporates physiologically valid approximations of changes in  acceleration and velocity along the vascular system.  Applications of the model are shown using a set of example labeling and saturation profiles.  

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Conan Chen^1,2, Ryan A. Barnes^1,2, Eric C. Wong^1,3, Thomas T. Liu^1,3,4, and Divya S. Bolar^1
1Center for fMRI, Department of Radiology, University of California San Diego, La Jolla, CA, United States, ²Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, United States, ³Department of Psychiatry, University of California San Diego, La Jolla, CA, United States, ⁴Department of Bioengineering, University of California San Diego, La Jolla, CA, United States

Keywords: Arterial spin labelling, Arterial spin labelling

Pulsatile blood flow has been linked to structural damage to the cerebral microvasculature. Previous methods have successfully measured pulsatility in the arteries, but few methods exist to target the microvasculature where the damage is occurring. In this current work, we present a simple theoretical model for CBF pulsatility, apply the model to experimental data acquired in human subjects, and report in vivo microvascular pulsatility using VSASL.

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Chenyang Zhao¹, Xingfeng Shao¹, Qinyang Shou¹, Samantha Ma², Sayim Gokyar¹, Christina Graf³, Rudolf Stollberger³, and Danny JJ Wang^1,4
1Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, ²Siemens Medical Solutions USA, Los Angeles, CA, United States, ³Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria, ⁴Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States

Keywords: Arterial spin labelling, Arterial spin labelling, Perfusion

The potential of 7T has not been fulfilled for pseudo-Continuous Arterial Spin Labeling (pCASL) because of challenges in labeling, background suppression (BS), and readouts. This study proposed a new labeling parameter, a superior BS pulse, and an accelerated and segmented 3D Turbo-FLASH (TFL) readouts. Despite the field inhomogeneity at 7T, the new labeling parameter achieves high labeling efficiency without signal interference, and OPTIM as BS pulse robustly achieves high inversion efficiency.  3D TFL pCASL provides whole brain coverage, abundant anatomical information without distortion, high resolution, and sufficient SNR in 11 mins.

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Xinran Chen¹, Liangjie Lin², Zhiliang Wei³, Lin Chen¹, and Zhong Chen^1
1Department of electronic science, Xiamen University, Xiamen, China, ²Clinical & Technical Support, Philips Healthcare, Beijing, China, ³Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States

Keywords: Arterial spin labelling, Data Processing, Denoising

Arterial-spin-labeling (ASL) MRI has been widely used in neurological studies for investigating brain activity via focusing on regional perfusion differences. However, sensitivity is a general issue in ASL MRI to prevent the high-resolution comparisons of perfusion heterogeneity, which are associated with pathological process, or lead to prolonged scan time, which inhibits the temporal resolution in monitoring acute-stage perfusion changes (e.g., perfusion recovery after spontaneous resuscitation in cardiac arrest). Therefore, in this study, a post-processing method exploring spatiotemporal redundant information of ASL data is proposed to enhance the sensitivity without extending scan durations. 

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Lena Sommer¹, Daniel Christopher Hoinkiss¹, Jörn Huber¹, Simon Konstandin^1,2, and Matthias Günther^1,2,3
1Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany, ²mediri GmbH, Heidelberg, Germany, ³University of Bremen, Bremen, Germany

Keywords: Arterial spin labelling, Kidney

A spatial mapping of the renal filtration function of the blood might be helpful in identifying parts of the kidney that only work with reduced function and are therefore impaired the most. This work shows an approach to a non-invasive method to map the filtration rate of the kidney.  

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Ebony Rosalind Gunwhy¹, Sirisha Tadimalla², John C. Waterton^3,4, Paul D. Hockings^5,6, Gunnar Schütz⁷, Claudia Green⁷, J. Gerry C. Kenna⁴, and Steven Sourbron^1
1Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, United Kingdom, ²Institute of Medical Physics, The University of Sydney, Sydney, Australia, ³Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester, United Kingdom, ⁴Bioxydyn Ltd, Manchester Science Park, Manchester, United Kingdom, ⁵BioVentureHub, Antaros Medical, Mölndal, Sweden, ⁶MedTech West, Chalmers University of Technology, Gothenburg, Sweden, ⁷MR & CT Contrast Media Research, Bayer AG, Berlin, Germany

Keywords: Validation, Animals, Arterial input functions, small animals, spleen, liver

Accurate biomarker quantification is hindered in small animal MRI due to difficulties in reliably deriving arterial input functions (AIFs). This study provides a robust alternative to commonly used approaches by deriving AIFs from a simple, whole-body circulation model. This method is compared with individual and population spleen-derived AIFs by evaluating performance in gadoxetate DCE-MRI of the rat liver. Results demonstrated that the whole-body circulation model-derived AIF yields greater repeatability, reproducibility, and goodness-of-fit to observed data, indicating that it provides more accurate biomarker quantification than the individual or population spleen-derived AIFs.

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Olivia Sobczyk¹, Ece Su Sayin², Julien Poublanc¹, Harrison Toby Levine², James Duffin², Joseph Arnold Fisher², and David John Mikulis^1
1University Health Network, Toronto, ON, Canada, ²Physiology, University of Toronto, Toronto, ON, Canada

Keywords: Susceptibility, Perfusion

The choroid plexus is composed of arteries and stroma with negligible metabolic activity allowing its vessels to remain arterialized throughout its structure.  We assessed the choroid plexus as a suitable alternate arterial input function rather than the middle cerebral artery in DSC imaging in individuals with both normal vasculature and pathology affecting the middle cerebral artery. 

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Muhammad Asaduddin¹, Eung Yeop Kim², and Sung-Hong Park^1
1Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea, Republic of, ²Department of Radiology, Samsung Medical Center, Sungkyunkwan University College of Medicine, Seoul, Korea, Republic of

Keywords: Contrast Agent, DSC & DCE Perfusion

The conventional deconvolution method in DSC perfusion MRI suffers from sensitivity to noise and threshold level. Regularization methods to mitigate the noise issue also suffers from other issues. In this study, we present a deep learning approach to perform deconvolution more robustly and accurately. Our result showed multi layers perceptron (MLP) performed deconvolution more accurately in synthetic data compared to the traditional regularization method. We also showed that MLP performed more robustly in patient data with varying levels of noise. This study provides a strong argument for using MLP as a stable and accurate deconvolution method for DSC perfusion calculation.