ASL‐MRICloud: An online tool for the processing of ASL MRI data

NMR in Biomedicine - Tập 32 Số 2 - 2019
Yang Li1,2, Peiying Liu2, Yue Li3, Hongli Fan4,2, Pan Su1,2, Shin‐Lei Peng5, Denise C. Park6, Karen M. Rodrigue6, Hangyi Jiang7,2, Andréia V. Faria2, Can Ceritoglu8, Michael I. Miller8,4, Susumu Mori7,2, Hanzhang Lu4,7,2
1Graduate School of Biomedical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
2The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
3AnatomyWorks, LLC, Baltimore, MD, USA
4Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
5Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung City, Taiwan
6Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA
7F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
8Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA

Tóm tắt

Arterial spin labeling (ASL) MRI is increasingly used in research and clinical settings. The purpose of this work is to develop a cloud‐based tool for ASL data processing, referred to as ASL‐MRICloud, which may be useful to the MRI community. In contrast to existing ASL toolboxes, which are based on software installation on the user's local computer, ASL‐MRICloud uses a web browser for data upload and results download, and the computation is performed on the remote server. As such, this tool is independent of the user's operating system, software version, and CPU speed. The ASL‐MRICloud tool was implemented to be compatible with data acquired by scanners from all major MRI manufacturers, is capable of processing several common forms of ASL, including pseudo‐continuous ASL and pulsed ASL, and can process single‐delay and multi‐delay ASL data. The outputs of ASL‐MRICloud include absolute and relative values of cerebral blood flow, arterial transit time, voxel‐wise masks indicating regions with potential hyper‐perfusion and hypo‐perfusion, and an image quality index. The ASL tool is also integrated with a T1‐based brain segmentation and normalization tool in MRICloud to allow generation of parametric maps in standard brain space as well as region‐of‐interest values. The tool was tested on a large data set containing 309 ASL scans as well as on publicly available ASL data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study.

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