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

Yang Li, Peiying Liu, Yue Li, Hongli Fan, Pan Su, Shin Lei Peng, Denise C. Park, Karen M. Rodrigue, Hangyi Jiang, Andreia V. Faria, Can Ceritoglu, Michael Miller, Susumu Mori, Hanzhang Lu

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article numbere4051
JournalNMR in biomedicine
Volume32
Issue number2
DOIs
StatePublished - Feb 1 2019

Keywords

  • ASL-MRICloud
  • arterial spin labeling
  • cerebral blood flow
  • cloud computing
  • data analysis

ASJC Scopus subject areas

  • Molecular Medicine
  • Radiology Nuclear Medicine and imaging
  • Spectroscopy

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