MRSCloud: A cloud-based MRS tool for basis set simulation

Steve C N Hui; Muhammad G Saleh; Helge J Zöllner; Georg Oeltzschner; Hongli Fan; Yue Li; Yulu Song; Hangyi Jiang; Jamie Near; Hanzhang Lu; Susumu Mori; Richard A E Edden

doi:10.1002/mrm.29370

MRSCloud: A cloud-based MRS tool for basis set simulation

Magn Reson Med. 2022 Nov;88(5):1994-2004. doi: 10.1002/mrm.29370. Epub 2022 Jul 1.

Authors

Steve C N Hui^{1

2}, Muhammad G Saleh³, Helge J Zöllner^{1

2}, Georg Oeltzschner^{1

2}, Hongli Fan^{1

4}, Yue Li^{1

5}, Yulu Song^{1

2}, Hangyi Jiang^{1

2}, Jamie Near⁶, Hanzhang Lu^{1

2}, Susumu Mori^{1

2}, Richard A E Edden^{1

2}

Affiliations

¹ Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
² F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA.
³ Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
⁴ Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
⁵ AnatomyWorks, LLC, Ellicott City, Maryland, USA.
⁶ Sunnybrook Research Institute and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.

Abstract

Purpose: The purpose of this study is to present a cloud-based spectral simulation tool "MRSCloud," which allows MRS users to simulate a vendor-specific and sequence-specific basis set online in a convenient and time-efficient manner. This tool can simulate basis sets for GE, Philips, and Siemens MR scanners, including conventional acquisitions and spectral editing schemes with PRESS and semi-LASER localization at 3 T.

Methods: The MRSCloud tool was built on the spectral simulation functionality in the FID-A software package. We added three extensions to accelerate computation (ie, one-dimensional projection method, coherence pathways filters, and precalculation of propagators). The RF waveforms were generated based on vendors' generic pulse shapes and timings. Simulations were compared within MRSCloud using different numbers of spatial resolution (21 × 21, 41 × 41, and 101 × 101). Simulated metabolite basis functions from MRSCloud were compared with those generated by the generic FID-A and MARSS, and a phantom-acquired basis set from LCModel. Intraclass correlation coefficients were calculated to measure the agreement between individual metabolite basis functions. Statistical analysis was performed using R in RStudio.

Results: Simulation time for a full PRESS basis set is approximately 11 min on the server. The interclass correlation coefficients ICCs were at least 0.98 between MRSCloud and FID-A and were at least 0.96 between MRSCloud and MARSS. The interclass correlation coefficients between simulated MRSCloud basis spectra and acquired LCModel basis spectra were lowest for glutamine at 0.68 and highest for N-acetylaspartate at 0.96.

Conclusions: Substantial reductions in runtime have been achieved. High ICC values indicated that the accelerating features are running correctly and produce comparable and accurate basis sets.

Keywords: basis set; coherence pathway filtering; density matrix; magnetic resonance spectroscopy; one dimensional projection; simulation.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Cloud Computing*
Computer Simulation
Glutamine*
Magnetic Resonance Spectroscopy / methods
Phantoms, Imaging

Substances

Glutamine

Abstract

Publication types

MeSH terms

Substances

Grants and funding