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Related Experiment Video

Updated: Sep 6, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

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

Steve C N Hui^1,2, Muhammad G Saleh³, Helge J Zöllner^1,2

¹Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Magnetic Resonance in Medicine

|July 1, 2022

Summary

This summary is machine-generated.

A new cloud tool, MRSCloud, enables fast, online simulation of magnetic resonance spectroscopy (MRS) basis sets for GE, Philips, and Siemens scanners. This accelerates research by providing accurate, vendor-specific simulations efficiently.

Keywords:

basis set coherence pathway filtering density matrix magnetic resonance spectroscopy one dimensional projection simulation

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Last Updated: Sep 6, 2025

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Published on: December 13, 2016

Area of Science:

Medical Imaging and Spectroscopy
Computational Biology
Software Development

Background:

Magnetic Resonance Spectroscopy (MRS) is crucial for in vivo metabolite quantification.
Accurate basis sets are essential for reliable MRS data analysis.
Current methods for generating vendor-specific basis sets can be time-consuming and complex.

Purpose of the Study:

To introduce MRSCloud, a novel cloud-based platform for simulating magnetic resonance spectroscopy (MRS) basis sets.
To provide a convenient and time-efficient online tool for generating vendor-specific and sequence-specific basis sets.
To support simulations for major MRI vendors (GE, Philips, Siemens) at 3 Tesla, including PRESS and semi-LASER sequences.

Main Methods:

MRSCloud was developed using the FID-A software package with added computational acceleration extensions.
RF waveforms were generated based on vendor-specific pulse shapes and timings.
Simulations were validated against existing software (FID-A, MARSS) and phantom data (LCModel), with comparisons across different spatial resolutions.

Main Results:

MRSCloud significantly reduces simulation time, with a full PRESS basis set taking approximately 11 minutes.
High intraclass correlation coefficients (ICCs) were observed: ≥0.98 vs. FID-A, ≥0.96 vs. MARSS.
ICCs for simulated vs. acquired basis sets were high (e.g., N-acetylaspartate at 0.96), indicating accuracy.

Conclusions:

MRSCloud offers substantial runtime reductions for MRS basis set simulations.
The high ICC values confirm the accuracy and reliability of the implemented acceleration features.
This tool enhances the efficiency and accessibility of MRS data analysis for researchers across different platforms.