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Nuclear magnetic resonance (NMR) spectroscopy is a very valuable analytical technique for researchers. It has been used for more than 50 years as an analytical tool. F. Bloch and E. Purcell formulated NMR in 1946 and won the 1952 Nobel Prize in Physics  for their work. Biological macromolecules such as proteins, nucleic acids, lipids, and organic molecules including pharmaceutical compounds, can be studied using this versatile tool that exploits the magnetic properties of certain nuclei.
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CloudBrain-MRS: An intelligent cloud computing platform for in vivo magnetic resonance spectroscopy preprocessing,

Xiaodie Chen1, Jiayu Li1, Dicheng Chen1

  • 1Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China.

Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|December 1, 2023
PubMed
Summary

CloudBrain-MRS is a novel cloud platform offering advanced magnetic resonance spectroscopy (MRS) processing. It integrates artificial intelligence and classic methods for disease biomarker discovery and metabolite analysis.

Keywords:
Cloud computingData analysisMagnetic resonance spectroscopyPreprocessingQuantification

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Area of Science:

  • Neuroimaging
  • Biomedical Engineering
  • Computational Biology

Background:

  • Magnetic resonance spectroscopy (MRS) is crucial for disease diagnosis by analyzing metabolite signals.
  • Limited accessibility of user-friendly MRS processing software hinders clinical research.
  • Existing tools lack integrated advanced algorithms and cloud-based accessibility.

Purpose of the Study:

  • To develop CloudBrain-MRS, a cloud-based platform for accessible and advanced MRS data processing.
  • To integrate both traditional and artificial intelligence (AI) algorithms for enhanced analysis.
  • To facilitate biomarker discovery and metabolite quantification in clinical research.

Main Methods:

  • Developed a web-accessible, cloud-based platform (CloudBrain-MRS) requiring no user-side installation.
  • Integrated the LCModel with advanced AI algorithms for batch processing of MRS data.
  • Implemented automated statistical analysis, consistency verification, and 3D visualization tools.

Main Results:

  • CloudBrain-MRS supports processing of MRS data from various vendors.
  • The platform enables automated biomarker discovery and comparison of quantification methods.
  • Demonstrated platform utility with data from healthy subjects and mild cognitive impairment patients.

Conclusions:

  • CloudBrain-MRS is the first cloud platform for in vivo MRS featuring AI processing.
  • The platform enhances accessibility and analytical capabilities for MRS clinical research.
  • Free access is provided via MRSHub for at least two years.