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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
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Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
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calf - Software for CEST Analysis with Lorentzian Fitting.

Hans-Jörg Wittsack1, Karl Ludger Radke2, Julia Stabinska3,4

  • 1Medical Faculty, Department of Diagnostic and Interventional Radiology, University Dusseldorf, D-40225, Dusseldorf, Germany. Hans-Joerg.Wittsack@med.uni-duesseldorf.de.

Journal of Medical Systems
|March 24, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a robust method for analyzing chemical exchange saturation transfer (CEST) MRI data, improving metabolite quantification. A user-friendly software tool is also provided to enhance accessibility for researchers.

Keywords:
CEST analysisLorentzian fittingMRISoftwarez-spectra

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Area of Science:

  • Magnetic Resonance Imaging
  • Biomedical Engineering
  • Metabolomics

Background:

  • Chemical Exchange Saturation Transfer (CEST) MRI is crucial for metabolite analysis in tissues.
  • CEST MRI data analysis is complex due to overlapping spectral components and various disturbances.
  • Reliable quantification of CEST z-spectra is essential for accurate metabolite detection.

Purpose of the Study:

  • To develop an advanced method for robust quantification of CEST MRI data.
  • To incorporate prior knowledge into the fitting process for improved accuracy.
  • To create and distribute user-friendly software for CEST data analysis.

Main Methods:

  • Adaptive nonlinear least squares algorithm for z-spectra fitting.
  • Incorporation of prior knowledge into the quantitative analysis.
  • Development of a Microsoft Windows-based software tool for CEST data analysis.

Main Results:

  • The developed method provides robust quantification of CEST z-spectra.
  • The software facilitates successful analysis of CEST data, even for less experienced users.
  • The method and software aim to lower the barrier for CEST MRI adoption in research.

Conclusions:

  • The presented method offers a significant improvement in CEST MRI data analysis.
  • The freely available software enhances the accessibility and usability of CEST MRI techniques.
  • This work supports the broader dissemination and application of CEST MRI in biomedical research.