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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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The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...
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Updated: Dec 24, 2025

Rapid Scan Electron Paramagnetic Resonance Opens New Avenues for Imaging Physiologically Important Parameters In Vivo
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Generalized parameter estimation in multi-echo gradient-echo-based chemical species separation.

Maximilian N Diefenbach1, Chunlei Liu2, Dimitrios C Karampinos1

  • 1Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany.

Quantitative Imaging in Medicine and Surgery
|April 10, 2020
PubMed
Summary
This summary is machine-generated.

A new generalized method enhances chemical species separation in multi-echo gradient-echo MRI. This framework simplifies magnetic resonance imaging analysis for various signal models, improving accuracy and applicability.

Keywords:
Cramér-Rao lower boundParameter estimationfatty acid compositionnoise analysisvariable projection method (VARPRO)water-fat imaging

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Biomedical Engineering
  • Signal Processing

Background:

  • Multi-echo gradient-echo (GRE) sequences are crucial for separating chemical species in MRI.
  • Existing methods often rely on specific signal models, limiting their universal applicability.
  • Accurate parameter estimation is essential for reliable chemical species separation.

Purpose of the Study:

  • To develop a generalized formulation for chemical species separation applicable to a wide range of MR signal models.
  • To create a flexible framework for parameter estimation and experimental design in multi-echo GRE MRI.
  • To provide a universally applicable computational tool for advanced MRI analysis.

Main Methods:

  • Developed a generalized formulation using a matrix-based abstraction of signal model constraints.
  • Employed a generic parameter gradient within a parameter estimation algorithm and Fisher information matrix.
  • Validated the framework through numerical simulations and comparison with existing literature and in vivo data.

Main Results:

  • The proposed framework demonstrated universal applicability across various MR signal models.
  • Previous findings in magnetic field mapping and water-fat imaging were successfully replicated using the same framework with different input matrices.
  • The gradient-based parameter estimation approach proved effective for diverse chemical species separation tasks.

Conclusions:

  • A validated, generalized framework for multi-echo GRE MR signal modeling and chemical species separation has been established.
  • The framework's modular design, based on matrix abstraction, allows for broad application and adaptation.
  • Freely available software facilitates the implementation and further development of this advanced MRI analysis technique.