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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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Blood Flow Imaging with Ultrafast Doppler

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Published on: October 14, 2020

Low-bandwidth space/frequency component separation for quantitative imaging.

Mikhail Zubkov¹, Timothy Stait-Gardner¹, William S Price¹

¹Nanoscale Organisation and Dynamics Group, School of Science and Health, Western Sydney University, Penrith, NSW, Australia.

Magnetic Resonance in Chemistry : MRC

|September 8, 2016

Summary

This summary is machine-generated.

A new quantitative MRI method uses low bandwidth to separate signals from different chemical species. This technique improves the accuracy of diffusion and relaxation measurements in multicomponent systems, especially those with more than two components.

Keywords:

1H, diffusion MRI low bandwidth multicomponent quantitative suppression

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Area of Science:

Magnetic Resonance Imaging
Quantitative MRI
Multicomponent System Analysis

Background:

Quantitative MRI is crucial for analyzing multicomponent systems.
Isolating contributions from different species is essential for accurate analysis.
Distinct chemical shifts allow for species separation.

Purpose of the Study:

To develop and validate a novel method for separating signals from different chemical species in quantitative MRI.
To assess the impact of this separation technique on the accuracy and variability of diffusion and relaxation measurements.
To compare the performance of the new method with conventional techniques for multicomponent analysis.

Main Methods:

Implementation of a low acquisition bandwidth technique in routine MRI diffusion and relaxation pulse sequences.
Testing the method on multicomponent systems including water/polyethylene glycol and chloroform/TMS/polyethylene glycol solutions.
Analysis of spectrally separated data using conventional monoexponential fitting and comparison with biexponential/triexponential fitting for unseparated data.

Main Results:

Successful spectral separation of NMR contributions from different species in the image space.
The low-bandwidth separation method reduced variability in determined diffusion coefficients and relaxation times, particularly for three-component systems.
Accuracy comparable to common methods for bicomponent systems and superior for systems with more than two components.

Conclusions:

The low-bandwidth separation method effectively separates multicomponent systems based on chemical shift differences.
This technique enhances the reliability and accuracy of quantitative MRI analyses for complex mixtures.
The method offers a significant advantage over conventional approaches for systems with multiple components.