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Related Concept Videos

NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

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When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
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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.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
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¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

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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.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
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¹H NMR: Complex Splitting01:13

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A proton M that is coupled to a proton X results in doublet signals for M. However, NMR-active nuclei can be simultaneously coupled to more than one nonequivalent nucleus. When M is coupled to a second proton A, such as in styrene oxide, each peak in the doublet is split into another doublet.
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¹H NMR Signal Integration: Overview00:58

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The intensity of a signal, which can be represented by the area under the peak, depends on the number of protons contributing to that signal. The area under each peak is shown as a vertical line called an integral, with the integral value listed under it, as seen in the proton NMR spectrum of benzyl acetate. Each integral value is divided by the smallest integral value to obtain the ratio of the number of protons producing each signal. The ratio reveals the relative number of protons and not...
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¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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A Multimodal Wide-Field Fourier-Transform Raman Microscope
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Spectral decomposition for resolving partial volume effects in MRSI.

Mohammed Z Goryawala1, Sulaiman Sheriff1, Radka Stoyanova2

  • 1Department of Radiology, University of Miami, Miami, Florida, USA.

Magnetic Resonance in Medicine
|November 14, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a spectral decomposition (sDec) technique to improve brain metabolite concentration accuracy in MR spectroscopic imaging (MRSI). The method reduces errors caused by tissue partial volume effects, enhancing specificity for white matter and gray matter analysis.

Keywords:
MR spectroscopic imaging (MRSI)gray matterpartial volume effectsspectral decompositionwhite matter

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Area of Science:

  • Neuroimaging
  • Magnetic Resonance Imaging
  • Spectroscopy

Background:

  • Magnetic Resonance Spectroscopic Imaging (MRSI) is crucial for estimating brain metabolite concentrations.
  • Partial volume effects from different tissues complicate accurate MRSI quantification.
  • Tissue-specific analysis is needed to overcome these limitations.

Purpose of the Study:

  • To evaluate a spectral decomposition (sDec) technique for enhancing tissue specificity in MRSI.
  • To improve the accuracy of brain metabolite concentration estimation by incorporating prior tissue distribution knowledge.
  • To assess the sDec method's performance in separating white matter (WM) and gray matter (GM) spectra.

Main Methods:

  • A spectral decomposition (sDec) technique was developed and evaluated.
  • Simulations and in vivo studies were conducted to compare sDec with traditional spectral fitting methods.
  • Metabolite quantifications were assessed against voxel-wise fitting, linear regression, and regionally integrated spectra.

Main Results:

  • The sDec method demonstrated low error rates (<2% for GM, 3.5% for putamen) in simulation studies.
  • sDec significantly reduced errors compared to methods ignoring partial volume effects.
  • Analysis of 197 studies revealed significant differences in metabolite values and age-related changes, with sDec improving spectral quality and revealing partial volume effects on age correlations.

Conclusions:

  • The sDec analysis approach offers significant value for MRSI studies, particularly in pathologies affecting WM or GM.
  • This technique is beneficial for analyzing smaller brain regions susceptible to partial volume effects.
  • sDec enhances the reliability of neurometabolite quantification in diverse clinical and research applications.