English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Macromolecular background signal and non‐Gaussian metabolite diffusion determined in human brain using ultra‐high diffusion weighting

Şimşek, K., Döring, A., Pampel, A., Möller, H. E., & Kreis, R. (2022). Macromolecular background signal and non‐Gaussian metabolite diffusion determined in human brain using ultra‐high diffusion weighting. Magnetic Resonance in Medicine, 88(5), 1962-1977. doi:10.1002/mrm.29367.

Item is

Basic

show hide
Genre: Journal Article

Files

show Files
hide Files
:
Simsek_2022.pdf (Publisher version), 3MB
Name:
Simsek_2022.pdf
Description:
-
OA-Status:
Hybrid
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Şimşek, Kadir1, 2, 3, Author
Döring, André4, Author
Pampel, André5, Author           
Möller, Harald E.5, Author           
Kreis, Roland1, 3, Author
Affiliations:
1Magnetic Resonance Methodology, University Hospital Bern, Switzerland, ou_persistent22              
2Graduate School for Cellular and Biomedical Sciences (GCB), University of Bern, Switzerland, ou_persistent22              
3Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland, ou_persistent22              
4Brain Research Imaging Centre, School of Psychology, Cardiff University, United Kingdom, ou_persistent22              
5Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              

Content

show
hide
Free keywords: MR spectroscopy; Apparent diffusion constants; Brain; Diffusion; Fitting; Macromolecules; Microstructure; Modeling; Quantification
 Abstract: Purpose: Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non-Gaussian diffusion of brain metabolites with strongly diffusion-weighted MR spectroscopy. Methods: Short echo time MRS with strong diffusion-weighting with b-values up to 25 ms/μm2 at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion-compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal. Results: The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non-Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum. Conclusion: The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure.

Details

show
hide
Language(s): eng - English
 Dates: 2022-07-08
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1002/mrm.29367
Other: epub 2022
PMID: 35803740
 Degree: -

Event

show

Legal Case

show

Project information

show hide
Project name : -
Grant ID : 202962; 320030-175984
Funding program : -
Funding organization : Swiss National Science Foundation

Source 1

show
hide
Title: Magnetic Resonance in Medicine
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: New York : Wiley-Liss
Pages: - Volume / Issue: 88 (5) Sequence Number: - Start / End Page: 1962 - 1977 Identifier: ISSN: 0740-3194
CoNE: https://pure.mpg.de/cone/journals/resource/954925538149