Meeting Banner
Abstract #1843

Linewidth and lineshape bias in modelled outcomes from GABA-edited 1H MRS

Alexander R Craven1,2, Lars Ersland2, Tiffany Bell3,4,5, Ashley Harris3,4,5, Kenneth Hugdahl1,6,7, and Georg Oeltzschner8,9
1Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway, 2Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway, 3Department of Radiology, University of Calgary, Calgary, AB, Canada, 4Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada, 5Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada, 6Division of Psychiatry, Haukeland University Hospital, Bergen, Norway, 7Department of Radiology, Haukeland University Hospital, Bergen, Norway, 8Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, 9F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States

Synopsis

Keywords: Spectroscopy, Spectroscopy

Motivation: The study addresses a gap in literature concerning the impact of spectral linewidth and lineshape differences on GABA+ estimates.

Goal(s): To assess the degree to which differences in linewidth/lineshape may confound GABA+ estimates.

Approach: In-vivo GABA+-edited spectra (N=222) were quantified with six modelling algorithms after applying varying degrees of Lorentzian and Gaussian linebroadening.

Results: Most algorithms showed strong negative associations between amount of Lorentzian linebroadening and GABA+ estimate (2-5% per Hz LB), consistently across datasets. Gaussian linebroadening showed contrasting, substantially weaker associations.
In functional applications and cases of differing T2 relaxation between regions or subject groups, these results indicate a potentially significant confound.

Impact: Comparing metabolite concentration estimates across different anatomical regions, subject groups or experimental conditions requires appropriate handling of differences in linewidth and linebroadening mechanisms. We demonstrate that several modelling algorithms have linebroadening biases, differing by lineshape, that may confound findings.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Abstract

Keywords