Cargando…
Effects of different macromolecular models on reproducibility of FID‐MRSI at 7T
PURPOSE: A properly characterized macromolecular (MM) contribution is essential for accurate metabolite quantification in FID‐MRSI. MM information can be included into the fitting model as a single component or parameterized and included over several individual MM resonances, which adds flexibility...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851974/ https://www.ncbi.nlm.nih.gov/pubmed/31393037 http://dx.doi.org/10.1002/mrm.27922 |
_version_ | 1783469730871377920 |
---|---|
author | Heckova, Eva Považan, Michal Strasser, Bernhard Motyka, Stanislav Hangel, Gilbert Hingerl, Lukas Moser, Philipp Lipka, Alexandra Gruber, Stephan Trattnig, Siegfried Bogner, Wolfgang |
author_facet | Heckova, Eva Považan, Michal Strasser, Bernhard Motyka, Stanislav Hangel, Gilbert Hingerl, Lukas Moser, Philipp Lipka, Alexandra Gruber, Stephan Trattnig, Siegfried Bogner, Wolfgang |
author_sort | Heckova, Eva |
collection | PubMed |
description | PURPOSE: A properly characterized macromolecular (MM) contribution is essential for accurate metabolite quantification in FID‐MRSI. MM information can be included into the fitting model as a single component or parameterized and included over several individual MM resonances, which adds flexibility when pathologic changes are present but is prone to potential overfitting. This study investigates the effects of different MM models on MRSI reproducibility. METHODS: Clinically feasible, high‐resolution FID‐MRSI data were collected in ~5 min at 7 Tesla from 10 healthy volunteers and quantified via LCModel (version 6.3) with 3 basis sets, each with a different approach for how the MM signal was handled: averaged measured whole spectrum (full MM), 9 parameterized components (param MM) with soft constraints to avoid overparameterization, or without any MM information included in the fitting prior knowledge. The test–retest reproducibility of MRSI scans was assessed voxel‐wise using metabolite coefficients of variation and intraclass correlation coefficients and compared between the basis sets. Correlations of concentration estimates were investigated for the param MM fitting model. RESULTS: The full MM model provided the most reproducible quantification of total NAA, total Cho, myo‐inositol, and glutamate + glutamine ratios to total Cr (coefficients of variations ≤ 8%, intraclass correlation coefficients ≥ 0.76). Using the param MM model resulted in slightly lower reproducibility (up to +3% higher coefficients of variations, up to −0.1 decreased intraclass correlation coefficients). The quantification of the parameterized macromolecules did not affect quantification of the overlapping metabolites. CONCLUSION: Clinically feasible FID‐MRSI with an experimentally acquired MM spectrum included in prior knowledge provides highly reproducible quantification for the most common neurometabolites in healthy volunteers. Parameterization of the MM spectrum may be preferred as a compromise between quantification accuracy and reproducibility when the MM content is expected to be pathologically altered. |
format | Online Article Text |
id | pubmed-6851974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68519742019-11-18 Effects of different macromolecular models on reproducibility of FID‐MRSI at 7T Heckova, Eva Považan, Michal Strasser, Bernhard Motyka, Stanislav Hangel, Gilbert Hingerl, Lukas Moser, Philipp Lipka, Alexandra Gruber, Stephan Trattnig, Siegfried Bogner, Wolfgang Magn Reson Med Note—Spectroscopic Methodology PURPOSE: A properly characterized macromolecular (MM) contribution is essential for accurate metabolite quantification in FID‐MRSI. MM information can be included into the fitting model as a single component or parameterized and included over several individual MM resonances, which adds flexibility when pathologic changes are present but is prone to potential overfitting. This study investigates the effects of different MM models on MRSI reproducibility. METHODS: Clinically feasible, high‐resolution FID‐MRSI data were collected in ~5 min at 7 Tesla from 10 healthy volunteers and quantified via LCModel (version 6.3) with 3 basis sets, each with a different approach for how the MM signal was handled: averaged measured whole spectrum (full MM), 9 parameterized components (param MM) with soft constraints to avoid overparameterization, or without any MM information included in the fitting prior knowledge. The test–retest reproducibility of MRSI scans was assessed voxel‐wise using metabolite coefficients of variation and intraclass correlation coefficients and compared between the basis sets. Correlations of concentration estimates were investigated for the param MM fitting model. RESULTS: The full MM model provided the most reproducible quantification of total NAA, total Cho, myo‐inositol, and glutamate + glutamine ratios to total Cr (coefficients of variations ≤ 8%, intraclass correlation coefficients ≥ 0.76). Using the param MM model resulted in slightly lower reproducibility (up to +3% higher coefficients of variations, up to −0.1 decreased intraclass correlation coefficients). The quantification of the parameterized macromolecules did not affect quantification of the overlapping metabolites. CONCLUSION: Clinically feasible FID‐MRSI with an experimentally acquired MM spectrum included in prior knowledge provides highly reproducible quantification for the most common neurometabolites in healthy volunteers. Parameterization of the MM spectrum may be preferred as a compromise between quantification accuracy and reproducibility when the MM content is expected to be pathologically altered. John Wiley and Sons Inc. 2019-08-08 2020-01 /pmc/articles/PMC6851974/ /pubmed/31393037 http://dx.doi.org/10.1002/mrm.27922 Text en © 2019 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Note—Spectroscopic Methodology Heckova, Eva Považan, Michal Strasser, Bernhard Motyka, Stanislav Hangel, Gilbert Hingerl, Lukas Moser, Philipp Lipka, Alexandra Gruber, Stephan Trattnig, Siegfried Bogner, Wolfgang Effects of different macromolecular models on reproducibility of FID‐MRSI at 7T |
title | Effects of different macromolecular models on reproducibility of FID‐MRSI at 7T |
title_full | Effects of different macromolecular models on reproducibility of FID‐MRSI at 7T |
title_fullStr | Effects of different macromolecular models on reproducibility of FID‐MRSI at 7T |
title_full_unstemmed | Effects of different macromolecular models on reproducibility of FID‐MRSI at 7T |
title_short | Effects of different macromolecular models on reproducibility of FID‐MRSI at 7T |
title_sort | effects of different macromolecular models on reproducibility of fid‐mrsi at 7t |
topic | Note—Spectroscopic Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851974/ https://www.ncbi.nlm.nih.gov/pubmed/31393037 http://dx.doi.org/10.1002/mrm.27922 |
work_keys_str_mv | AT heckovaeva effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT povazanmichal effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT strasserbernhard effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT motykastanislav effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT hangelgilbert effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT hingerllukas effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT moserphilipp effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT lipkaalexandra effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT gruberstephan effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT trattnigsiegfried effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t AT bognerwolfgang effectsofdifferentmacromolecularmodelsonreproducibilityoffidmrsiat7t |