Comparison of different linear‐combination modeling algorithms for short‐TE proton spectra
Short‐TE proton MRS is used to study metabolism in the human brain. Common analysis methods model the data as a linear combination of metabolite basis spectra. This large‐scale multi‐site study compares the levels of the four major metabolite complexes in short‐TE spectra estimated by three linear‐c...
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| Published in | NMR in biomedicine Vol. 34; no. 4; pp. e4482 - n/a |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Wiley Subscription Services, Inc
01.04.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0952-3480 1099-1492 1099-1492 |
| DOI | 10.1002/nbm.4482 |
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| Summary: | Short‐TE proton MRS is used to study metabolism in the human brain. Common analysis methods model the data as a linear combination of metabolite basis spectra. This large‐scale multi‐site study compares the levels of the four major metabolite complexes in short‐TE spectra estimated by three linear‐combination modeling (LCM) algorithms. 277 medial parietal lobe short‐TE PRESS spectra (TE = 35 ms) from a recent 3 T multi‐site study were preprocessed with the Osprey software. The resulting spectra were modeled with Osprey, Tarquin and LCModel, using the same three vendor‐specific basis sets (GE, Philips and Siemens) for each algorithm. Levels of total N‐acetylaspartate (tNAA), total choline (tCho), myo‐inositol (mI) and glutamate + glutamine (Glx) were quantified with respect to total creatine (tCr). Group means and coefficient of variations of metabolite estimates agreed well for tNAA and tCho across vendors and algorithms, but substantially less so for Glx and mI, with mI systematically estimated as lower by Tarquin. The cohort mean coefficient of determination for all pairs of LCM algorithms across all datasets and metabolites was
R2¯= 0.39, indicating generally only moderate agreement of individual metabolite estimates between algorithms. There was a significant correlation between local baseline amplitude and metabolite estimates (cohort mean
R2¯= 0.10).
While mean estimates of major metabolite complexes broadly agree between linear‐combination modeling algorithms at group level, correlations between algorithms are only weak‐to‐moderate, despite standardized preprocessing, a large sample of young, healthy and cooperative subjects, and high spectral quality. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes.
Three linear‐combination algorithms (Osprey, Tarquin and LCModel) were used to quantify the levels of tNAA, tCho, mI, and Glx in 277 short‐TE PRESS. Group means and CVs of metabolite estimates agreed well for tNAA and tCho, but substantially less so for Glx and mI, with a cohort mean correlation coefficient of
R2¯= 0.39, indicating moderate agreement between algorithms. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23 |
| ISSN: | 0952-3480 1099-1492 1099-1492 |
| DOI: | 10.1002/nbm.4482 |