PEAKIT: A Gaussian Process regression analysis tool for chemical exchange saturation transfer spectra.
Chemical Exchange Saturation Transfer (CEST)
Gaussian process regression
Noise level
Peak detection
Python
Tkinter
User interface
Z-spectrum
Journal
Journal of magnetic resonance (San Diego, Calif. : 1997)
ISSN: 1096-0856
Titre abrégé: J Magn Reson
Pays: United States
ID NLM: 9707935
Informations de publication
Date de publication:
01 2022
01 2022
Historique:
received:
08
10
2021
revised:
26
11
2021
accepted:
30
11
2021
pubmed:
16
12
2021
medline:
27
1
2022
entrez:
15
12
2021
Statut:
ppublish
Résumé
Chemical Exchange Saturation Transfer (CEST) is a powerful technique for metabolic imaging, capable of exploring concentrations in the μM to mM range. However, extracting quantitative information from Z-spectra can be challenging due to the non-CEST contributions present and the limited knowledge about the exchanging pools. The PEAKIT tool is proposed as an alternative approach to quantifying CEST peaks, which requires no prior assumptions about the frequency offset or the underlying shape of the baseline. Specifically, the tool takes as input an experimental Z-spectrum and proceeds to identify peak candidates. After a baseline estimation based on Gaussian Process regression, PEAKIT outputs the chemical shift offsets, the areas, the heights and the statistical significance of the detected peaks. The performance and limitations of the PEAKIT tool are discussed for in vitro and in vivo applications.
Identifiants
pubmed: 34906779
pii: S1090-7807(21)00211-1
doi: 10.1016/j.jmr.2021.107122
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
107122Informations de copyright
Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.