ProFit-1D for quantifying J-difference edited data at 3T

Chan, KL; Borbath, T; Sherlock, S; Maher, EA; Patel, TR; Henning, A

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ProFit-1D for quantifying J-difference edited data at 3T

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Borbath, T
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Henning, A
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;

Externe Ressourcen

https://submissions.mirasmart.com/ISMRM2024/Itinerary/ConferenceMatrixEventDetail.aspx?ses=O-54
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Zitation

Chan, K., Borbath, T., Sherlock, S., Maher, E., Patel, T., & Henning, A. (2024). ProFit-1D for quantifying J-difference edited data at 3T. Poster presented at ISMRM & ISMRT Annual Meeting & Exhibition 2024, Singapore.

Zitierlink: https://hdl.handle.net/21.11116/0000-000F-3964-1

Zusammenfassung

Motivation: Reproducible and accurate fitting of the MR spectrum is critical in estimating metabolite concentrations. We have previously developed a fitting software called ProFit-1D which was shown to fit 9.4T sLASER data from the human brain with high accuracy and precision. Goal(s): Here, ProFit-1D was optimized for fitting 3T J-difference edited data. Approach: ProFit-1D was evaluated for accuracy and precision in simulated and in vivo 2HG-edited and GABA- edited data and compared to that of Gannet and LCModel Results: ProFit-1D was found to be more accurate than LCModel in fitting the GABA-edited and 2HG-edited data and more precise than Gannet in fitting the GABA-edited spectra. Impact: Here, we show that ProFit-1D produces more accurate measurements than LCModel and more precise measurements than Gannet in simulated and in vivo spectra from tumors and healthy participants. ProFit-1D is a promising fitting software with high clinical applicability.