| Zugriffsnummer | 48504 |
| Dokumenttyp | Konferenzartikel |
| Peer Review | unbekannt |
| Sprache | Englisch |
| Titel | Macromolecule modelling for improved metabolite quantification using very short echo time MRS at 3T: The PRaMM model |
| Autor(in); Institution |
Dell’Orco, Andrea; 8.1, Biomedizinische Magnetresonanz, PTB-Berlin
Riemann, Layla Tabea; 8.1, Biomedizinische Magnetresonanz, PTB-Berlin
Aydin, Semiha; 8.1, Biomedizinische Magnetresonanz, PTB-Berlin
Schell, M.; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuroradiology, Berlin, GERMANY
|
| Quelle/Jahr | Proceedings of the International Society for Magnetic Resonance in Medicine: 30 (2022), 2 S. |
| Artikelnummer | 0161 |
| Availability | [online only] |
| ISSN | 1545-4428 (online) |
| DOI | |
| Konferenzangaben | 31st Joint Annual Meeting ISMRM-ESMRMB & ISMRT, London, 07-12, May, 2022, UK |
| Zusammenfassung | The accurate quantification of ultra-short echo-time 1H-MRS spectra is challenging due to broad macromolecular (MM) signal components. Here, we propose the parameterized-ratio MM (PRaMM) method to model the MM and its use in linear-combination model fitting of 1H-MRS spectra. The PRaMM method uses ratios of MM signal amplitudes as soft-constraints to limit the degrees of freedom of the fitting model, while allowing for more flexibility than commonly used approaches. The suggested model is demonstrated to improve the quantification of metabolites compared to two common methods for MM treatment. |
| Themenbereich der Metrologie | Metrologie in der Medizin |
| Forschungsprojekt | 18HLT09: NeuroMET2: Metrology and innovation for early diagnosis and accurate stratification of patients with neurodegenerative diseases |
| Förderinformationen (1) |
Förderername: European Commission (EC)
Förderer ID: 0000 0001 2242 8989 Förderer ID Typ: ISNI Förderprogramm: EMPIR 2018 Health Titel der Förderung: 18HLT09: NeuroMET2: Metrology and innovation for early diagnosis and accurate stratification of patients with neurodegenerative diseases Förderungsnummer: 18HLT09 |
Zitierung
Dell’Orco, A., Riemann, L. T., Aydin, S., Schell, M., & Fillmer, A. (2022). Macromolecule modelling for improved metabolite quantification using very short echo time MRS at 3T: The PRaMM model. 31st Joint Annual Meeting ISMRM-ESMRMB & ISMRT, London, 07-12, May, 2022, UK. https://doi.org/10.58530/2022/0161