Aarhus Universitets segl

English

Du er her: AU » Om AU » Organisation » Developing a metabolic clearance rate framework as a tran...

Om AU

Developing a metabolic clearance rate framework as a translational analysis approach for hyperpolarized 13C magnetic resonance imaging

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

DOI

  • James T Grist, University of Oxford, University of Birmingham
    • ,
  • Nikolaj Bøgh
  • Esben Søvsø Szocska Hansen
  • Anna Schneider, University of Oxford
    • ,
  • Richard Healicon, University of Oxford
    • ,
  • Vicky Ball, University of Oxford
    • ,
  • Jack Miller
  • Sean Smart, University of Oxford
    • ,
  • Yvonne Couch, University of Oxford
    • ,
  • Alastair Buchan, University of Oxford
    • ,
  • Damian J Tyler, University of Oxford
    • ,
  • Christoffer Laustsen

Hyperpolarized carbon-13 magnetic resonance imaging is a promising technique for in vivo metabolic interrogation of alterations between health and disease. This study introduces a formalism for quantifying the metabolic information in hyperpolarized imaging. This study investigated a novel perfusion formalism and metabolic clearance rate (MCR) model in pre-clinical stroke and in the healthy human brain. Simulations showed that the proposed model was robust to perturbations in T 1, transmit B 1, and k PL. A significant difference in ipsilateral vs contralateral pyruvate derived cerebral blood flow (CBF) was detected in rats (140 ± 2 vs 89 ± 6 mL/100 g/min, p < 0.01, respectively) and pigs (139 ± 12 vs 95 ± 5 mL/100 g/min, p = 0.04, respectively), along with an increase in fractional metabolism (26 ± 5 vs 4 ± 2%, p < 0.01, respectively) in the rodent brain. In addition, a significant increase in ipsilateral vs contralateral MCR (0.034 ± 0.007 vs 0.017 ± 0.02/s, p = 0.03, respectively) and a decrease in mean transit time (31 ± 8 vs 60 ± 2 s, p = 0.04, respectively) was observed in the porcine brain. In conclusion, MCR mapping is a simple and robust approach to the post-processing of hyperpolarized magnetic resonance imaging.

OriginalsprogEngelsk
Artikelnummer1613
TidsskriftScientific Reports
Vol/bind13
Nummer1
ISSN2045-2322
DOI
StatusUdgivet - jan. 2023

Se relationer på Aarhus Universitet Citationsformater

ID: 305424317