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Non-invasive quantification of 18F-florbetaben with total-body EXPLORER PET.
Holy, Emily Nicole; Li, Elizabeth; Bhattarai, Anjan; Fletcher, Evan; Alfaro, Evelyn R; Harvey, Danielle J; Spencer, Benjamin A; Cherry, Simon R; DeCarli, Charles S; Fan, Audrey P.
Afiliação
  • Holy EN; Department of Neurology, University of California (UC) Davis Health, 1590 Drew Avenue, Davis, CA, 95618, USA. enholy@ucdavis.edu.
  • Li E; Department of Biomedical Engineering, UC Davis, Davis, USA. enholy@ucdavis.edu.
  • Bhattarai A; Department of Biomedical Engineering, UC Davis, Davis, USA.
  • Fletcher E; Department of Neurology, University of California (UC) Davis Health, 1590 Drew Avenue, Davis, CA, 95618, USA.
  • Alfaro ER; Department of Biomedical Engineering, UC Davis, Davis, USA.
  • Harvey DJ; Department of Neurology, University of California (UC) Davis Health, 1590 Drew Avenue, Davis, CA, 95618, USA.
  • Spencer BA; Department of Neurology, University of California (UC) Davis Health, 1590 Drew Avenue, Davis, CA, 95618, USA.
  • Cherry SR; Department of Public Health Sciences, UC Davis Health, Davis, USA.
  • DeCarli CS; Department of Biomedical Engineering, UC Davis, Davis, USA.
  • Fan AP; Department of Radiology, UC Davis Health, Davis, USA.
EJNMMI Res ; 14(1): 39, 2024 Apr 16.
Article em En | MEDLINE | ID: mdl-38625413
ABSTRACT

BACKGROUND:

Kinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.

METHODS:

18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer's disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ([Formula see text] was also calculated from the multi-reference tissue model (MRTM).

RESULTS:

Amyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with [Formula see text] analysis. [Formula see text]and VT from kinetic models were correlated (r² = 0.46, P < 2[Formula see text] with a stronger positive correlation observed in amyloid-positive participants, indicating reliable model fits with the IDIFs. VT from 2TCM was highly correlated ([Formula see text]= 0.65, P < 2[Formula see text]) with Logan graphical VT estimation.

CONCLUSION:

Non-invasive quantification of amyloid binding from total-body 18F-florbetaben PET data is feasible using aorta IDIFs with high agreement between kinetic distribution volume parameters compared to [Formula see text]in amyloid-positive and amyloid-negative older individuals.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article