Analysis of [18F]flutemetamol PET data

11C-labelled Pittsburgh compound B, PIB, is a widely used PET radiopharmaceutical for the detection amyloid β plaques. The relatively short half-life of 11C limits the diagnostic use of [11C]PIB to PET sites close to cyclotron and radiochemistry facilities. [18F]Flutemetamol ([18F]AH110690, [18F]-3'-F-6-OH-BTA1, [18F]-GE067) is a derivative of PIB (see MICAD) that due to the longer halflife of 18F allows distribution of the radiopharmaceutical to distant PET sites. [18F]Flutemetamol is approved for clinical use.

Like with [11C]PIB, the binding of [18F]flutemetamol to amyloid-β in the grey brain matter is specific and reversible. Due to its higher lipophilicity the clearance of [18F]flutemetamol from grey matter, and especially from white matter, is slower (Snellman et al., 2012). In rodents, 60 min after administration the uptake ratio of white matter to parietal cortex was ∼11 (Snellman et al., 2012). PIB and related compounds also have affinity to the β-sheet structure present in the myelin in white matter. Metabolism of [18F]flutemetamol in rodents is faster than that of [11C]PIB, but very low bone uptake implicates that marked amounts of free [18F]F- are not formed (Snellman et al., 2012). [18F]Flutemetamol and its metabolites are cleared from circulation via hepatobiliary route and kidneys (Koole et al., 2009). Gallbladder wall is the critical organ in dosimetry.

The clinical performance of [18F]flutemetamol and [11C]PIB is similar (Vanderberghe et al., 2010; Leinonen et al., 2013; Hatashita et al., 2014; Landau et al., 2014). Clinical utility for detecting amyloid &meta; plaques has been demonstrated (Vanderberghe et al., 2010; Wolk et al., 2011; Rinne et al., 2012 and 2014; Wong et al., 2013; Leinonen et al., 2013 and 2014; Ikonomovic et al., 2016; Thal et al., 2018). [18F]Flutemetamol PET helps in diagnosis of early-onset dementia and affects the patient management plan (Zwan et al., 2017). In patients with amnestic mild cognitive impairment, presence of amyloid pathology at early phase predicts amyloid accumulation at 3-year follow-up PET scan (Rauhala et al., 2022). Brain uptake correlates negatively with [18F]FDG uptake (Kalheim et al., 2018).

Cerebellum (or preferably cerebellar grey matter) or pons is used as the reference region in the analysis of brain PET data (Nelissen et al., 2009; Heurling et al., 2015a; Pemberton et al., 2023). The brain uptake of [18F]flutemetamol is usually reported as SUV ratio (SUVR), which reaches its maximum at ∼80 min in AD patients and then stays almost constant (Nelissen et al., 2009). Test-retest variability of regional SUVRs are 1-4% (Vanderberghe et al., 2010). SUVR85-105min was slightly higher than DVR (see below) but correlation was good (Nelissen et al., 2009). Pons could also be used as reference region but the SUVRs are then slightly lower than DVRs (Nelissen et al., 2009). The proposed SUVR start calculation time of ∼80-90 min has since been used in several studies as the start time of the static PET scan (Hatashita et al., 2014; Rinne et al., 2014; Kalheim et al., 2018; Rauhala et al., 2022). SUVR image analysis can be automated (Thurfjell et al., 2014). Even simple visual assessment of [18F]flutemetamol PET images good sensitivity (Curtis et al., 2015).

Nelissen et al (2009) used metabolite corrected arterial plasma as input function for compartmental model analysis. PET data was collected in three phases, totally until 250 min after administration. Reversible two-tissue compartmental model (2TCM) generally fitted the data better than one-tissue compartmental model or irreversible model, based on AIC. Cerebral VB was constrained to 2% in pons and subcortical white matter, to 3.5% in the striatum, to 5% in cerebellar and occipital cortex, and to 4% in other cortical regions. Model rate constants were used to calculate the total distribution volume (VT), and further the distribution volume ratio (DVR) using cerebellum as the reference region. VT and DVR were also calculated with Logan plot, starting linear fitting at 60 min, and subtracting vascular contribution from the tissue data. 2TCM and Logan plots (with plasma and reference tissue input) provided highly correlated results (Nelissen et al., 2009). Reference input Logan plot can be also used in mouse models (Snellman et al., 2014). Binding potential (BPND) can be calculated from DVR as BPND=DVR-1. Logan plot and reference tissue input compartmental models can be applied to calculate parametric images of DVR and BPND (Heurling et al., 2015a; Heeman et al., 2021). Results of reference input Logan plot were not much affected by using k2'. Basis function method provided BPND images that best matched with the results of regional 2TCM analysis (Heurling et al., 2015a). Spectral analysis may help in separation of β-amyloid binding and white matter uptake (Heurling et al., 2015b).

See also:


Adamczuk K, Schaeverbeke J, Nelissen N, Neyens V, Vandenbulcke M, Goffin K, Lilja J, Hilven K, Dupont P, Van Laere K, Vandenberghe R. Amyloid imaging in cognitively normal older adults: comparison between 18F-flutemetamol and 11C-Pittsburgh compound B. Eur J Nucl Med Mol Imaging 2016; 43(1): 142-151. doi: 10.1007/s00259-015-3156-9.

Heurling K, Leuzy A, Zimmer ER, Lubberink M, Nordberg A. Imaging β-amyloid using [18F]flutemetamol positron emission tomography: from dosimetry to clinical diagnosis. Eur J Nucl Med Mol Imaging 2016; 43(2): 362-373. doi: 10.1007/s00259-015-3208-1.

Landau SM, Thomas BA, Thurfjell L, Schmidt M, Margolin R, Mintun M, Pontecorvo M, Baker SL, Jagust WJ; Alzheimer’s Disease Neuroimaging Initiative. Amyloid PET imaging in Alzheimer's disease: a comparison of three radiotracers. Eur J Nucl Med Mol Imaging 2014; 41(7): 1398-1407. doi: 10.1007/s00259-014-2753-3.

Pemberton HG, Collij LE, Heeman F, Bollack A, Shekari M, Salvadó G, Alves IL, Garcia DV, Battle M, Buckley C, Stephens AW, Bullich S, Garibotto V, Barkhof F, Gispert JD, Farrar G; AMYPAD consortium. Quantification of amyloid PET for future clinical use: a state-of-the-art review. Eur J Nucl Med Mol Imaging 2022; 49(10): 3508-3528. doi: 10.1007/s00259-022-05784-y.

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Updated at: 2023-06-13
Created at: 2019-03-17
Written by: Vesa Oikonen