Quantification of myocardial perfusion using [18F]Flurpiridaz


[18F]Flurpiridaz (BMS-747158-02, [18F]BMS-747158-01, 2-tert-Butyl-4-chloro-5-[4-(2-[18F]fluoroethoxymethyl)-benzyloxy]-2H-pyridazin-3-one, [18F]BMS) is a myocardial perfusion imaging (MPI) radioligand which binds to (inhibits) the mitochondrial complex 1 (MC-1) of the electron transport chain with high affinity. It is a structural analogue of the insecticide pyridaben, which competes for MC-1 binding with ubiquinone. Yet, Flurpiridaz does not affect the viability of cardiomyocytes. [18F]Flurpiridaz can be safely used for clinical MPI (Maddahi et al. 2011 and 2018). [18F]Flurpiridaz and related compounds have shown promise in quantification of MC-1 activity in the brain (Fukumoto et al., 2012; Tsukada et al., 2014), and later also in the liver (Rokugawa et al., 2017) and kidney.

The radiotracer has high first-pass extraction, >0.9 over the physiological perfusion values (Huisman et al., 2008), and high retention in the heart and kidney, and because of the high density of mitochondria, in the myocardial muscle the image contrast is very good. Myocardial uptake is not dependent on food intake (Yu et al., 2009). Instead it is partly dependent on mitochondrial membrane potential, especially when it is reduced, which was seen as underestimated perfusion values in pig studies with ligated arteries (Nekolla et al., 2009).

Uptake in the brain is intermediate and low in muscle (Tsukada et al., 2014). [18F]Flurpiridaz is mainly excreted via kidneys into urine.


Input function

The model input function can be estimated from a ROI placed on LV chamber. Metabolite correction is not needed (Nekolla et al., 2009). In porcine studies the LV cavity ROI was about 2×2×2 cm3 in size, and provided more reliable input TAC than arterial sampling (Guehl et al., 2017a). Obtaining the good quality input curve from the cavity still demands optimization of the imaging protocol and image reconstruction parameters.

In a pig study, Petibon et al. (2017a and 2017b) report that the image-derived blood TAC was transformed to plasma TAC using a factor based on previous pig studies, but the factor is not given in the referred abstract. Based on the rat study by Tsukada et al. (2014), plasma-to-blood ratio of [18F]Flurpiridaz can be calculated to be steadily 1.28 during 60 min after injection.

Compartmental model

Regional tissue curves (0-20 min after tracer injection) can be fitted using 3-compartmental model (two tissue compartments) with assumption of irreversible trapping (k4=0), using geometrical recovery and spill-over correction (Nekolla et al., 2009). In a 5-min pig study even assumption k3=0 could be made (Petibon et al., 2017b). K1 is assumed to represent blood flow, either directly, or after division by extraction fraction E=0.94 (Petibon et al., 2017a). Extraction fraction can be assumed to be flow-independent in this case (Nekolla et al., 2009). Nekolla et al. (2009) noticed a modest underestimation of myocardial blood flow (MBF), and discussed possible reasons for that.

In practise, it has been difficult to estimate k2 and k3 independently in the myocardium. To improve parameter identifiability, Alpert et al. (2012) and Guehl et al (2017a) fixed k3 at a nominal physiologically plausible value of 0.026 min-1. Setting k3 to different values in the range 0 - 0.1 min-1 has only minimal effect on K1 (Alpert et al., 2012; Guehl et al., 2017a).


Fractional uptake rates (FURs, retention) correlated well with MBF calculated using compartmental model (Sherif et al., 2011), although FUR estimates will need a conversion factor to achieve quantitative MBF.

Patlak plot

Feasible FUR analysis suggests that also Patlak plot, if linear, could be used to analyze the data. Patlak analysis provides net influx rate (Ki), which is usually close to FUR estimate, and relates to compartment model parameters as

If k2 << k3, then Ki ≅ K1 (and K1 is assumed to represent MBF with this tracer). If k2 >> k3, then Ki ≅ (K1/k2) × k3, which would not correlate well with MBF. The k2 and k3 estimates reported by Nekolla et al. (2009; Table 4) would suggest that the former could be the case, but the estimates reported by Alpert et al. 2012, and the level of FUR values (Sherif et al., 2011) would suggest something in between.


Standardized uptake values (SUVs) calculated 5-10 min p.i. correlated well with MBF calculated using compartmental model. This would allow tracer administration outside the PET scanner and performing a physical stress test (Sherif et al., 2011). Dual-gated imaging (Le Meunier et al., 2010) would probably further enhance the SUV estimates.

However, SUV method is not suitable for measurement of coronary flow reserve (CRF) in rest-stress setting (Johnson & Gould, 2011).

Rest-stress studies

Coronary flow reserve can be calculated as the ratio of the MBF during the pharmacological stress (usually adenosine or dipyridamole) to the MBF at rest:

In rest-stress studies, the radioactivity that is remaining from the first study (rest) must be subtracted from the image data of the second study (stress). PET scanning in the stress study can be started shortly before tracer administration, and the concentrations in the first frame are then subtracted from every image frame (Nekolla et al., 2009). Visual scoring provides good diagnostic certainty even without subtraction (Berman et al., 2013). Lazewatsky et al. (2010) have developed a method for optimizing dose ratio and required inter-injection interval.

Woo et al. (2011) developed a method for automatic registration of rest and stress perfusion images.

Alpert et al. (2012) have developed an analysis method where the rest-stress study with two injections can be performed during a single PET session, without the assumptions that are necessary when using the subtraction method. The model instead has time varying kinetic parameters, accounting for the blood flow change induced by adenosine with a step function. The method has been validated with [18F]Flurpiridaz in a porcine model (Guehl et al., 2017a), suggesting that less than 15 min PET acquisition would be sufficient to accurately measure rest and stress blood flow. Model is also applicable for calculation of parametric images (Guehl et al., 2017b).

See also:


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Created at: 2010-11-29
Updated at: 2018-12-02
Written by: Vesa Oikonen, Harri Merisaari, Chunlei Han