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. 2018 Jul 3;8(1):58.
doi: 10.1186/s13550-018-0412-6.

Non-invasive kinetic modelling of PET tracers with radiometabolites using a constrained simultaneous estimation method: evaluation with 11C-SB201745

Hasan Sari  1 , Kjell Erlandsson  2 , Lisbeth Marner  3   4 , Ian Law  4 , Henrik B W Larsson  4 , Kris Thielemans  2 , Sébastien Ourselin  5 , Simon Arridge  5 , David Atkinson  6 , Brian F Hutton  2   7
Affiliations

Non-invasive kinetic modelling of PET tracers with radiometabolites using a constrained simultaneous estimation method: evaluation with 11C-SB201745

Hasan Sari et al. EJNMMI Res. .

Abstract

Background: Kinetic analysis of dynamic PET data requires an accurate knowledge of available PET tracer concentration within blood plasma over time, known as the arterial input function (AIF). The gold standard method used to measure the AIF requires serial arterial blood sampling over the course of the PET scan, which is an invasive procedure and makes this method less practical in clinical settings. Traditional image-derived methods are limited to specific tracers and are not accurate if metabolites are present in the plasma.

Results: In this work, we utilise an image-derived whole blood curve measurement to reduce the computational complexity of the simultaneous estimation method (SIME), which is capable of estimating the AIF directly from tissue time activity curves (TACs). This method was applied to data obtained from a serotonin receptor study (11C-SB207145) and estimated parameter results are compared to results obtained using the original SIME and gold standard AIFs derived from arterial samples. Reproducibility of the method was assessed using test-retest data. It was shown that the incorporation of image-derived information increased the accuracy of total volume of distribution (V T) estimates, averaged across all regions, by 40% and non-displaceable binding potential (BP ND) estimates by 16% compared to the original SIME. Particular improvements were observed in K1 parameter estimates. BP ND estimates, based on the proposed method and the gold standard arterial sample-derived AIF, were not significantly different (P=0.7).

Conclusions: The results of this work indicate that the proposed method with prior AIF information obtained from a partial volume corrected image-derived whole blood curve, and modelled parent fraction, has the potential to be used as an alternative non-invasive method to perform kinetic analysis of tracers with metabolite products.

Keywords: Arterial input function; Kinetic modelling; PET/MR; Positron emission tomography.

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Conflict of interest statement

Ethics approval and consent to participate

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Ethics Committee for Copenhagen and Frederiksberg ((KfF)01-274821). Informed consent was obtained from all individual participants included in the study.

Consent for publication

All patients included gave written informed consent that their data could be used for scientific purposes.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Constrained SIME model used in the analysis. CP represents the AIF, CF represents the free state and CB of the 2-TC model. The CP was modelled as a product of plasma to whole blood ratio and the Hill function. Three parameters of the Hill function (a, b, c) and two parameters of the straight line function (d, e) were optimised simultaneously by fitting N (where N=4) TACs extracted from different brain regions. CWB is derived from PV-corrected PET images. TACs derived from the cerebellum, parietal cortex, hippocampus and striatum from one subject are shown on the right
Fig. 2
Fig. 2
Comparison of image-derived and arterial blood sample-derived whole blood curves for one subject plotted together with the metabolite-free parent AIF derived from blood samples. The x-axis is set to log scale to display curve peaks and tails clearly
Fig. 3
Fig. 3
TACs from one subject with simultaneously fitted curves using SIME constrained modelling
Fig. 4
Fig. 4
Average of the parent fractions estimated using the SIME constrained plotted together with average of parent fractions derived from plasma samples. Error bars represent the variation between estimated and measured parent fraction curves from 10 datasets
Fig. 5
Fig. 5
AIFs derived using SIME original, SIME constrained and AIF samples plotted together for one subject. The x-axis is set to log scale to display curve peaks and tails clearly
Fig. 6
Fig. 6
V T estimated for four brain regions using the AIFs estimated from AIF samples, SIME original and SIME constrained. The bars represent the V T values estimated across 10 studies and error bars represent the standard deviation
Fig. 7
Fig. 7
K1 estimated for four brain regions using the AIFs estimated from AIF samples, SIME original and SIME constrained. The bars represent the K1 values estimated across 10 studies and error bars represent the standard deviation
Fig. 8
Fig. 8
a V T and b BP ND estimated using SIME constrained compared to V T and BP ND determined by AIF from arterial samples. Results from each scan are shown per each ROI. A linear function was fitted to the data points and plotted together with the line of identity
Fig. 9
Fig. 9
Intraclass correlation coefficient (ICC) scores of the V T estimates obtained using AIF samples, SIME original and SIME constrained. + 1 represents maximum reliability whereas − 1 represents minimum reliability
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