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Voxel-based NK1 Receptor Occupancy Measurements with [18F]SPA-RQ and Positron Emission Tomography: A Procedure for Assessing Errors from Image Reconstruction and Physiological Modeling

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Abstract

Purpose

Receptor occupancy studies with positron emission tomography (PET) are widely used as aids in the drug development process. This study introduces a general procedure for assessing errors that arise from the applied image processing methods in PET receptor occupancy studies using the neurokinin-1 (NK1) receptor occupancy study as an example.

Procedures

The bias and variance among eight combinations of image reconstruction and model calculation methods for estimating voxel-level receptor occupancy results were examined. The tests were performed using a dynamic numerical phantom based on a previous PET drug occupancy study with the NK1 receptor antagonist tracer [18F]SPA-RQ.

Results

The simplified reference tissue model with basis functions (SRTM BF) was best at estimating receptor occupancy in terms of average bias. On the other hand, median root prior (MRP) image reconstruction produced the lowest variances in the occupancy estimates. These results suggest that SRTM BF and MRP is, in this case, the combination of choice in voxel-based receptor occupancy calculation. In the calculation of regional binding potential values, the commonly used sample mean is not applicable and, e.g., the median could be used instead.

Conclusions

This study shows that even this kind of complicated receptor study can be statistically evaluated. The reconstruction methods had an effect on the variance in the voxel-based receptor occupancy calculation. The model calculation methods influenced the average bias. The test method was found useful in assessing the methodological sources of systematic and random error in receptor occupancy estimation with PET.

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Acknowledgments

Financial support from Tampere Graduate School for Information Science and Engineering; the National Technology Agency of Finland (Tekes) Drug2000 technology program; and the Academy of Finland, project no. 213462 [Finnish Centre of Excellence program (2006-2011)] is gratefully acknowledged. The authors thank Johanna Eskola, Heidi Koivistoinen, Sakari Alenius, and Anu Juslin for their work during the preparation of this paper, as well as Merck & Co. for access to the NK1 receptor occupancy data set.

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Correspondence to Esa Wallius.

Appendix

Appendix

The test channel (cf. Fig. 1) for assessing the errors caused by the methods in receptor occupancy studies as pseudocode. The numbers in parentheses correspond to the number of phantom realizations and methods applied in the present study.

  • For baseline (1) and each pharmaceutical dose level (3)

    • Virtual radioactivity distribution is created on the basis of time–radioactivity curves

    • The virtual radioactivity distribution is forward projected to sinograms

      • For each noise realization (corresponding individual PET studies) (30)

        • Noise is added to sinograms according to a noise model

        • For every reconstruction method (2)

          • The sinograms are reconstructed to dynamic images

            • For each model calculation method (4)

              • Reference region radioactivity concentrations are extracted

              • Binding potential images are calculated using the reference region

              • Receptor occupancy values are calculated in regions of interest from BP images (3 × 30 × 2 × 4 = 720)

            • until computations for all model calculation methods have been performed

        • until images for each reconstruction method have been made

    • until every noise realization has been performed

  • until all dose levels have been covered

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Wallius, E., Nyman, M., Oikonen, V. et al. Voxel-based NK1 Receptor Occupancy Measurements with [18F]SPA-RQ and Positron Emission Tomography: A Procedure for Assessing Errors from Image Reconstruction and Physiological Modeling. Mol Imaging Biol 9, 284–294 (2007). https://doi.org/10.1007/s11307-007-0096-1

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