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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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.
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.
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.
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.
Key wordsBias Variance Root mean squared error Receptor occupancy PET
- 18.Morcuende S, Harris EA, Sheasby A, et al. (2002) Adult neurogenesis is increased in the hippocampus of NK1 receptor knock-out mice. In: Abstracts in the 32nd SFN Annual Meeting, Orlando, 2–7 November 2002Google Scholar
- 23.Nyman MJ, Eskola O, Kajander J, et al. (2007) Gender and age affect NK1 receptors in the human brain—a positron emission tomography study with [18F]SPA-RQ. Int J Neuropsychopharmacol 10:219–229Google Scholar
- 31.Jain A (1989) Fundamentals of digital image processing. Englewood Cliffs, NJ: Prentice-Hall InternationalGoogle Scholar
- 38.Yavuz M, Fessler JA (1997) New statistical models for randoms-precorrected PET scans. In: Duncan J, Gindi G (eds) Information processing in medical imaging, lecture notes in computer science, vol 1230. Berlin Heidelberg New York: Springer, pp 190–203Google Scholar
- 42.Sederholm K (2004) Study on basis function methods reliance on θ3 parameter limits. Turku PET centre modelling report. http://www.turkupetcentre.net/reports/tpcmod0028.pdf. Cited 26 August 2006.
- 43.Sederholm K (2004) Study on basis function methods reliance on θ3 parameter limits—phantom study. Turku PET centre modelling report. http://www.turkupetcentre.net/reports/private/tpcmod0028_app_b.pdf. Cited 26 August 2006.
- 45.Sederholm K, Oikonen V, Hietala J (2004) Generation of parametric receptor binding potential images—comparing performance of basis function method, multilinear method and graphical analysis. Eur J Nucl Med Mol Imaging 31(Suppl 2):s407 (Abstract)Google Scholar