Reducing between scanner differences in multi-center PET studies

Abstract

This work is part of the multi-center Alzheimer's Disease Neuroimaging Initiative (ADNI), a large multi-site study of dementia, including patients having mild cognitive impairment (MCI), probable Alzheimer's disease (AD), as well as healthy elderly controls. A major portion of ADNI involves the use of [(18)F]-fluorodeoxyglucose (FDG) with positron emission tomography (PET). The objective of this paper is the reduction of inter-scanner differences in the FDG-PET scans obtained from the 50 participating PET centers having fifteen different scanner models. In spite of a standardized imaging protocol, systematic inter-scanner variability in PET images from various sites is observed primarily due to differences in scanner resolution, reconstruction techniques, and different implementations of scatter and attenuation corrections. Two correction steps were developed by comparison of 3-D Hoffman brain phantom scans with the 'gold standard' digital 3-D Hoffman brain phantom: i) high frequency correction; where a smoothing kernel for each scanner model was estimated to smooth all images to a common resolution and ii) low frequency correction; where smooth affine correction factors were obtained to reduce the attenuation and scatter correction errors. For the phantom data, the high frequency correction reduced the variability by 20%-50% and the low frequency correction further reduced the differences by another 20%-25%. Correction factors obtained from phantom studies were applied to 95 scans from normal control subjects obtained from the participating sites. The high frequency correction reduced differences similar to the phantom studies. However, the low frequency correction did not further reduce differences; hence further refinement of the procedure is necessary.

Figure 1

Three levels in the Hoffman brain phantom scans for 5 different scanner models pre- and post- high frequency corrections.

Figure 2

Low frequency correction factors for simulations of images with residual attenuation error alone. Panels A and B show the multiplicative and additive correction factors. Panel C shows a sample profile through the 3-D correction factors. Panel D shows the same profile through the true, uncorrected, and corrected digital phantom images.

Figure 3

Low frequency correction factors for simulations of images with residual scatter error alone. Panels A and B show the multiplicative and additive correction factors. Panel C shows a sample profile through the 3-D correction factors. Panel D shows the same profile through the true, uncorrected, and corrected digital phantom images.

Figure 4

Reduction in average between-scanner RMSE for Hoffman phantom scans. Correction factors derived from the phantom data are applied to the phantom data itself.

Figure 5

Reduction in average between-subject RMSE for normal control FDG PET scans. Correction factors derived from the phantom data are applied to normal control scans.