Investigating the impact of scatter correction on Centiloid. (31st December 2021)

• Record Type: Journal Article
• Authors: Li, Shenpeng; O'Keefe, Graeme; Gillman, Ashley; Burnham, Samantha C; Masters, Colin L; Williams, Robert; Rowe, Christopher C; Fripp, Jurgen; Bourgeat, Pierrick; Villemagne, Victor L; Dore, Vincent
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 1
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.053822
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Centiloid (CL) is a semiquantitative measure of amyloid‐β burden based on the ratio between neo‐cortical target region and the whole cerebellum. Photon scatter is one of the major sources of noise in PET data. Scatter correction methods are very different across PET cameras. In this study, we investigate how scatter correction affects the CL for inter/intra‐cameras by comparing PET images with/without scatter correction. Method: 203 subjects (Siemens mCT Biography (N=109), Philips Gemini TF 64 (N=94)) from the AIBL study were scanned with 18F‐NAV6240. All PET images were reconstructed off‐line with scatter correction enabled and then disabled. All images were processed by CapAIBL to generate CL values. The ΔCL, which was calculated as the difference between the scatter corrected CL and non‐scatter corrected CL, was investigated to quantify the impact of scatter correction. For the intra‐camera comparison, all subjects were categorised in three groups based on the head tilt along anteroposterior axis compared to the MNI‐152 template. For inter‐camera comparison, the head tilt angle was included as covariate into an ANOVA. Hierarchical linear regressions that included head tilt and camera models were used as covariates to investigate their effect on CL. Result: Figure 1 shows that scatter correction has a larger impact on the cerebellum cortex than in neocortex. Figure 2 shows that scatter correction depends on the head position, and it has more impact on subjects with higher CL for both cameras. Figure 3 presents that scatter corrections from two different cameras have different impact on CL values. Both head tilt and camera model had an impact on the scatter correction with (F=19.5, p=1.67e‐5) and (F=109.4, p=1.1e‐20), respectively. The b coefficients were 0.38CL/degree for head tilt and 8.2CL for the camera model, where more scatter is corrected on the Siemens CT than on the Philips Gemini TF. Conclusion: Our results show that difference in scatter correction from different cameras have a significant impact on CL, it is yet to be known whether it is caused by hardware difference or software difference. Additional investigations using test‐retest data is needed to further characterize the real impact of scatter correction on Centiloid.