Amyloid burden quantification depends on PET and MR image processing methodology

Abstract

Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer’s Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study’s goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines.

Longitudinal amyloid and tau PET imaging in Alzheimer's disease: A systematic review of methodologies and factors affecting quantification

“…However, Kolinger et al compared the impact of the reference space for analysis on the SUVr and found no significant difference between native and standard space, but any image feature using volumetric information should be performed in native space. 184 With the increasing availability of longitudinal registration pipelines for structural MRI, a few studies have begun to implement them into longitudinal analysis of amyloid and tau PET data. 26,39,54,66,185 Longitudinal registration pipelines are available in SPM, 179 FreeSurfer, 16 and ANTs.…”

Quantification of amyloid PET for future clinical use: a state-of-the-art review

“…However, accurate measurement and cut-off values are highly dependent on the chosen tracer, reference region (Fig. 2 ), and delineation method [ 74 , 129 , 130 ], which challenges the pooling of multi-centre SUVr data across tracers [ 131 ]. In addition, there is high variability in longitudinal results [ 93 , 132 ], which limits the power in detecting genuine biological differences.…”

Pursuit of precision medicine: Systems biology approaches in Alzheimer's disease mouse models

“…To combat this, the field is pushing towards standardization of imaging acquisition and processing methods ( Mueller et al, 2005 ; Whitesell et al, 2019 ). Even when using identical mouse models and similar imaging approaches, independent labs can achieve varying results for measures like rate of amyloid plaque accumulation or regional levels of atrophy ( Kolinger et al, 2021 ; Mannheim et al, 2018 ; Morbelli and Bauckneht, 2018 ; Osborne et al, 2017 ). This lack of consistency makes it difficult to combine and compare results, and for these reasons, all processing parameters should be disclosed to promote reproducibility ( Eisenstein, 2020 ).…”