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• W3133730557 startingPage "e0248122" @default.
• W3133730557 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." @default.
• W3133730557 created "2021-03-15" @default.
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• W3133730557 date "2021-03-05" @default.
• W3133730557 modified "2023-10-18" @default.
• W3133730557 title "Amyloid burden quantification depends on PET and MR image processing methodology" @default.
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• W3133730557 doi "https://doi.org/10.1371/journal.pone.0248122" @default.
• W3133730557 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7935288" @default.
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• W3133730557 hasPublicationYear "2021" @default.
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