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Title
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Amyloid burden quantification depends on PET and MR image processing methodology
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Author
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Abstract
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| 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. |
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Language
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English
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Source (journal)
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PLoS ONE
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Publication
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2021
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ISSN
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1932-6203
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DOI
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10.1371/JOURNAL.PONE.0248122
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Volume/pages
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16
:3
(2021)
, 19 p.
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Article Reference
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e0248122
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ISI
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000626604300023
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Pubmed ID
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33667281
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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