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Updated: Nov 15, 2025
Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451
Published on: April 18, 2025
Amyloid burden quantification depends on PET and MR image processing methodology
Guilherme D Kolinger1, David Vállez García1, Antoon T M Willemsen1
1Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
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.
Insights
Image processing methods significantly impact Alzheimer's Disease amyloid quantification. Intensity-based metrics are robust, while volumetric measures require careful processing in Native Space for reliable results.
Area of Science:
- Neuroimaging
- Biomarkers
- Alzheimer's Disease Research
Background:
- Positron emission tomography (PET) enables in-vivo quantification of amyloid load, crucial for Alzheimer's Disease (AD) assessment.
- Image processing methodologies can introduce variability, potentially affecting the accuracy of amyloid quantification in AD.
- Standardized and robust quantification methods are essential for reliable clinical assessment and research in AD.
Purpose of the Study:
- To investigate the influence of different semi-automatic image processing pipelines on amyloid quantification in AD.
- To compare the impact of various spatial normalization techniques and grey matter segmentation strategies on quantification metrics.
- To identify processing pipelines that yield robust and reproducible amyloid load measurements for AD assessment.
Main Methods:
- Analysis of PET images in Native Space and Standard Space using non-rigid spatial transformations.
- Exploration of maximum a posteriori (MAP) approaches and tissue probability maps (TPM) for regularization.
- Evaluation of grey matter segmentation performed before and after spatial normalization, and using a population-based template.
- Assessment of five quantification metrics: two intensity-based, two volumetric-based, and one multi-parametric feature.
Main Results:
- Intensity-based metrics showed minimal impact (≤10%) from spatial normalization and segmentation methods, comparable to test-retest variability.
- Volumetric and multi-parametric features exhibited significant sensitivity to image processing, with variability up to 45%.
- Analysis in Native Space without non-rigid transformations was recommended for volumetric measurements.
Conclusions:
- Image processing methodology significantly influences amyloid quantification, particularly for volumetric and multi-parametric metrics.
- Intensity-based metrics offer greater robustness against variations in image processing pipelines.
- For Standard Space analysis, spatial normalization regularized by TPM is preferred; volumetric measurements are best performed in Native Space.
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