Appearance modeling of 11C PiB PET images: Characterizing amyloid deposition in Alzheimer's disease, mild cognitive impairment and healthy aging
Abstract
Beta-amyloid (Abeta) deposition is one of the neuropathological hallmarks of Alzheimer's disease (AD), Abeta burden can be quantified using (11)C PiB PET. Neuropathological studies have shown that the initial plaques are located in the temporal and orbitofrontal cortices, extending later to the cingulate, frontal and parietal cortices (Braak and Braak, 1997). Previous studies have shown an overlap in (11)C PiB PET retention between AD, mild cognitive impairment (MCI) patients and normal elderly control (NC) participants. It has also been shown that there is a relationship between Abeta deposition and memory impairment in MCI patients. In this paper we explored the variability seen in 15 AD, 15 MCI and 18 NC by modeling the voxel data from spatially and uptake normalized PiB images using principal component analysis. The first two principal components accounted for 80% of the variability seen in the data, providing a clear separation between AD and NC, and allowing subsequent classification. The MCI cases were distributed along an apparent axis between the AD and NC group, closely aligned with the first principal component axis. The NC cases that were PiB(+) formed a distinct cluster that was between, but separated from the AD and PiB(-) NC clusters. The PiB(+) MCI were found to cluster with the AD cases, and exhibited a similar deposition pattern. The primary principal component score was found to correlate with episodic memory scores and mini mental status examination and it was observed that by varying the first principal component, a change in amyloid deposition could be derived that is similar to the expected progression of amyloid deposition observed from post mortem studies.
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Serial amyloid PET scans show Aβ deposition starts in anterior temporal areas and spreads to frontal and medial parietal areas, associative neocortex, and later primary sensorimotor areas and subcortical regions, mirroring neuropathological staging of AD.
“Serial amyloid PET scans show that Αβ deposition starts in the anterior temporal areas and spreads to the frontal and medial parietal areas, the associative neocortex and later on at the primary sensorimotor areas and subcortical regions mirroring the neuropathological staging of AD pathology [164–166].”
From The use of neuroimaging techniques in the early and differential diagnosis of dementia (2023) · cites this paper as [164]
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“Whereas previous work focuses on the methodology of multivariate analysis for detecting dementia (Fripp et al, 2008; Habeck et al, 2008; Markiewicz et al, 2009), this work primarily investigates different data preprocessing methods to obtain optimal performance of the classification.”
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“In fact, amyloid deposition is evident in the medial prefrontal cortex of patients diagnosed with amnestic mild cognitive impairment (aMCI; Fripp et al., 2008; Pike et al., 2007), a diagnostic category that typically precedes AD (Petersen, 2004).”
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“…that can be generated with or without the aid of a MRI scan (Acosta et al., 2012; Fripp et al., 2008b) leading to automatic quantifi cation of A β imaging scans (Raniga et al., 2008) or using appearance models for the characterization of A β deposition in the AIBL cohort (Fripp et al., 2008a).”
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“PCA has been used before for characterizing voxel data with C PiB PET images on Alzheimer’s disease (AD) patients [17], or with Fluorodeoxyglucose (F ) PET images to classify fronto temporal dementia and AD [18].”
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Self-citationEvaluation of in vivo staging of amyloid deposition in cognitively unimpaired elderly aged 78–94
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“This has previously been used to study the effects of ageing on cerebral glucose metabolism [16], to distinguish between dementia types [17], with amyloid-PET for discrimination between AD patients and controls [18] or for generating templates for spatial processing [19].”
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“For instance, PCA has been performed for feature extraction and dimensionality reduction in the identification of Alzheimer’s disease [24] using positron emission tomography images.”
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Self-citationClinical applications of PET amyloid imaging: an update
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- Authors
- Fripp, J., Bourgeat, P., Acosta, O., Raniga, P., Modat, M., Pike, K. E., Jones, G., O'Keefe, G., Masters, C. L., Ames, D., Ellis, K. A., Maruff, P., Currie, J., Villemagne, V. L., Rowe, C. C., Salvado, O., & Ourselin, S.
- Affiliations
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Mental Health Research Institute (AU)
- The University of Melbourne (AU)
- National Ageing Research Institute (AU)
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2008-11
- Volume
- 43
- Issue
- 3
- Pages
- 430-439
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2126757998
- Cited by
- 80
- References
- 0
- Citations by year
- 2024: 1 · 2023: 2 · 2022: 2 · 2020: 6 · 2019: 4 · 2018: 5 · 2017: 4 · 2016: 2 · 2015: 5 · 2014: 5 · 2013: 5 · 2012: 5
- FWCI
- 7.95
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Commonwealth Scientific and Industrial Research Organisation
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Keywords
- 11C-PiB PET, amyloid-beta deposition, Alzheimer's disease, mild cognitive impairment, healthy aging, appearance modeling, principal component analysis, episodic memory
- MeSH terms
- Aged, Aging, Alzheimer Disease, Amyloid, Aniline Compounds, Brain, Carbon Radioisotopes, Cognition Disorders, Female, Humans, Image Processing, Computer-Assisted, Male, Models, Neurological, Neuropsychological Tests, Thiazoles, Radiopharmaceuticals, Principal Component Analysis, Positron-Emission Tomography, Benzothiazoles
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