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Partial volume correction in quantitative amyloid imaging
Open accessAbstract
Amyloid imaging is a valuable tool for research and diagnosis in dementing disorders. As positron emission tomography (PET) scanners have limited spatial resolution, measured signals are distorted by partial volume effects. Various techniques have been proposed for correcting partial volume effects, but there is no consensus as to whether these techniques are necessary in amyloid imaging, and, if so, how they should be implemented. We evaluated a two-component partial volume correction technique and a regional spread function technique using both simulated and human Pittsburgh compound B (PiB) PET imaging data. Both correction techniques compensated for partial volume effects and yielded improved detection of subtle changes in PiB retention. However, the regional spread function technique was more accurate in application to simulated data. Because PiB retention estimates depend on the correction technique, standardization is necessary to compare results across groups. Partial volume correction has sometimes been avoided because it increases the sensitivity to inaccuracy in image registration and segmentation. However, our results indicate that appropriate PVC may enhance our ability to detect changes in amyloid deposition.
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“Quality control reviewed post-processing PUP output 42,43 , which includes uptake measure for FreeSurfer-based regions, was included for 1356 PET sessions.”
From OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer Disease (2019) · cites this paper as [42]
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“Su et al. 42,49 has demonstrated that the RSF technique was able to improve PET quantification and achieve better sensitivity to longitudinal changes in amyloid burden.”
From OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer Disease (2019) · cites this paper as [42]
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“PET imaging analyses were performed using the PET unified pipeline 42,43 (PUP, https://github.com/ysu001/PUP) via XNAT on Dell PowerEdge 1950 servers with Intel Xeon processors running CentOS 5.5 Linux.”
From OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer Disease (2019) · cites this paper as [42]
Experimental — accuracy not yet measuredIn the citing paper
“Both types of PET data were partial volume corrected using a regional spread function technique27,28.”
From Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study (2018) · cites this paper as [27]
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Self-citationA Novel Hybrid Ordinal Learning Model With Health Care Application
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Self-citationNeitzel, J., Nuttall, R., & Sorg, C. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00026 · Cited by 7
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Metadata
- Authors
- Su, Y., Blazey, T. M., Snyder, A. Z., Raichle, M. E., Marcus, D. S., Ances, B. M., Bateman, R. J., Cairns, N. J., Aldea, P., Cash, L., Christensen, J. J., Friedrichsen, K., Hornbeck, R. C., Farrar, A. M., Owen, C. J., Mayeux, R., Brickman, A. M., Klunk, W., Price, J. C., Thompson, P. M., Ghetti, B., Saykin, A. J., Sperling, R. A., Johnson, K. A., Schofield, P. R., Buckles, V., Morris, J. C., & Benzinger, T. L. S.
- Affiliations
- Washington University in St. Louis (US)
- Columbia University Irving Medical Center (US)
- University of Pittsburgh (US)
- University of Southern California (US)
- Indiana University School of Medicine (US)
- Indiana University Indianapolis (US)
- Harvard University (US)
- UNSW Sydney (AU)
- Corresponding author
- Su, Yi
- ORCID
- Su, Yi
- Blazey, Tyler M.
- Snyder, Abraham Z.
- Raichle, Marcus E.
- Marcus, Daniel S.
- Ances, Beau M.
- Bateman, Randall J.
- Cairns, Nigel J.
- Friedrichsen, Karl
- Hornbeck, Russ C.
- Mayeux, Richard
- Brickman, Adam M.
- Klunk, William
- Price, Julie C.
- Thompson, Paul M.
- Saykin, Andrew J.
- Sperling, Reisa A.
- Johnson, Keith A.
- Schofield, Peter R.
- Morris, John C.
- Benzinger, Tammie L.S.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2015-02
- Volume
- 107
- Pages
- 55-64
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4300252
- OpenAlex
- W1977541817
- Semantic Scholar
- 77ada80d1d7d2ece501b4ca861e835ea5129a4f1
- Cited by
- 247
- References
- 49
- Citations by year
- 2026: 16 · 2025: 21 · 2024: 21 · 2023: 26 · 2022: 34 · 2021: 22 · 2020: 27 · 2019: 14 · 2018: 24 · 2017: 11 · 2016: 22 · 2015: 8
- FWCI
- 10.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- IUScholarWorks (Indiana University) (submittedVersion)
- Funders
- Knight Alzheimer's Disease Research Center (P50AG005681, P01AG003991, P01AG026276, U19AG032438, P30NS048056)
- Charles F. and Joanne Knight Alzheimer's Initiative
- David and Betty Farrell Medical Research Fund
- F Simmons
- O Mohan
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Keywords
- partial volume correction, amyloid imaging, Pittsburgh compound B, PET, amyloid deposition, image registration, image segmentation, dementing disorders
- MeSH terms
- Algorithms, Alzheimer Disease, Amyloid, Aniline Compounds, Cerebral Cortex, Computer Simulation, Cross-Sectional Studies, Humans, Individuality, Longitudinal Studies, Thiazoles, Reproducibility of Results, Cohort Studies, Amyloid Neuropathies, Radiopharmaceuticals, Positron-Emission Tomography, Benzothiazoles
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