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 was included for 1356 PET sessions.
“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]
The Image Analysis section (page unavailable) describes quality assurance of FreeSurfer segmentation and PET uptake measures for FreeSurfer-defined regions, supporting the description of the output. It does not identify that output as PUP; the 1356-session count describes the citing authors’ dataset, not a result attributed to this source. (LLM, conf=0.78)
Experimental — accuracy not yet measuredSu et al. has demonstrated that the RSF technique was able to improve PET quantification and achieve better sensitivity to longitudinal changes in amyloid burden.
“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]
PET imaging analyses were performed using the PET unified pipeline (PUP).
“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]
Section 2.3 (Image Analysis; page unavailable) describes PET processing methods, including FreeSurfer segmentation and in-house motion-correction software, but does not identify them as the PET unified pipeline. Searches for “PET unified pipeline,” “PUP,” and “pipeline” found no passage establishing that identification. The citation is attached to PUP, not the server details later in the sentence. (LLM, conf=0.76)
Experimental — accuracy not yet measuredBoth types of PET data were partial volume corrected using a regional spread function technique.
“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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Predicting continuous amyloid PET values with CSF and plasma Aβ42/Aβ40
Wisch, J. K., Gordon, B. A., Boerwinkle, A. H., Luckett, P. H., Bollinger, J. G., Ovod, V., Li, Y., Henson, R. L., West, T., Meyer, M. R., et al. (2023) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12405 · Cited by 33 · see citing works
Self-citationAlzheimer Disease Pathology and Neurodegeneration in Midlife Obesity: A Pilot Study
Dolatshahi, M., Commean, P. K., Rahmani, F., Liu, J., Lloyd, L., Nguyen, C., Hantler, N., Ly, M. J., Yu, G. Z., Ippolito, J. E., et al. (2023) · Aging and Disease · doi:10.14336/ad.2023.0707 · Cited by 31 · see citing works
Self-citationVascular endothelial‐cadherin as a marker of endothelial injury in preclinical Alzheimer disease
Tarawneh, R. M., Kasper, R. S., Sanford, J., Phuah, C., Hassenstab, J. J., & Cruchaga, C. (2022) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51685 · Cited by 29 · see citing works
- 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
- Health Sciences › Medicine › Physiology › 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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