Existing Pittsburgh Compound-B positron emission tomography thresholds are too high: statistical and pathological evaluation
Open accessAbstract
Amyloid-β, a hallmark of Alzheimer's disease, begins accumulating up to two decades before the onset of dementia, and can be detected in vivo applying amyloid-β positron emission tomography tracers such as carbon-11-labelled Pittsburgh compound-B. A variety of thresholds have been applied in the literature to define Pittsburgh compound-B positron emission tomography positivity, but the ability of these thresholds to detect early amyloid-β deposition is unknown, and validation studies comparing Pittsburgh compound-B thresholds to post-mortem amyloid burden are lacking. In this study we first derived thresholds for amyloid positron emission tomography positivity using Pittsburgh compound-B positron emission tomography in 154 cognitively normal older adults with four complementary approaches: (i) reference values from a young control group aged between 20 and 30 years; (ii) a Gaussian mixture model that assigned each subject a probability of being amyloid-β-positive or amyloid-β-negative based on Pittsburgh compound-B index uptake; (iii) a k-means cluster approach that clustered subjects into amyloid-β-positive or amyloid-β-negative based on Pittsburgh compound-B uptake in different brain regions (features); and (iv) an iterative voxel-based analysis that further explored the spatial pattern of early amyloid-β positron emission tomography signal. Next, we tested the sensitivity and specificity of the derived thresholds in 50 individuals who underwent Pittsburgh compound-B positron emission tomography during life and brain autopsy (mean time positron emission tomography to autopsy 3.1 ± 1.8 years). Amyloid at autopsy was classified using Consortium to Establish a Registry for Alzheimer's Disease (CERAD) criteria, unadjusted for age. The analytic approaches yielded low thresholds (standard uptake value ratiolow = 1.21, distribution volume ratiolow = 1.08) that represent the earliest detectable Pittsburgh compound-B signal, as well as high thresholds (standard uptake value ratiohigh = 1.40, distribution volume ratiohigh = 1.20) that are more conservative in defining Pittsburgh compound-B positron emission tomography positivity. In voxel-wise contrasts, elevated Pittsburgh compound-B retention was first noted in the medial frontal cortex, then the precuneus, lateral frontal and parietal lobes, and finally the lateral temporal lobe. When compared to post-mortem amyloid burden, low proposed thresholds were more sensitive than high thresholds (sensitivities: distribution volume ratiolow 81.0%, standard uptake value ratiolow 83.3%; distribution volume ratiohigh 61.9%, standard uptake value ratiohigh 62.5%) for CERAD moderate-to-frequent neuritic plaques, with similar specificity (distribution volume ratiolow 95.8%; standard uptake value ratiolow, distribution volume ratiohigh and standard uptake value ratiohigh 100.0%). A receiver operator characteristic analysis identified optimal distribution volume ratio (1.06) and standard uptake value ratio (1.20) thresholds that were nearly identical to the a priori distribution volume ratiolow and standard uptake value ratiolow. In summary, we found that frequently applied thresholds for Pittsburgh compound-B positivity (typically at or above distribution volume ratiohigh and standard uptake value ratiohigh) are overly stringent in defining amyloid positivity. Lower thresholds in this study resulted in higher sensitivity while not compromising specificity.
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For amyloid imaging, different ligands, methods of image acquisition, and image processing can result in different thresholds when compared to neuropathologic standards.
“For amyloid imaging, where over a decade of data are available, different ligands, methods of image acquisition, and image processing can result in different thresholds when compared to neuropathologic standards [21,22,196].”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [196]
In a subanalysis of a study aimed to identify different Aβ PET cut-offs, the first significant SUVR differences between controls and a group with sub-threshold SUVRs were located in the medial frontal cortex and the precuneus, similar to our early Aβ regions.
“They found that the first significant SUVR differences between the controls and a group with sub-threshold SUVRs were located in the medial frontal cortex and the precuneus, similar to our early Aβ regions.”
From Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity (2017) · cites this paper as [17]
Mixture modeling provides an unbiased threshold for abnormality and is a well-established method for defining Aβ PET cut-offs.
“Mixture modeling statistics provide an unbiased threshold for abnormality (i.e., the diagnosis or status is not used in analysis) and it is a well-established method for defining Aβ PET cut-offs12, 17, 60, 61.”
From Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity (2017) · cites this paper as [17]
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Ciampa, C. J., Parent, J. H., Harrison, T. M., Fain, R. M., Betts, M. J., Maass, A., Winer, J. R., Baker, S. L., Janabi, M., Furman, D. J., et al. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-022-01269-6 · Cited by 54 · see citing works
Self-citationWhite matter hyperintensities are associated with subthreshold amyloid accumulation
Moscoso, A., Rey-Bretal, D., Silva-Rodríguez, J., Aldrey, J. M., Cortés, J., Pías-Peleteiro, J., Ruibal, Á., & Aguiar, P. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116944 · Cited by 49 · see citing works
“In this regard, our results also emphasize the need to rede fi ne current amyloid PET cut-points to capture early amyloid pathology, as other studies have pointed out (Villeneuve et al., 2015).”
Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults
ten Kate, M., Visser, P. J., Bakardjian, H., Barkhof, F., Sikkes, S. A. M., van der Flier, W. M., Scheltens, P., Hampel, H., Habert, M.-O., Dubois, B., et al. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00067 · Cited by 41 · see citing works
Asken, B. M., Tanner, J. A., VandeVrede, L., Mantyh, W. G., Casaletto, K. B., Staffaroni, A. M., La Joie, R., Iaccarino, L., Soleimani-Meigooni, D., Rojas, J. C., et al. (2022) · Neurology · doi:10.1212/wnl.0000000000200678 · Cited by 40 · see citing works
Self-citationSmith, G. S., Protas, H., Kuwabara, H., Savonenko, A., Nassery, N., Gould, N. F., Kraut, M., Avramopoulos, D., Holt, D., Dannals, R. F., et al. (2023) · NeuroImage: Clinical · doi:10.1016/j.nicl.2023.103322 · Cited by 22 · see citing works
Liu, A. J., Staffaroni, A. M., Rojas-Martinez, J. C., Olney, N. T., Alquezar-Burillo, C., Ljubenkov, P. A., La Joie, R., Fong, J. C., Taylor, J., Karydas, A., et al. (2020) · JAMA Neurology · doi:10.1001/jamaneurol.2019.4284 · Cited by 18 · see citing works
“Repetitive behaviors 5/16 (31) 6/15 (40) 0/16”
Self-citation
- Authors
- Villeneuve, S., Rabinovici, G. D., Cohn-Sheehy, B. I., Madison, C., Ayakta, N., Ghosh, P. M., La Joie, R., Arthur-Bentil, S. K., Vogel, J. W., Marks, S. M., Lehmann, M., Rosen, H. J., Reed, B., Olichney, J., Boxer, A. L., Miller, B. L., Borys, E., Jin, L.-W., Huang, E. J., Grinberg, L. T., DeCarli, C., Seeley, W. W., & Jagust, W.
- Affiliations
- University of California, Berkeley (US)
- Lawrence Berkeley National Laboratory (US)
- University of California, San Francisco (US)
- VA Northern California Health Care System (US)
- University of California, Davis (US)
- Loyola University Chicago (US)
- ORCID
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-05-06
- Volume
- 138
- Issue
- 7
- Pages
- 2020-2033
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- PMC
- PMC4806716
- OpenAlex
- W2174753847
- Cited by
- 408
- References
- 16
- Citations by year
- 2026: 20 · 2025: 36 · 2024: 40 · 2023: 36 · 2022: 40 · 2021: 44 · 2020: 49 · 2019: 46 · 2018: 32 · 2017: 40 · 2016: 21 · 2015: 4
- FWCI
- 26.27
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Brain (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Hellman Family Foundation
- Tau Consortium
- Canadian Institutes of Health Research
- National Institute on Aging (P01AG 12435, P30AG10129, P30AG010129, R01AG021028, R01AG045611, P01 AG1972403, R01AG032306, P01AG003991, K23AG031861, K24AG045333, R01AG038791, P01AG012435, P01AG019724, R01AG034570, R01AG031563, P50AG023501)
- National Institute of Neurological Disorders and Stroke (U54NS092089)
- 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
- Pittsburgh compound B, amyloid PET, Alzheimer's disease, amyloid burden, sensitivity and specificity, Gaussian mixture model, K-means clustering, voxel-based analysis, medial frontal cortex, precuneus, lateral temporal lobe, cognitively normal older adults
- MeSH terms
- Aged, Alzheimer Disease, Aniline Compounds, Female, Humans, Image Interpretation, Computer-Assisted, Male, Reference Values, Thiazoles, Amyloid beta-Peptides, Radiopharmaceuticals, Positron-Emission Tomography, Young Adult
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