This title appears in the Scientific Report :
2021
Please use the identifier:
http://hdl.handle.net/2128/27760 in citations.
Please use the identifier: http://dx.doi.org/10.2967/jnumed.120.244061 in citations.
One-Stop Shop: 18 F-Flortaucipir PET Differentiates Amyloid-Positive and -Negative Forms of Neurodegenerative Diseases
One-Stop Shop: 18 F-Flortaucipir PET Differentiates Amyloid-Positive and -Negative Forms of Neurodegenerative Diseases
Tau protein aggregations are a hallmark of amyloid-associated Alzheimer disease and some forms of non–amyloid-associated frontotemporal lobar degeneration. In recent years, several tracers for in vivo tau imaging have been under evaluation. This study investigated the ability of 18F-flortaucipir PET...
Saved in:
Personal Name(s): | Hammes, Jochen (Corresponding author) |
---|---|
Bischof, Gérard N. / Bohn, Karl P. / Onur, Özgür / Schneider, Anja / Fliessbach, Klaus / Hönig, Merle C / Jessen, Frank / Neumaier, Bernd / Drzezga, Alexander / van Eimeren, Thilo | |
Contributing Institute: |
Nuklearchemie; INM-5 Molekulare Organisation des Gehirns; INM-2 Kognitive Neurowissenschaften; INM-3 |
Published in: | Journal of nuclear medicine, 62 (2021) 2, S. 240 - 246 |
Imprint: |
New York, NY
Soc.
2021
|
DOI: |
10.2967/jnumed.120.244061 |
Document Type: |
Journal Article |
Research Program: |
Decoding Brain Organization and Dysfunction |
Link: |
Get full text OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.2967/jnumed.120.244061 in citations.
Tau protein aggregations are a hallmark of amyloid-associated Alzheimer disease and some forms of non–amyloid-associated frontotemporal lobar degeneration. In recent years, several tracers for in vivo tau imaging have been under evaluation. This study investigated the ability of 18F-flortaucipir PET not only to assess tau positivity but also to differentiate between amyloid-positive and -negative forms of neurodegeneration on the basis of different 18F-flortaucipir PET signatures. Methods: The 18F-flortaucipir PET data of 35 patients with amyloid-positive neurodegeneration, 19 patients with amyloid-negative neurodegeneration, and 17 healthy controls were included in a data-driven scaled subprofile model (SSM)/principal-component analysis (PCA) identifying spatial covariance patterns. SSM/PCA pattern expression strengths were tested for their ability to predict amyloid status in a receiver-operating-characteristic analysis and validated with a leave-one-out approach. Results: Pattern expression strengths predicted amyloid status with a sensitivity of 0.94 and a specificity of 0.83. A support vector machine classification based on pattern expression strengths in 2 different SSM/PCA components yielded a prediction accuracy of 98%. Anatomically, prediction performance was driven by parietooccipital gray matter in amyloid-positive patients versus predominant white matter binding in amyloid-negative patients. Conclusion: SSM/PCA-derived binding patterns of 18F-flortaucipir differentiate between amyloid-positive and -negative neurodegenerative diseases with high accuracy. 18F-flortaucipir PET alone may convey additional information equivalent to that from amyloid PET. Together with a perfusion-weighted early-phase acquisition (18F-FDG PET–equivalent), a single scan potentially contains comprehensive information on amyloid (A), tau (T), and neurodegeneration (N) status as required by recent biomarker classification algorithms (A/T/N). |