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Multitracer model for staging cortical amyloid deposition using PET imaging.
Lyduine E Collij1, Fiona Heeman1, Gemma Salvadó1
1From Department of Radiology and Nuclear Medicine (L.E.C., F.H., S.I., M.Y., S.S.V.G., V.W., A.M.W., A.A.L., R.B., B.N.M.v.B., F.B., I.L.A.), Neurochemistry Laboratory (C.E.T.), Alzheimer Center (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), and Department of Neurology (D.A., A.d.W., E.K., M.v.B., P.J.V., P.S., W.M.v.d.F.), Amsterdam UMC, Vrije Universiteit Amsterdam, Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation (G.S., J.L.M., J.D.G.), Barcelona; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (J.D.G.); Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (J.L.M.), Madrid; IMIM (Hospital del Mar Medical Research Institute) (G.S., J.L.M., J.D.G.), Barcelona; Universitat Pompeu Fabra (J.L.M., J.D.G.), Barcelona, Spain; Laboratory of Neuroimaging of Aging (D.A.), University of Geneva; Memory Clinic (D.A.), University Hospital of Geneva, Switzerland; Centre for Medical Image Computing (P.M., F.B.), Medical Physics and Biomedical Engineering, University College London, London, UK; and Janssen Pharmaceutica NV (M.E.S.), Beerse, Belgium.
A new staging model for cortical amyloid deposition was developed using PET scans. This model accurately classifies amyloid burden and predicts cognitive decline in over 3,000 individuals across multiple cohorts.
Area of Science:
- Neuroimaging
- Neurology
- Biomarkers
Background:
- Alzheimer's disease (AD) diagnosis relies on identifying amyloid-beta (Aβ) plaques.
- Positron Emission Tomography (PET) imaging is crucial for visualizing Aβ deposition.
- Standardized staging models are needed for consistent assessment across diverse populations and PET tracers.
Purpose of the Study:
- To develop and validate a generalizable model for staging cortical amyloid deposition using PET.
- To assess the model's ability to correlate amyloid burden with cognitive decline.
- To establish a robust staging system applicable across multiple cohorts and radiotracers.
Main Methods:
- Retrospective analysis of 3,027 individuals from 6 cohorts undergoing amyloid PET scans.
- Development of a pooled multitracer regional ranking based on Standardized Uptake Value Ratio (SUVr) abnormality in 400 cognitively unimpaired individuals.
- Creation of a 4-cluster staging model using the pooled ranking and investigation of its relationship with clinical variables and cognitive decline.
Main Results:
- A 4-stage model was developed, classifying amyloid burden from 0% to 100% across stages.
- Higher amyloid stages significantly predicted Mini-Mental State Examination (MMSE) score decline and faster progression to MMSE ≤25.
- The model demonstrated high correlation across single-tracer rankings and consistent performance across cohorts.
Conclusions:
- The developed pooled multitracer staging model effectively classifies amyloid burden in a large, diverse population.
- The model identifies pre-global amyloid burden and distinct cognitive decline risk profiles.
- This staging system offers a generalizable tool for assessing amyloid deposition and its clinical impact.
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