Data‐driven approaches for tau‐PET imaging biomarkers in Alzheimer's disease

Previous positron emission tomography (PET) studies have quantified filamentous tau pathology using regions‐of‐interest (ROIs) based on observations of the topographical distribution of neurofibrillary tangles in post‐mortem tissue. However, such approaches may not take full advantage of information...

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Vydáno v:	Human brain mapping Ročník 40; číslo 2; s. 638 - 651
Hlavní autoři:	Vogel, Jacob W., Mattsson, Niklas, Iturria‐Medina, Yasser, Strandberg, Olof T., Schöll, Michael, Dansereau, Christian, Villeneuve, Sylvia, Flier, Wiesje M., Scheltens, Philip, Bellec, Pierre, Evans, Alan C., Hansson, Oskar, Ossenkoppele, Rik
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Hoboken, USA John Wiley & Sons, Inc 01.02.2019
Témata:	Aged Aged, 80 and over Alzheimer Disease - diagnostic imaging Alzheimer Disease - metabolism Alzheimer Disease - pathology Alzheimer Disease - physiopathology Alzheimer's disease Annan medicin och hälsovetenskap AV1451 Biomarkers Carbolines Cluster Analysis Clustering Cognition Cognition & reasoning Cognitive ability Cohort Studies Computer and Information Sciences Data- och informationsvetenskap (Datateknik) Datasets as Topic data‐driven Dementia disorders Demographics Demography Disease control Education Emission analysis Episodic memory Female Fluorine isotopes Gerontologi, medicinsk/hälsovetenskaplig inriktning Gerontology, specialising in Medical and Health Sciences Humans Male Medical and Health Sciences Medical imaging Medicin och hälsovetenskap Memory Neurodegenerative diseases Neurofibrillary tangles Neuroimaging Neuroimaging - methods Neurology Neurosciences Neurovetenskaper Other Medical and Health Sciences Pathology Pattern Recognition, Automated - methods Positron emission Positron emission tomography Positron-Emission Tomography - methods Spatial data Tau protein tau Proteins - metabolism tau‐PET Tomography AV1451 cognition data-driven tau-PET Alzheimer's disease
ISSN:	1065-9471, 1097-0193, 1097-0193
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Popis
Shrnutí:	Previous positron emission tomography (PET) studies have quantified filamentous tau pathology using regions‐of‐interest (ROIs) based on observations of the topographical distribution of neurofibrillary tangles in post‐mortem tissue. However, such approaches may not take full advantage of information contained in neuroimaging data. The present study employs an unsupervised data‐driven method to identify spatial patterns of tau‐PET distribution, and to compare these patterns to previously published “pathology‐driven” ROIs. Tau‐PET patterns were identified from a discovery sample comprised of 123 normal controls and patients with mild cognitive impairment or Alzheimer's disease (AD) dementia from the Swedish BioFINDER cohort, who underwent [18F]AV1451 PET scanning. Associations with cognition were tested in a separate sample of 90 individuals from ADNI. BioFINDER [18F]AV1451 images were entered into a robust voxelwise stable clustering algorithm, which resulted in five clusters. Mean [18F]AV1451 uptake in the data‐driven clusters, and in 35 previously published pathology‐driven ROIs, was extracted from ADNI [18F]AV1451 scans. We performed linear models comparing [18F]AV1451 signal across all 40 ROIs to tests of global cognition and episodic memory, adjusting for age, sex, and education. Two data‐driven ROIs consistently demonstrated the strongest or near‐strongest effect sizes across all cognitive tests. Inputting all regions plus demographics into a feature selection routine resulted in selection of two ROIs (one data‐driven, one pathology‐driven) and education, which together explained 28% of the variance of a global cognitive composite score. Our findings suggest that [18F]AV1451‐PET data naturally clusters into spatial patterns that are biologically meaningful and that may offer advantages as clinical tools.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf Funding information Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Department of Defense; National Institutes of Health, Grant/Award Number: U01 AG024904; Alzheimer's Disease Neuroimaging Initiative Oskar Hansson and Rik Ossenkoppele contributed equally to this study.
ISSN:	1065-9471 1097-0193 1097-0193
DOI:	10.1002/hbm.24401