title: Insight on AV-45 binding in white and grey matter from histogram analysis: a study on early Alzheimer's disease patients and healthy subjects.
abstract: OBJECTIVE
  AV-45 amyloid biomarker is known to show uptake in white matter in patients with Alzheimer's disease (AD), but also in the healthy population. This binding, thought to be of a non-specific lipophilic nature, has not yet been investigated. The aim of this study was to determine the differential pattern of AV-45 binding in white matter in healthy and pathological populations.
  
  
  METHODS
  We recruited 24 patients presenting with AD at an early stage and 17 matched, healthy subjects. We used an optimized positron emission tomography-magnetic resonance imaging (PET-MRI) registration method and an approach based on an intensity histogram using several indices. We compared the results of the intensity histogram analyses with a more canonical approach based on target-to-cerebellum Standard Uptake Value (SUVr) in white and grey matter using MANOVA and discriminant analyses. A cluster analysis on white and grey matter histograms was also performed.
  
  
  RESULTS
  White matter histogram analysis revealed significant differences between AD and healthy subjects, which were not revealed by SUVr analysis. However, white matter histograms were not decisive to discriminate groups, and indices based on grey matter only showed better discriminative power than SUVr. The cluster analysis divided our sample into two clusters, showing different uptakes in grey, but also in white matter.
  
  
  CONCLUSIONS
  These results demonstrate that AV-45 binding in white matter conveys subtle information not detectable using the SUVr approach. Although it is not more efficient than standard SUVr in discriminating AD patients from healthy subjects, this information could reveal white matter modifications.
authors.affiliation: Inserm, imagerie cérébrale et handicaps neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse, Place du Dr. Baylac, CHU Purpan, Pavillon Baudot, 31059, Toulouse cedex 9, France, federico.nemmi@gmail.com.
authors.forename: Federico
authors.initials: F
authors.lastname: Nemmi
authors.forename: Laure
authors.initials: L
authors.lastname: Saint-Aubert
authors.forename: Djilali
authors.initials: D
authors.lastname: Adel
authors.forename: Anne-Sophie
authors.initials: AS
authors.lastname: Salabert
authors.forename: Jérémie
authors.initials: J
authors.lastname: Pariente
authors.forename: Emmanuel J
authors.initials: EJ
authors.lastname: Barbeau
authors.forename: Pierre
authors.initials: P
authors.lastname: Payoux
authors.forename: Patrice
authors.initials: P
authors.lastname: Péran
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000000981:diagnostic imaging / Q000378:metabolism*; D000682:Amyloid / Q000378:metabolism; D000814:Aniline Compounds / Q000378:metabolism*; D016022:Case-Control Studies; D016000:Cluster Analysis; D016002:Discriminant Analysis; D005026:Ethylene Glycols / Q000378:metabolism*; D005260:Female; D066128:Gray Matter / Q000000981:diagnostic imaging / Q000378:metabolism*; D006801:Humans; D008297:Male; D049268:Positron-Emission Tomography; D011485:Protein Binding; D066127:White Matter / Q000000981:diagnostic imaging / Q000378:metabolism*
chemical_list: D000682:Amyloid; D000814:Aniline Compounds; D005026:Ethylene Glycols; C545186:florbetapir