A multisite analysis of the concordance between visual image interpretation and quantitative analysis of [18F]flutemetamol amyloid PET images

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Background: [18F]flutemetamol PET scanning provides information on brain amyloid load and has been approved for routine clinical use based upon visual interpretation as either negative (equating to none or sparse amyloid plaques) or amyloid positive (equating to moderate or frequent plaques). Quantitation is however fundamental to the practice of nuclear medicine and hence can be used to supplement amyloid reading methodology especially in unclear cases. Methods: A total of 2770 [18F]flutemetamol images were collected from 3 clinical studies and 6 research cohorts with available visual reading of [18F]flutemetamol and quantitative analysis of images. These were assessed further to examine both the discordance and concordance between visual and quantitative imaging primarily using thresholds robustly established using pathology as the standard of truth. Scans covered a wide range of cases (i.e. from cognitively unimpaired subjects to patients attending the memory clinics). Methods of quantifying amyloid ranged from using CE/510K cleared marked software (e.g. CortexID, Brass), to other research-based methods (e.g. PMOD, CapAIBL). Additionally, the clinical follow-up of two types of discordance between visual and quantitation (V+Q- and V-Q+) was examined with competing risk regression analysis to assess possible differences in prediction for progression to Alzheimer’s disease (AD) and other diagnoses (OD). Results: Weighted mean concordance between visual and quantitation using the autopsy-derived threshold was 94% using pons as the reference region. Concordance from a sensitivity analysis which assessed the maximum agreement for each cohort using a range of cut-off values was also estimated at approximately 96% (weighted mean). Agreement was generally higher in clinical cases compared to research cases. V-Q+ discordant cases were 11% more likely to progress to AD than V+Q- for the SUVr with pons as reference region. Conclusions: Quantitation of amyloid PET shows a high agreement vs binary visual reading and also allows for a continuous measure that, in conjunction with possible discordant analysis, could be used in the future to identify possible earlier pathological deposition as well as monitor disease progression and treatment effectiveness.


  • Marco Bucci
  • Irina Savitcheva
  • Gill Farrar
  • Gemma Salvadó
  • Lyduine Collij
  • Vincent Doré
  • Juan Domingo Gispert
  • Roger Gunn
  • Bernard Hanseeuw
  • Oskar Hansson
  • Mahnaz Shekari
  • Renaud Lhommel
  • José Luis Molinuevo
  • Christopher Rowe
  • Cyrille Sur
  • Alex Whittington
  • Christopher Buckley
  • Agneta Nordberg
External organisations
  • Karolinska Institutet
  • Karolinska University Hospital
  • GE Healthcare, UK
  • Hospital del Mar Medical Research Institute
  • University of Melbourne
  • CSIRO Health and Biosecurity
  • Pompeu Fabra University
  • CIBER Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN)
  • Imperial College London
  • Saint-Luc University Hospital
  • Harvard Medical School
  • Pasqual Maragall Foundation for Research on Alzheimer
  • Amsterdam UMC - Vrije Universiteit Amsterdam
  • Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)
  • Merck Sharp And Dohme Corp., US
  • Invicro
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Radiology, Nuclear Medicine and Medical Imaging


  • Alzheimer’s disease, Amyloid PET, Image interpretation, Quantification, Visual inspection, [F]flutemetamol
Original languageEnglish
JournalEuropean Journal of Nuclear Medicine and Molecular Imaging
Publication statusE-pub ahead of print - 2021 Apr 21
Publication categoryResearch