Imaging biomarkers in neurodegeneration: Current and future practices

Research output: Contribution to journalReview article

Abstract

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course "Biomarkers in neurodegenerative diseases". In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

Details

Authors
  • Peter N.E. Young
  • Mar Estarellas
  • Emma Coomans
  • Meera Srikrishna
  • Helen Beaumont
  • Anne Maass
  • Ashwin V. Venkataraman
  • Rikki Lissaman
  • Daniel Jiménez
  • Matthew J. Betts
  • Eimear McGlinchey
  • David Berron
  • Antoinette O'Connor
  • Nick C. Fox
  • Joana B. Pereira
  • William Jagust
  • Stephen F. Carter
  • Ross W. Paterson
  • Michael Schöll
Organisations
External organisations
  • University of Manchester
  • German Center for Neurodegenerative Diseases (DZNE), Bonn
  • Imperial College London
  • Cardiff University
  • University College London
  • University of Chile
  • Otto von Guericke University Magdeburg
  • Trinity College Dublin
  • Karolinska Institutet
  • University of California, Berkeley
  • Lawrence Berkeley National Laboratory
  • University of Cambridge
  • Sahlgrenska University Hospital
  • University of Gothenburg
  • Amsterdam UMC - Vrije Universiteit Amsterdam
  • Vrije Universiteit Amsterdam
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Neurosciences

Keywords

  • Alzheimer's disease, dementia, Machine learning, MRI, Neurodegenerative diseases, Neuroimaging, PET
Original languageEnglish
Article number49
JournalAlzheimer's Research and Therapy
Volume12
Issue number1
Publication statusPublished - 2020 Apr 27
Publication categoryResearch
Peer-reviewedYes