Strategies for the Molecular Imaging of Amyloid and the Value of a Multimodal Approach

Amandeep Kaur, Elizabeth J. New, Margaret Sunde

Research output: Contribution to journalReview ArticleResearchpeer-review

11 Citations (Scopus)

Abstract

Protein aggregation has been widely implicated in neurodegenerative diseases such as Alzheimer's disease, frontotemporal dementia, Parkinson's disease, and Huntington disease, as well as in systemic amyloidoses and conditions associated with localized amyloid deposits, such as type-II diabetes. The pressing need for a better understanding of the factors governing protein assembly has driven research for the development of molecular sensors for amyloidogenic proteins. To date, a number of sensors have been developed that report on the presence of protein aggregates utilizing various modalities, and their utility demonstrated for imaging protein aggregation in vitro and in vivo. Analysis of these sensors highlights the various advantages and disadvantages of the different imaging modalities and makes clear that multimodal sensors with properties amenable to more than one imaging technique need to be developed. This critical review highlights the key molecular scaffolds reported for molecular imaging modalities such as fluorescence, positron emission tomography, single photon emission computed tomography, and magnetic resonance imaging and includes discussion of the advantages and disadvantages of each modality, and future directions for the design of amyloid sensors. We also discuss the recent efforts focused on the design and development of multimodal sensors and the value of cross-validation across multiple modalities.

Original languageEnglish
Pages (from-to)2268-2282
Number of pages15
JournalACS Sensors
Volume5
Issue number8
DOIs
Publication statusPublished - 28 Aug 2020
Externally publishedYes

Keywords

  • Alzheimer's disease
  • amyloid detection
  • amyloids
  • dementia
  • fluorescent sensing
  • magnetic resonance imaging
  • neurodegeneration
  • radio imaging
  • super-resolution imaging

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