Imaging β-amyloid fibrils in Alzheimer's disease: A critical analysis through simulation of amyloid fibril polymerization

Kooresh Shoghi-Jadid, Jorge R. Barrio, Vladimir Kepe, Hsiao Ming Wu, Gary W. Small, Michael E. Phelps, Sung Cheng Huang

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


The polymerization of β-amyloid (Aβ) peptides into fibrillary plaques is implicated, in part, in the pathogenesis of Alzheimer's disease. Aβ molecular imaging probes (Aβ-MIPs) have been introduced in an effort to quantify amyloid burden or load, in subjects afflicted with AD by invoking the classic PET receptor model for the quantitation of neuronal receptor density. In this communication, we explore conceptual differences between imaging the density of amyloid fibril polymers and neuronal receptors. We formulate a mathematical model for the polymerization of Aβ with parameters that are mapped to biological modulators of fibrillogenesis and introduce a universal measure for amyloid load to accommodate various interactions of Aβ-MIPs with fibrils. Subsequently, we hypothesize four Aβ-MIPs and utilize the fibrillogenesis model to simulate PET tissue time activity curves (TACs). Given the unique nature of polymer growth and resulting PET TAC, the four probes report differing amyloid burdens for a given brain pathology, thus complicating the interpretation of PET images. In addition, we introduce the notion of an MIP's resolution, apparent maximal binding site concentration, optimal kinetic topology and its resolving power in characterizing the pathological progression of AD and the effectiveness of drug therapy. The concepts introduced in this work call for a new paradigm that goes beyond the classic parameters Bmax and KD to include binding characteristics to polymeric peptide aggregates such as amyloid fibrils, neurofibrillary tangles and prions.

Original languageEnglish
Pages (from-to)337-351
Number of pages15
JournalNuclear Medicine and Biology
Issue number4
StatePublished - May 2005


  • Alzheimer's disease
  • Amyloid burden
  • Amyloid fibril
  • Imaging
  • Mathematical model
  • Polymerization


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