The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification

Anne M. Smith, Nancy A. Obuchowski, Norman L. Foster, Gregory Klein, P. David Mozley, Adriaan A. Lammertsma, Richard L. Wahl, John J. Sunderland, Jean Luc Vanderheyden, Tammie L.S. Benzinger, Paul E. Kinahan, Dean F. Wong, Eric S. Perlman, Satoshi Minoshima, Dawn Matthews

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of b-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging.

Original languageEnglish
Pages (from-to)294-303
Number of pages10
JournalJournal of Nuclear Medicine
Volume64
Issue number2
DOIs
StatePublished - Feb 1 2023

Keywords

  • Alzheimer disease
  • QIBA
  • amyloid PET
  • guidelines
  • quantitative imaging biomarkers

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