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

Bucci, Marco; Savitcheva, Irina; Farrar, Gill; Salvadó, Gemma; Collij, Lyduine E.; Doré, Vincent; Gispert, Juan Domingo; Gunn, Roger; Hanseeuw, Bernard; Hansson, Oskar; Shekari, Mahnaz; Lhommel, Renaud; Molinuevo, José Luis; Rowe, Christopher; Sur, Cyrille; Whittington, Alex; Buckley, Christopher, 1948-; Nordberg, Agneta

doi:http://dx.doi.org/10.1007/s00259-021-05311-5

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

Citation

Bucci M, Savitcheva I, Farrar G, Salvadó G, Collij L, Doré V, Gispert JD, Gunn R, Hanseeuw B, Hansson O, Shekari M, Lhommel R, Molinuevo JL, Rowe C, Sur C, Whittington A, Buckley C, Nordberg A. A multisite analysis of the concordance between visual image interpretation and quantitative analysis of [18F]flutemetamol amyloid PET images. Eur J Nucl Med Mol Imaging. 2021;48(7):2183-99. DOI: 10.1007/s00259-021-05311-5

Abstract

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.