Eligibility in the INTERCEPT‐AD trial: visual amyloid classification for equivocal SUVrs in early Alzheimer’s disease

Abstract

AbstractBackgroundPET tracers enable the in‐vivo measurement of amyloid in the brain and have been incorporated in eligibility criteria for clinical trials. Automated quantitative image analysis enables the calculation of a standardised uptake value ratio (SUVr) which can enable a rapid amyloid classification without requiring a visual read. However, quantitative analysis may have an equivocal range where amyloid classification does require a visual read. The range of SUVrs that is equivocal is not well understood.MethodParticipants in the INTERCEPT‐AD trial of ACU193 (Siemers et al., J Prev Alzheimers Dis. 2023;10(1):19‐24) underwent an amyloid [18F] Florbetapir PET scan and T1‐weighted MRI scans. MRIs were segmented using the LEAP algorithm (Wolz et al., NeuroImage. 2010;49(2):1316‐1325), registered to the PET image, and the global cortical average (GCA) SUVr based on brain regions typically with high amyloid load in Alzheimer’s disease (Klunk et al., Alzheimers Dement. 2015;11(1):1‐15) was calculated, using the whole cerebellum as the reference region. SUVrs greater than 1.2 were classified as amyloid positive, SUVrs less than 1.0 were classified as amyloid negative, and SUVrs in the equivocal range were assessed by visual read by trained central radiologists.ResultsOf 194 participants who underwent screening, 188 had an SUVr available from automated analysis. Of these, 64 were within the equivocal range (SUVr 1.0 – 1.2) and had a visual read performed. For PET scans in the equivocal range, 53 (83%) were classified as amyloid negative and 11 (17%) were classified as amyloid positive by visual read. Within the equivocal range, there was no difference in SUVrs between the images classified by visual read as amyloid negative or positive.ConclusionSUVrs may be used as an objective quantitative amyloid classification method at values > 1.2 for trial inclusion; however, in the equivocal range, the GCA SUVr did not correspond with amyloid classification based on a visual read. Further study is required to investigate the equivocal range and the use of combined quantitative measures and visual reads.