Visual assessment of [18F]flutemetamol PET images can detect early amyloid pathology and grade its extent

Abstract

PurposeTo investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR.Methods[18F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the [18F]flutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density.ResultsVR showed excellent agreement against CL = 12 (κ = .89, 95.2%) and CL = 30 (κ = .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERADSOT-based classification (i.e., any region mCERADSOT > 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density.ConclusionVR is an appropriate method for assessing early amyloid pathology and that grading the extent of visual amyloid positivity could present clinical value.