Alzheimer’s Disease Prediction Using Attention Mechanism with Dual‑Phase 18 F‑Florbetaben Images / 대한핵의학회잡지

ABSTRACT

Materials and Methods@#A total of 264 patients (74 CN and 190 AD), who underwent FBB imaging test and neuropsychological tests, were retrospectively analyzed. Early- and delay-phase FBB images were spatially normalized with an in-house FBB template. The regional standard uptake value ratios were calculated with the cerebellar region as a reference region and used as independent variables that predict the diagnostic label assigned to the raw image. @*Results@#AD positivity scores estimated from dual-phase FBB showed better accuracy (ACC) and area under the receiver operating characteristic curve (AUROC) for AD detection (ACC 0.858, AUROC 0.831) than those from delay phase FBB imaging (ACC 0.821, AUROC 0.794). AD positivity score estimated by dual-phase FBB (R −0.5412) shows a higher correlation with psychological test compared to only dFBB (R −0.2975). In the relevance analysis, we observed that LSTM uses different time and regions of early-phase FBB for each disease group for AD detection. @*Conclusions@#These results show that the aggregated model with dual-phase FBB with long short-term memory and attention mechanism can be used to provide a more accurate AD positivity score, which shows a closer association with AD, than the prediction with only a single phase FBB.