Alzheimer’s Disease Prediction Using Attention Mechanism with Dual‑Phase 18 F‑Florbetaben Images
10.1007/s13139-022-00767-1
- Author:
Hyeon KANG
1
;
Do‑Young KANG
Author Information
1. Institute of Convergence BioHealth, Dong-A University, Busan, Republic of Korea
- Publication Type:ORIGINAL ARTICLE
- From:Korean Journal of Nuclear Medicine
2023;57(2):61-72
- CountryRepublic of Korea
- Language:English
-
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.
