Abstract
Background and Purpose To determine the imaging characteristics and cutoff value of 18 F-florapronol (FC119S) quantitative analysis for detecting β-amyloid positivity and Al-zheimer’s disease (AD), we compared the findings of FC119S and18F-florbetaben (FBB) posi-tron-emission tomography (PET) in patients with cognitive impairment. Methods We prospectively enrolled 35 patients with cognitive impairment who underwent FBB-PET, FC119S-PET, and brain magnetic resonance imaging. We measured global and vertex-wise standardized uptake value ratios (SUVRs) using a surface-based method with the cerebellar gray matter as reference. Optimal global FC119S SUVR cutoffs were determined using receiver operating characteristic curves for β-amyloid positivity based on the global FBB SUVR of 1.478 and presence of AD, respectively. We evaluated the global and vertex-wise SUVR correlations between the two tracers. In addition, we performed correlation analysis for global or vertex-wise SUVR of each tracer with the vertex-wise cortical thicknesses. Results The optimal global FC119S SUVR cutoff value was 1.385 both for detecting β-amyloid positivity and for detecting AD. Based on the global SUVR cutoff value of each tracer, 32 (91.4%) patients had concordant β-amyloid positivity. The SUVRs of FC119S and FBB had strong global (r=0.72) and vertex-wise (r>0.7) correlations in the overall cortices, except for the parietal and temporal cortices (0.4<r<0.7). The FC119S SUVR had significant negative vertex-wise correlations with cortical thicknesses in the posterior cingulate, anterior cingulate, parietal, posterior temporal, and occipital cortices. Conclusions Quantitative FC119S-PET analysis provided reliable information for detecting β-amyloid deposition and the presence of AD.
Original language | English |
---|---|
Pages (from-to) | 260-269 |
Number of pages | 10 |
Journal | Journal of Clinical Neurology (Korea) |
Volume | 19 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2023 May |
Bibliographical note
Publisher Copyright:© 2023 Korean Neurological Association.
All Science Journal Classification (ASJC) codes
- Neurology
- Clinical Neurology