Quantitative agreement between AMYclz and CortexID for 18F-florbetapir amyloid PET: a retrospective study of 103 patients

Purpose Quantitative analysis of amyloid PET images is increasingly used to support visual interpretation and to provide objective measures of amyloid burden. However, quantitative values may vary depending on the analysis software used. This study aimed to evaluate the quantitative agreement between two analysis platforms, AMYclz and CortexID, for 18 F-florbetapir amyloid PET. Materials and methods This retrospective study included 103 consecutive patients who underwent 18 F-florbetapir PET for evaluation of cognitive impairment. Visual interpretation was used to classify scans as amyloid-positive or amyloid-negative. Quantitative analysis was performed using CortexID and AMYclz software to obtain global cortical standardized uptake value ratios (SUVr). AMYclz additionally provided Centiloid scale (CL) values. The ability of quantitative metrics to differentiate visually positive and negative scans was evaluated using receiver operating characteristic (ROC) analysis, and agreement between software platforms was assessed using correlation, linear regression, and Bland–Altman analysis. Results Among 103 patients, 59 were visually classified as amyloid-positive and 44 as amyloid-negative. CortexID SUVr values were significantly higher in amyloid-positive patients than in amyloid-negative patients (1.30 ± 0.14 vs. 0.97 ± 0.09, p < 0.001). AMYclz SUVr showed similar separation between groups (1.34 ± 0.14 vs. 0.99 ± 0.09, p < 0.001). ROC analysis demonstrated excellent discrimination for CortexID SUVr (AUC = 0.986), AMYclz SUVr (AUC = 0.996), and CL values (AUC = 0.996). CortexID and AMYclz SUVr values showed strong correlation ( r = 0.957) with minimal systematic bias. Discordant classification between the two software platforms was observed in three cases (2.9%), all near the diagnostic threshold. Conclusion AMYclz and CortexID demonstrated excellent quantitative agreement for 18 F-florbetapir amyloid PET. Both AMYclz SUVr and CL values showed excellent ability to differentiate visually amyloid-positive and amyloid-negative scans, supporting the reliability of quantitative amyloid PET analysis across different software platforms in clinical practice.