The Patlak graphical analysis (PGAREF) for quantification of irreversible tracer binding with a reference tissue model was approximated by a dual time point imaging approach (DTPREF). The DTPREF was applied to 18 [18F]-FDOPA brain scans using the occipital cortex as reference region (DTPOCC) and compared to both PGAOCC and striatal-to-occipital ratios (SOR). Pearson correlation analysis and Bland-Altman plots showed an excellent correlation and good agreement between DTPOCC and PGAOCC, while correlations between SOR and PGAOCC were consistently lower. Linear discriminant analysis (LDA) demonstrated a similar performance for all methods in differentiating patients with Parkinson's disease (PD) from healthy controls (HC). Specifically for [18F]-FDOPA brain imaging, these findings validate DTPOCC as an approximation for PGAOCC, providing the same quantitative information while reducing the acquisition time to two short static scans. For PD patients, this approach can greatly improve patient comfort while reducing motion artifacts and increasing image quality. In general, DTPREF can improve the clinical applicability of tracers with irreversible binding characteristics when a reference tissue is available.
Keywords: Dual time point imaging; Parkinson’s disease; Patlak graphical analysis; [18F]-FDOPA; positron emission tomography.