Dual time point method for the quantification of irreversible tracer kinetics: A reference tissue approach applied to [18F]-FDOPA brain PET

Author:

Lopes Alves Isadora1,Meles Sanne K2,Willemsen Antoon TM1,Dierckx Rudi A1,Marques da Silva Ana M3,Leenders Klaus L2,Koole Michel4

Affiliation:

1. Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, The Netherlands

2. Department of Neurology, University of Groningen, University Medical Center Groningen, the Netherlands

3. Laboratory of Medical Imaging, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil

4. Department of Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven, Belgium

Abstract

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.

Publisher

SAGE Publications

Subject

Cardiology and Cardiovascular Medicine,Clinical Neurology,Neurology

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