Parametric Methods for Quantification of 18F-FAZA Kinetics in Non–Small Cell Lung Cancer Patients

Journal of Nuclear Medicine

Egbert F. Smit¹  Floris H.P. van Velden¹  Pieter Raijmakers¹  Maqsood Yaqub¹  Robert C. Schuit¹  Albert D. Windhorst¹  Eline E. Verwer¹  Otto S. Hoekstra¹  Ronald Boellaard¹  Adriaan A. Lammertsma¹  Idris Bahce¹ 

关键词: PET;    hypoxia;    non–small cell lung cancer;    ¹⁸F-FAZA;    parametric images;   

DOI  :  10.2967/jnumed.114.141846

学科分类：医学（综合）

来源: Society of Nuclear Medicine

【 摘 要 】

18F-fluoroazomycinarabinoside (18F-FAZA) is a hypoxia-specific PET tracer. In future clinical applications of hypoxia imaging, such as early response monitoring or radiation therapy dose painting, accurate quantification of tracer uptake at the voxel level will be required. The aim of the present study was to assess the validity of parametric methods for the quantification of 18F-FAZA studies. Methods: Dynamic 70-min 18F-FAZA scans were obtained from 9 non–small cell lung cancer patients. Arterial blood samples, collected at 7 time points, were used for preprocessing an image-derived input function derived from volumes of interest (VOIs) defined within the ascending aorta. Time–activity curves derived from various tumor VOIs were fitted using nonlinear regression analysis (NLR) to a reversible 2-tissue-compartment model, providing volumes of distribution (VT) as an outcome measure. Next, parametric images were generated by use of both Logan graphic analysis with various linear regression start times and spectral analysis with multiple sets of basis functions. The previously defined tumor VOIs were projected onto these parametric images, and the resulting VT were compared with those obtained from NLR. In addition, the results were compared with tumor-to-blood ratios (SUVr), which are more easily obtainable. Results: The highest correlations and correspondence with NLR-derived VT were found for Logan graphic analysis with a start time of 30 min after injection (R2, 0.88; intraclass correlation coefficient [ICC], 0.93) and for spectral analysis–derived VT with a set of 30 basis functions with exponents ranging from 0.0175 to 1.9 (R2, 0.79; ICC, 0.81). SUVr yielded similar correlations but showed significant bias at high VT (R2, 0.85; ICC, 0.80). Conclusion: Both Logan graphic analysis and spectral analysis yielded VT that showed high correlations with nonlinear regression analysis–derived VT. SUVr showed bias at high VT.

【 授权许可】

Unknown