Details

Autor(en) / Beteiligte

• Lee, Taek-Soo
• Wang, Jizhe
• Xu, Jingyan
• Olivier, Patrick
• Perkins, Amy
• Tung, Chi-Hua
• Tsui, Benjamin

Titel

Development and evaluation of robust data-driven respiratory motion extraction methods for clinical list-mode ^sup 18^F-FDG PET

Ist Teil von

• The Journal of nuclear medicine (1978), 2017-05, Vol.58, p.1350

Ort / Verlag

New York: Society of Nuclear Medicine

Erscheinungsjahr

2017

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Objectives: The goal is to develop and evaluate several data-driven respiratory motion (RM) extraction methods from patient list-mode 18F-FDG PET datasets acquired from a commercial PET scanner. Methods: We have developed several data-driven RM extraction methods designed for different activity distributions in various internal organs found in typical patient 18F-FDG PET images from the rebinned list-mode data. In a typical method, surrogate RM signals were obtained from the centroids of the image intensity of the myocardial activity uptake within a 3D VOI (volume-of-interest) covering the heart region. The Fourier Transform (FT) of the time sequence of the surrogate RM signals and smoothing reveal the RM peak and its average period (Pav). The other RM extraction methods evaluate the motion of various organs of interest depending on the activity distributions. The 3D VOIs used were optimized in terms of the location, size, and shape for the highest signal-to-noise (S/N) in the RM peak extraction. A preliminary evaluation study of the different methods was conducted with 14 patient 18F-FDG PET datasets. The accuracy of the Pav estimates was evaluated by comparing them with results from a commercial external RM monitoring system and by cross comparison of results from the application of the different RM methods to the same patient. Results: All 14 patient RG list-mode 18F-FDG PET datasets were successfully analyzed by one or more of the different RM extraction methods. Among them, 11 were found to have relatively high myocardial uptake, and the extracted RM peak and Pav showed high S/N and excellent agreement with those obtained from the external RM monitoring belt system. The other methods were successfully applied to patient studies in which the levels of myocardial activity uptakes were relatively low. Excellent agreements were also found in cross comparison between Pav estimates obtained from different methods and measurements obtained from the external RM monitoring device of the same patient in several cases. Conclusion: We have developed and evaluated several data-driven RM extraction methods that were designed to cover typical activity distributions found in 18F-FDG PET patient studies. They were successfully applied to all 14 patient CG list-mode 18F-FDG PET datasets in a preliminary evaluation study. This work is an important first step in the full clinical application of RM estimation and compensation for improved image quality and quantitation in 18F-FDG and myocardial perfusion PET.