Rigid motion tracking using moments of inertia in TOF-PET brain studies. (13th September 2021)

• Record Type: Journal Article
• Authors: Rezaei, Ahmadreza; Spangler-Bickell, Matthew; Schramm, Georg; Van Laere, Koen; Nuyts, Johan; Defrise, Michel
• Is Part Of: Physics in medicine & biology. Volume 66:Number 18(2021)
• Publication Date: 2021-09-13
• Subjects: time of flight positron emission tomography -- brain imaging -- data-driven motion estimation -- rigid motion correction; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/ac2268
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: A data-driven method is proposed for rigid motion estimation directly from time-of-flight (TOF)-positron emission tomography (PET) emission data. Rigid motion parameters (translations and rotations) are estimated from the first and second moments of the emission data masked in a spherical volume. The accuracy of the method is analyzed on 3D analytical simulations of the PET-SORTEO brain phantom, and subsequently tested on 18 F-FDG as well as 11 C-PIB brain datasets acquired on a TOF-PET/CT scanner. The estimated inertia-based motion is later compared to rigid motion parameters obtained by directly registering the short frame backprojections. We find that the method provides sub mm/degree accuracies for the estimated rigid motion parameters for counts corresponding to typical 0.5 s, 1 s, and 2 s 18 F-FDG brain scans, with the current TOF resolutions clinically available. The method provides robust motion estimation for different types of patient motion, most notably for a continuous patient motion case where conventional frame-based approaches which rely on little to no intra-frame motion of short time intervals could fail. The method relies on the detection of stable eigenvectors for accurate motion estimation, and a monitoring of this condition can reveal time-frames where the motion estimation is less accurate, such as in dynamic PET studies.