Inter-Pass Motion Correction for Whole-Body Dynamic PET and Parametric Imaging

Whole-body dynamic fluoro-D-glucose (FDG)-positron emission tomography (PET) imaging through continuous-bed-motion (CBM) mode multi-pass acquisition protocol is a promising metabolism measurement. However, inter-pass misalignment originating from body movement could degrade parametric quantification. We aim to apply a non-rigid registration method for inter-pass motion correction in whole-body dynamic PET. 27 subjects underwent a 90-min whole-body FDG CBM PET scan on a Biograph mCT (Siemens Healthineers), acquiring 9 over-the-heart single-bed passes and subsequently 19 CBM passes (frames). The inter-pass motion correction was executed using non-rigid image registration with multi-resolution, B-spline free-form deformations. The parametric images were then generated by Patlak analysis. The overlaid Patlak slope <inline-formula> <tex-math notation="LaTeX">$K_{i}$ </tex-math></inline-formula> and y-intercept <inline-formula> <tex-math notation="LaTeX">$V_{b}$ </tex-math></inline-formula> images were visualized to qualitatively evaluate motion impact and correction effect. The normalized weighted mean-squared Patlak fitting errors (NFEs) were compared in the whole body, head, and hypermetabolic regions of interest (ROIs). In <inline-formula> <tex-math notation="LaTeX">$K_{i}$ </tex-math></inline-formula> images, ROI statistics were collected and malignancy discrimination capacity was estimated by the area under the receiver operating characteristic curve (AUC). After the inter-pass motion correction was applied, the spatial misalignment appearance between <inline-formula> <tex-math notation="LaTeX">$K_{i}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$V_{b}$ </tex-math></inline-formula> images was successfully reduced. Voxel-wise normalized fitting error maps showed global error reduction after motion correction. The NFE in the whole body (<inline-formula> <tex-math notation="LaTeX">$p \,\,=$ </tex-math></inline-formula> 0.0013), head (<inline-formula> <tex-math notation="LaTeX">$p \,\,=$ </tex-math></inline-formula> 0.0021), and ROIs (<inline-formula> <tex-math notation="LaTeX">$p \,\,=$ </tex-math></inline-formula> 0.0377) significantly decreased. The visual performance of each hypermetabolic ROI in <inline-formula> <tex-math notation="LaTeX">$K_{i}$ </tex-math></inline-formula> images was enhanced, while 3.59% and 3.67% average absolute percentage changes were observed in mean and maximum <inline-formula> <tex-math notation="LaTeX">$K_{i}$ </tex-math></inline-formula> values, respectively, across all evaluated ROIs. The estimated mean <inline-formula> <tex-math notation="LaTeX">$K_{i}$ </tex-math></inline-formula> values had substantial changes with motion correction (<inline-formula> <tex-math notation="LaTeX">$p \,\,=$ </tex-math></inline-formula> 0.0021). The AUC of both mean <inline-formula> <tex-math notation="LaTeX">$K_{i}$ </tex-math></inline-formula> and maximum <inline-formula> <tex-math notation="LaTeX">$K_{i}$ </tex-math></inline-formula> after motion correction increased, possibly suggesting the potential of enhancing oncological discrimination capacity through inter-pass motion correction.