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- Title
Error propagation analysis of seven partial volume correction algorithms for [<sup>18</sup>F]THK-5351 brain PET imaging.
- Authors
Oyama, Senri; Hosoi, Ayumu; Ibaraki, Masanobu; McGinnity, Colm J.; Matsubara, Keisuke; Watanuki, Shoichi; Watabe, Hiroshi; Tashiro, Manabu; Shidahara, Miho
- Abstract
Background: Novel partial volume correction (PVC) algorithms have been validated by assuming ideal conditions of image processing; however, in real clinical PET studies, the input datasets include error sources which cause error propagation to the corrected outcome. Methods: We aimed to evaluate error propagations of seven PVCs algorithms for brain PET imaging with [18F]THK-5351 and to discuss the reliability of those algorithms for clinical applications. In order to mimic brain PET imaging of [18F]THK-5351, pseudo-observed SUVR images for one healthy adult and one adult with Alzheimer's disease were simulated from individual PET and MR images. The partial volume effect of pseudo-observed PET images were corrected by using Müller-Gärtner (MG), the geometric transfer matrix (GTM), Labbé (LABBE), regional voxel-based (RBV), iterative Yang (IY), structural functional synergy for resolution recovery (SFS-RR), and modified SFS-RR algorithms with incorporation of error sources in the datasets for PVC processing. Assumed error sources were mismatched FWHM, inaccurate image-registration, and incorrectly segmented anatomical volume. The degree of error propagations in ROI values was evaluated by percent differences (%diff) of PV-corrected SUVR against true SUVR. Results: Uncorrected SUVRs were underestimated against true SUVRs (− 15.7 and − 53.7% in hippocampus for HC and AD conditions), and application of each PVC algorithm reduced the %diff. Larger FWHM mismatch led to larger %diff of PVC-SUVRs against true SUVRs for all algorithms. Inaccurate image registration showed systematic propagation for most algorithms except for SFS-RR and modified SFS-RR. Incorrect segmentation of the anatomical volume only resulted in error propagations in limited local regions. Conclusions: We demonstrated error propagation by numerical simulation of THK-PET imaging. Error propagations of 7 PVC algorithms for brain PET imaging with [18F]THK-5351 were significant. Robust algorithms for clinical applications must be carefully selected according to the study design of clinical PET data.
- Subjects
IMAGE reconstruction algorithms; BRAIN imaging; ERROR analysis in mathematics; POSITRON emission tomography; TRANSFER matrix; IMAGE registration; MAGNETIC resonance imaging
- Publication
EJNMMI Physics, 2020, Vol 7, Issue 1, pN.PAG
- ISSN
2197-7364
- Publication type
Article
- DOI
10.1186/s40658-020-00324-9