Purpose: To quantitatively validate in-phantom effectiveness of a respiratory signal-guided 4D CT protocol based on retrospective reconstruction in GE CT scanners outlined by Pan et al. (2017) with the purpose of reducing breathing artifacts. This protocol has the striking advange of not requiring any off-line data processing, new software or hardware besides the scanner itself.
Methods: A custom made slab-like wooden insert was fit inside a CIRS motion phantom. Five motion curves were generated and loaded into the phantom during CT examination on a GE Optima 580 scanner. The motion curves simulate an increasingly irregular breathing pattern, ranging from a sinusoidal (meant to establish a baseline) to a breath-hold like signal. CT examinations were performed with and without using Pan et al.’s manual prospective gating 4D CT protocol. The wooden insert AP and LL motions were compared in each scenario by the means of in-house R-based image processing code.
Results: For each CT acquisition, total angular deviations in the wooden insert motion are calculated. Considering ordinary examinations, compared to the sinusoidal baseline acquisition, a regular breathing profile one would display +22.1% angular deviations, increasing to +107.5%, +182.1% and +256.9% as the loaded motion curves raise in their degree of irregularity. If the gating signal-guided protocol is applied, though, these percentage ratios in the irregular profiles drop to +11,8%, +54,1% and +43,32% respectively.
Conclusion: In-phantom qualitative validation of this protocol had already been provided by Pan et al. (2017) and Werner et al. (2020) with further development of AI integration. Concerning breathing artifact reduction, the concept of the applied protocol has proven itself to be effective from a quantitative point of view. Further work will be needed to include in this validation C-C motion.
Motion Artifacts, Image Analysis, Gating