Comparison of two elastic motion correction approaches for whole-body PET/CT: motion deblurring vs gate-to-gate motion correction

Abstract

Background Respiratory motion in PET/CT leads to well-known image degrading effects commonly compensated using elastic motion correction approaches. Gate-to-gate motion correction techniques are promising tools for improving clinical PET data but suffer from relatively long reconstruction times. In this study, the performance of a fast elastic motion compensation approach based on motion deblurring (DEB-MC) was evaluated on patient and phantom data and compared to an EM-based fully 3D gate-to-gate motion correction method (G2G-MC) which was considered the gold standard. Methods Twenty-eight patients were included in this study with suspected or confirmed malignancies in the thorax or abdomen. All patients underwent whole-body [18F]FDG PET/CT examinations applying hardware-based respiratory gating. In addition, a dynamic anthropomorphic thorax phantom was studied with PET/CT simulating tumour motion under controlled but realistic conditions. PET signal recovery values were calculated from phantom scans by comparing lesion activities after motion correction to static ground truth data. Differences in standardized uptake values (SUV) and metabolic volume (MV) between both reconstruction methods as well as between motion-corrected (MC) and non motion-corrected (NOMC) results were statistically analyzed using a Wilcoxon signed-rank test. Results Phantom data analysis showed high lesion recovery values of 91% (2 cm motion) and 98% (1 cm) for G2G-MC and 83% (2 cm) and 90% (1 cm) for DEB-MC. The statistical analysis of patient data found significant differences between NOMC and MC reconstructions for SUV max, SUV mean, MV, and contrast-to-noise ratio (CNR) for both reconstruction algorithms. Furthermore, both methods showed similar increases of 11–12% in SUV max and SUV mean after MC. The statistical analysis of the MC/NOMC ratio found no significant differences between the methods. Conclusion Both motion correction techniques deliver comparable improvements of SUV max, SUV mean, and CNR after MC on clinical and phantom data. The fast elastic motion compensation technique DEB-MC may thereby be a valuable alternative to state-of-the art motion correction techniques.

Evaluation of a respiratory motion-corrected image reconstruction algorithm in 2-[18F]FDG and [68Ga]Ga-DOTA-NOC PET/CT: impacts on image quality and tumor quantification

“…O u r r e s u l t s s h o w e d t h a t M C I R i m p r o v e d t h e quantification accuracy of lesions' SUVs and volumes caused by respiratory motion artifacts, which agrees with previous findings in other studies that used elastic respiratory motion correction algorithms (13,14,23,26). Pösse et al (23) reported that compared with uncorrected images, a gate-to-gate elastic motion compensation (G2G-MC) and an elastic motion deblurring (EMDB) algorithm yielded a 12% and 11% increase in lesion SUVs and an 18% and 28% decrease in lesion volume in 28 patients, respectively. In this study, we found that the SUVs increased by 11-15% while lesion volume decreased by 15-20% in a larger population using MCIR.…”

“…Previous clinical studies found a large variance in respiratory amplitude at the diaphragm that can be from 0.4 to 3.8 cm in a superior-inferior direction depending on breathing patterns (2,22). The average motion extent of a lung tumor is usually in the order of 1 cm (23)(24)(25). Our phantom study also showed that the SUV and volume change caused by motion correction were associated with motion amplitudes (Figure 2).…”

Respiratory and cardiac motion correction in PET using elastic motion approach for simultaneous abdomen and thorax PET/MRI.

“…Elastic motion correction (eMOCO) is usually used in PET/CT to correct for cardiac and respiratory motions in PET images, which has proven to be effective [24][25][26] .…”

Respiratory motion correction in F-18-FDG PET/CT impacts lymph node assessment in lung cancer patients

“…Signals from both sources were used for elastic motioncorrected PET reconstructions by first reconstructing the "optimal gate" comprising coincidence data from the narrowest signal amplitude interval covering 35% of the total data, giving a good compromise between motion resolution and data statistics, and then using mass-preserving optical flow techniques to determine a motion vector field between the gated and a static reconstruction. This vector field was then finally used in an effective deblurring step within a motion-corrected image reconstruction [18,19], resulting in BG-MC and DDG-MC datasets.…”

“…An important subset of the latter methods, software or data-driven gating (DDG) is based on analyzing measured PET raw data to calculate breathing signals instead of using additional hardware to record these signals, thus potentially simplifying clinical scans and increasing patient comfort [14][15][16][17]. Finally, fully motion-corrected reconstructions have been recently introduced by taking all measured PET data into account, rather than just a subset determined by a specified gating approach [18,19].…”