Clinical respiratory motion correction software (reconstruct, register and averaged—RRA), for 18F-FDG-PET-CT: phantom validation, practical implications and patient evaluation

Abstract

Objective: On fluorine-18 fludeoxyglucose ( 18 F-FDG) positron emission tomography (PET) CT of pulmonary or hepatic lesions, standard uptake value (SUV) is often underestimated due to patient breathing. The aim of this study is to validate, on phantom and patient data, a motion correction algorithm [reconstruct, register and averaged (RRA)] implemented on a PET-CT system. Methods: Three phantoms containing five spheres filled with 18 F-FDG and suspended in a water or Styrofoam® 18 F-FDG-filled tank to create different contrasts and attenuation environment were acquired on a Discovery GE710. The spheres were animated with a 2-cm longitudinal respiratory-based movement. Respiratory-gated (RRA) and ungated PET images were compared with static reference images (without movement). The optimal acquisition time, number of phases and the best phase within the respiratory cycle were investigated. The impact of irregular motion was also investigated. Quantification impact was computed on each sphere. Quantification improvement on 28 lung lesions was also investigated. Results: Phantoms: 4 min was required to obtain a stable quantification with the RRA method. The reference phase and the number of phases used for RRA did not affect the quantification which was similar on static acquisitions but different on ungated images. The results showed that the maximum standard uptake value (SUV max ) restoration is majored for the smallest spheres (#2.1 ml). Patients: SUV max on RRA and ungated acquisitions were statistically different to the SUV max on whole-body images (p 5 0.05) but not different from each other (mean SUV max : 7.0 6 7.8 vs 6.9 6 7.8, p 5 0.23 on RRA and ungated images, respectively). We observed a statistically significant correlation between SUV restoration and lesion displacement, with a real SUV quantitation improvement for lesion with movement .1.2 mm. Conclusion: According to the results obtained using phantoms, RRA method is promising, showing a real impact on the lesion quantification on phantom data. With regard to the patient study, our results showed a trend towards an increase in the SUVs and a decrease in the volume between the ungated and RRA data. We also noticed a statistically significant correlation between the quantitative restoration obtained with RRA compared with ungated data and lesion displacement, indicating that the RRA approach should be reserved to patients with small lesions or nodes moving with a displacement larger than 1.2 cm. Advances in knowledge: This article investigates the performances of motion correction software recently introduced in PET. The conclusion revealed that such respiratory motion correction approach shows a real impact on the lesion quantification but must be reserved to the patient for whom lesion displacement was confirmed and high enough to clearly impact lesion evaluation.

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

“…This finding should be further investigated. It has been reported before that motion correction may lead to degraded image results for small motion amplitudes [29]. Although this effect was not expected in both motion correction methods used in our study, we tested G2G-MC with a zero MVF which resulted in no measurable image degradation.…”

Respiratory-gated PET/CT for pulmonary lesion characterisation—promises and problems

“…Software developments, such as Q.Freeze (GE Healthcare), have been introduced to overcome the issue of low counts in individual 4D gated bins. [20][21][22] Flow techniques to merge and register count data from all the acquired gated bins to recover a motion-corrected lesion image with good count statistics. A further development has been datadriven gating or software gating which aims to eliminate the need for hardware tracking of external respiratory motion.…”

“…QuAntiFicAtion & AssessMent oF GAted iMAGinG: novel techniQues Q.Freeze Bouyeure-Petit et al 21 and Minamimoto et al 22 have recently investigated the current commercial version of Q.Freeze in phantom and patient studies. Initial results show that in phantom studies Q.Freeze is effective in restoring sphere object quantification (e.g.…”

Trends in oncologic hybrid imaging

“…An underlying principle is, however, that motion is captured in the acquired PET data without the need for an external gaiting device (e.g. respiration belts) (Bouyeure-Petit et al, 2017 ).

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