Prospective data-driven respiratory gating of [⁶⁸Ga]Ga-DOTATOC PET/CT

The aim of this prospective study was to evaluate a data-driven gating software's performance, in terms of identifying the respiratory signal, comparing [⁶⁸Ga]Ga-DOTATOC and [¹⁸F]FDG examinations. In addition, for the [⁶⁸Ga]Ga-DOTATOC examinations, tracer uptake quantitation and liver lesion detectability were assessed.

Twenty-four patients with confirmed or suspected neuroendocrine tumours underwent whole-body [⁶⁸Ga]Ga-DOTATOC PET/CT examinations. Prospective DDG was applied on all bed positions and respiratory motion correction was triggered automatically when the detected respiratory signal exceeded a certain threshold (R value ≥ 15), at which point the scan time for that bed position was doubled. These bed positions were reconstructed with quiescent period gating (QPG), retaining 50% of the total coincidences. A respiratory signal evaluation regarding the software's efficacy in detecting respiratory motion for [⁶⁸Ga]Ga-DOTATOC was conducted and compared to [¹⁸F]FDG data. Measurements of SUV_max, SUV_mean, and tumour volume were performed on [⁶⁸Ga]Ga-DOTATOC PET and compared between gated and non-gated images.

The threshold of R ≥ 15 was exceeded and gating triggered on mean 2.1 bed positions per examination for [⁶⁸Ga]Ga-DOTATOC as compared to 1.4 for [¹⁸F]FDG. In total, 34 tumours were evaluated in a quantitative analysis. An increase of 25.3% and 28.1%, respectively, for SUV_max (P < 0.0001) and SUV_mean (P < 0.0001), and decrease of 21.1% in tumour volume (P < 0.0001) was found when DDG was applied.

High respiratory signal was exclusively detected in bed positions where respiratory motion was expected, indicating reliable performance of the DDG software on [⁶⁸Ga]Ga-DOTATOC PET/CT. DDG yielded significantly higher SUV_max and SUV_mean values and smaller tumour volumes, as compared to non-gated images.