Evaluation of data-driven gating for 68Ga-DOTATOC PET-CT in patients with neuroendocrine tumors

Introduction: In PET imaging, respiratory motion can severely impair image quality, especially in tissues near the diaphragm, and consequently may lead to poorer lesion detection, delineation and quantitation. Respiratory gating has been available for many years. Previously available gating techniques involve separate devices and are hard to implement in routine clinical practice, respiratory gating has therefore often not been utilized to its full extent. Data-driven gating (DDG), based on detection of respiratory signal using principal component analysis of dynamic sinogram data, would allow for routine implementation of respiratory gating. To date, DDG has only been validated for FDG-PET. The aim of the present work was to assess the effectivity of respiratory signal detection in DDG and its effect on standardized uptake values (SUV) for ⁶⁸Ga-DOTATOC.

Methods: Fifteen patients underwent a whole-body PET-CT scan 1 h after injection of 1.5 MBq/kg body weight of ⁶⁸Ga-DOTATOC on a General Electric Discovery MI 4-ring PET-Scanner, with 2 min acquisition per bed position. MotionFree (GE-Healthcare), a principal component analysis based respiratory DDG software, was applied prospectively and the scan time per bed position was doubled for beds where a respiratory motion signal was detected in the raw data. Quiescent period gated images, containing 50 % of the doubled scan time data, were reconstructed with Q. Static software (GE Healthcare). All images were reconstructed using TOF-OSEM (3 iterations, 16 subsets) with resolution recovery. SUV_max measurements on ⁶⁸Ga-DOTATOC positive lesions (n=22) without and with DDG were compared. Also, the effectiveness of the detection of respiratory signal was evaluated retrospectively.

Results: Using the same threshold value for respiratory motion detection as recommended by the manufacturer for FDG (r = 15), motion was detected on mean 2.2 bed positions per scan. DDG resulted in a mean 16% (range -2 - 47) increase in SUV_max (p = 0.0001).

Conclusions: Using the same threshold as for FDG, respiration signals were detected in considerably more bed positions than previously reported for FDG (mean 2.2 versus 1.2), likely due to the higher image contrast for ⁶⁸Ga-DOTATOC than for FDG. DDG yielded significantly higher SUV_max values as compared to non-gated images.

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