Data-Driven Respiratory Gating Outperforms Device-Based Gating for Clinical 18F-FDG PET/CT

Abstract

A data-driven method for respiratory gating in PET has recently been commercially developed. We sought to compare the performance of the algorithm with an external, device-based system for oncologic ¹⁸F-FDG PET/CT imaging. Methods: In total, 144 whole-body ¹⁸F-FDG PET/CT examinations were acquired, with a respiratory gating waveform recorded by an external, device-based respiratory gating system. In each examination, 2 of the bed positions covering the liver and lung bases were acquired with a duration of 6 min. Quiescent-period gating retaining approximately 50% of coincidences was then able to produce images with an effective duration of 3 min for these 2 bed positions, matching the other bed positions. For each examination, 4 reconstructions were performed and compared: data-driven gating (DDG) (we use the term DDG-retro to distinguish that we did not use the real-time R-threshold-based application of DDG that is available within the manufacturer's product), external device-based gating (real-time position management (RPM)-gated), no gating but using only the first 3 min of data (ungated-matched), and no gating retaining all coincidences (ungated-full). Lesions in the images were quantified and image quality scored by a radiologist who was masked to the method of data processing. Results: Compared with the other reconstruction options, DDG-retro increased the SUV_max and decreased the threshold-defined lesion volume. Compared with RPM-gated, DDG-retro gave an average increase in SUV_max of 0.66 ± 0.1 g/mL (n = 87, P < 0.0005). Although the results from the masked image evaluation were most commonly equivalent, DDG-retro was preferred over RPM-gated in 13% of examinations, whereas the opposite occurred in just 2% of examinations. This was a significant preference for DDG-retro (P = 0.008, n = 121). Liver lesions were identified in 23 examinations. Considering this subset of data, DDG-retro was ranked superior to ungated-full in 6 of 23 (26%) cases. Gated reconstruction using the external device failed in 16% of examinations, whereas DDG-retro always provided a clinically acceptable image. Conclusion: In this clinical evaluation, DDG-retro provided performance superior to that of the external device-based system. For most examinations the performance was equivalent, but DDG-retro had superior performance in 13% of examinations, leading to a significant preference overall.

Keywords: FDG; PET/CT; RPM; data-driven gating; respiratory gating.

Figure 1

A depiction of quiescent period gating, in which part of the respiratory cycle associated with relatively little motion is identified and retained in the gated image.

Figure 2

Boxplots showing SUV_max for DDG-retro, minus that obtained from RPM gated, Ungated matched, or Ungated full. Positive values indicate higher SUV_max in the case of DDG-retro. The line on the box indicates the median.

Figure 3

Comparison of clinical scoring between DDG-retro and A) RPM-gated, B) Ungated matched, and C) Ungated full. A lower score indicated preference, and hence negative scores represent preference for DDG-retro.

Figure 4

Considering only those studies with visible lesions in the liver, a comparison of clinical scoring between DDG-retro and A) RPM-gated, B) Ungated matched, and C) Ungated full. A lower score indicated preference, and hence negative scores represent preference for DDG-retro.

Figure 5

A coronal slice showing an ¹⁸F-FDG avid liver metastasis (indicated by arrow) which is easier to detect and has a higher SUV_max on the two gated reconstructions, as compared to ungated. In this example, the DDG-retro and RPM-gated images received an equal score for overall image quality, and both were considered superior to the ungated images. The lesion indicated by the arrow was not considered to be definitely visible on the Ungated matched image, and was borderline-visible on the Ungated full image. One can also see the reduction in noise in the Ungated full image, as compared to the other three images. The images are on an SUV grayscale of 0–6.

Figure 6

Comparison of noise scoring across the four image reconstructions. Error bars represent standard errors on the mean.