Impact of Data-driven Respiratory Gating in Clinical PET

To measure the internal lung motion due to respiration using magnetic resonance images (MRIs); to evaluate the correlation between lung motion and skin surface motion and the reliability of tracking lung motion with external fiducials. An MRI protocol using fast gradient-echo sequences was developed to acquire dynamic cine images of the thoracoabdominal region along the axial, sagittal, and coronal planes. The subjects (3 healthy volunteers and 4 lung cancer patients) were instructed to perform normal or altered breathing during MRI. Lung vessels identified on MRI were used as anatomic landmarks for internal lung structures. From sagittal cine MRI scans, the positions of the lung vessels and skin surface were tracked and their movements measured. Correlation between the movements of the external markers and internal structures was then calculated and analyzed. Lung vessel motion in the superior-inferior (SI) direction correlated best with mid-upper abdominal skin surface movement (correlation coefficient, 0.89 +/- 0.09 and 0.87 +/- 0.23 for volunteers and patients, respectively). The anterior-posterior (AP) vessel motion generally correlated poorly with the skin surface movement, with marker placement on the upper chest yielding the strongest results (correlation coefficient, 0.72 +/- 0.23 and 0.44 +/- 0.27 for volunteers and patients, respectively). The strength of the correlation depended on the locations of the tracked vessels, locations of the skin surface, and subjects' breathing patterns. The best correlation was seen between the motion of an abdominal fiducial and SI lung motion. Significant intersubject variability was also observed. Movement of an external fiducial may not correlate fully with, or predict, internal lung motion. Effective monitoring of respiration may have to rely on a combination of multiple fiducials and other physiologic parameters, such as lung volume and/or air flow.

Respiratory gating is used for reducing the effects of breathing motion in a wide range of applications from radiotherapy treatment to diagnostical imaging. Different methods are feasible for respiratory gating. In this study seven gating methods were developed and tested on positron emission tomography (PET) listmode data. The results of seven patient studies were compared quantitatively with respect to motion and noise. (1) Equal and (2) variable time-based gating methods use only the time information of the breathing cycle to define respiratory gates. (3) Equal and (4) variable amplitude-based gating approaches utilize the amplitude of the respiratory signal. (5) Cycle-based amplitude gating is a combination of time and amplitude-based techniques. A baseline correction was applied to methods (3) and (4) resulting in two new approaches: Baseline corrected (6) equal and (7) variable amplitude-based gating. Listmode PET data from seven patients were acquired together with a respiratory signal. Images were reconstructed applying the seven gating methods. Two parameters were used to quantify the results: Motion was measured as the displacement of the heart due to respiration and noise was defined as the standard deviation of pixel intensities in a background region. The amplitude-based approaches (3) and (4) were superior to the time-based methods (1) and (2). The improvement in capturing the motion was more than 30% (up to 130%) in all subjects. The variable time (2) and amplitude (4) methods had a more uniform noise distribution among all respiratory gates compared to equal time (1) and amplitude (3) methods. Baseline correction did not improve the results. Out of seven different respiratory gating approaches, the variable amplitude method (4) captures the respiratory motion best while keeping a constant noise level among all respiratory phases.

Purpose We investigated the added value of a new respiratory amplitude-based PET reconstruction method called optimal gating (OG) with the aim of providing accurate image quantification in lung cancer. Methods FDG-PET imaging was performed in 26 lung cancer patients during free breathing using a 24-min list-mode acquisition on a PET/CT scanner. The data were reconstructed using three methods: standard 3D PET, respiratory-correlated 4D PET using a phase-binning algorithm, and OG. These datasets were compared in terms of the maximum SUV (SUVmax) in the primary tumour (main endpoint), noise characteristics, and volumes using thresholded regions of SUV 2.5 and 40% of the SUVmax. Results SUVmax values from the 4D method (13.7 ± 5.6) and the OG method (14.1 ± 6.5) were higher (4.9 ± 4.8%, p < 0.001 and 6.9 ± 8.8%, p < 0.001, respectively) than that from the 3D method (13.1 ± 5.4). SUVmax did not differ between the 4D and OG methods (2.0 ± 8.4%, p = NS). Absolute and relative threshold volumes did not differ between methods, except for the 40% SUVmax volume in which the value from the 3D method was lower than that from the 4D method (−5.3 ± 7.1%, p = 0.007). The OG method exhibited less noise than the 4D method. Variations in volumes and SUVmax of up to 40% and 27%, respectively, of the individual gates of the 4D method were also observed. Conclusion The maximum SUVs from the OG and 4D methods were comparable and significantly higher than that from the 3D method, yet the OG method was visibly less noisy than the 4D method. Based on the better quantification of the maximum and the less noisy appearance, we conclude that OG PET is a better alternative to both 3D PET, which suffers from breathing averaging, and the noisy images of a 4D PET.