MO-D-141-02: Evaluation of Optimal Gating Respiratory Motion Management Technique On PET Quantification.
PURPOSE
To evaluate the uncertainty of PET quantification resulting from irregular breathing patterns when optimal gating (HD-Chest) acquisition is performed on a Siemens Biograph PET-CT scanner.


METHODS
A NEMA phantom containing spherical VOIs (Volumes-of-Interest) with diameters of 28, 22, 17, 13, and 10 mm was scanned on a moving platform. Seven breathing traces that were previously recorded optically from lung PET patients and one synthetic regular trace were used to drive the platform. Motion amplitudes for individual traces were 5∼20 mm peak-to-peak with intra-traces amplitude variances ranging between 1.6 mm to 10.3 mm. For each trace, the average (SUVavg) and maximum (SUVmax) standard uptake values within the VOIs were calculated. VOIs volumes were also evaluated at a threshold equal to 10% of SUVmax. Relative percent deviations of these parameters from ground truth values derived from a static acquisition were calculated.


RESULTS
The average deviations for all patient breathing patterns were 10.5% (SD=5.9%), 11% (SD=7.9%), and 9% (SD=9.3%) for volume, SUVavg, and SUVmax, respectively. The average deviations for the regular breathing pattern were 3.8%, 5.2%, and 6.6% for volume, SUVavg, and SUVmax, respectively. VOI size significantly affected the uncertainty. For the 28 mm VOI the average deviations were 6.9%, 6.6%, and 2.7% for volume, SUVavg, and SUVmax, respectively while for the 10 mm VOI these were 11.8%, 15.1%, and 19.3% for volume, SUVavg, and SUVmax, respectively. Without any breathing motion management technique in place, the average deviations for the regular breathing pattern were 16.6%, 42.8%, and 42.4% for volume, SUVavg, and SUVmax, respectively.


CONCLUSION
The optimal gating (HD-Chest) technique improved the PET quantification. However, one needs to take the residual deviations for regular and for all irregular breathing patterns into account for PET quantification. M. Casey and R. Rajaram are the employees of Siemens Medical Solutions.