Evaluation of image-based correction for mismatch between PET and CT on quantification of solitary pulmonary nodules with FDG

1512 Objectives Respiration causes mismatch between CT and PET images, affecting PET quantification. We have recently developed an image-based method to correct for known errors in the attenuation factors. The method does not need re-reconstruction and is fast ( Methods Respiratory-gated CT and FDG-PET data were acquired on 5 patients at San Raffaele Hospital, Milan using a GE DSTE PET/CT scanner and Varian RPM tracking device. CT and PET data were gated into 6 matching phases. Each PET gate was reconstructed using each CT gate, introducing mismatch in 5 images for each PET gate. These images were corrected based on the difference of the mismatched and matched attenuation images. 9 lesions were segmented on each image, and meanSUV and volume was computed. The effect of attenuation mismatch was analyzed with the following metrics: 1) for every PET gate, the relative Root Mean Square Error (RRMSE) of the 5 mismatched data sets was computed and then averaged over all 6 PET gates; 2) the maximum relative error (maxRE). Results Segmented lesion volumes were 1-4cc, while maximum lesion displacement ranged between 6-12 mm. Conclusions Using CT data of a different respiration stage for attenuation correction affects quantification of SPNs. Changes in SUV values depend on the amount of motion and the surrounding tissue. The image-based correction decreased average variability in meanSUV from 7% to 3%. As the method is fast, it shows great potential for interactive correction of PET images for misalignment with CT.