PT - JOURNAL ARTICLE AU - Kris Thielemans AU - Evren Asma AU - Ravindra Manjeshwar TI - Evaluation of image-based correction for mismatch between PET and CT on quantification of solitary pulmonary nodules with FDG DP - 2009 May 01 TA - Journal of Nuclear Medicine PG - 1512--1512 VI - 50 IP - supplement 2 4099 - http://jnm.snmjournals.org/content/50/supplement_2/1512.short 4100 - http://jnm.snmjournals.org/content/50/supplement_2/1512.full SO - J Nucl Med2009 May 01; 50 AB - 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 (<2s). Here we evaluate the effect of attenuation mismatch and the efficacy of the correction method on quantification of SPNs. 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.