PURPOSE: We investigated the magnitude of respiratory-induced errors in tumor maximum standardized uptake value (SUVmax), localization, and volume for different respiratory motion traces and various lesion sizes in different locations of the thorax and abdomen in positron emission tomography (PET) images. PROCEDURES: Respiratory motion traces were simulated based on the common patient breathing cycle and three diaphragm motions used to drive the 4D XCAT phantom. Lesions with different diameters were simulated in different locations of lungs and liver. The generated PET sinograms were subsequently corrected using computed tomography attenuation correction involving the end exhalation, end inhalation, and average of the respiratory cycle. By considering respiration-averaged computed tomography as a true value, the lesion volume, displacement, and SUVmax were measured and analyzed for different respiratory motions. RESULTS: Respiration with 35-mm diaphragm motion results in a mean lesion SUVmax error of 24 %, a mean superior inferior displacement of 7.6 mm and a mean lesion volume overestimation of 129 % for a 9-mm lesion in the liver. Respiratory motion results in lesion volume overestimation of 50 % for a 9-mm lower lung lesion near the liver with just 15-mm diaphragm motion. Although there are larger errors in lesion SUVmax and volume for 35-mm motion amplitudes, respiration-averaged computed tomography results in smaller errors than the other two phases, except for the lower lung region. CONCLUSIONS: The respiratory motion-induced errors in tumor quantification and delineation are highly dependent upon the motion amplitude, tumor location, tumor size, and choice of the attenuation map for PET image attenuation correction.
PURPOSE: We investigated the magnitude of respiratory-induced errors in tumor maximum standardized uptake value (SUVmax), localization, and volume for different respiratory motion traces and various lesion sizes in different locations of the thorax and abdomen in positron emission tomography (PET) images. PROCEDURES: Respiratory motion traces were simulated based on the common patient breathing cycle and three diaphragm motions used to drive the 4D XCAT phantom. Lesions with different diameters were simulated in different locations of lungs and liver. The generated PET sinograms were subsequently corrected using computed tomography attenuation correction involving the end exhalation, end inhalation, and average of the respiratory cycle. By considering respiration-averaged computed tomography as a true value, the lesion volume, displacement, and SUVmax were measured and analyzed for different respiratory motions. RESULTS: Respiration with 35-mm diaphragm motion results in a mean lesion SUVmax error of 24 %, a mean superior inferior displacement of 7.6 mm and a mean lesion volume overestimation of 129 % for a 9-mm lesion in the liver. Respiratory motion results in lesion volume overestimation of 50 % for a 9-mm lower lung lesion near the liver with just 15-mm diaphragm motion. Although there are larger errors in lesion SUVmax and volume for 35-mm motion amplitudes, respiration-averaged computed tomography results in smaller errors than the other two phases, except for the lower lung region. CONCLUSIONS: The respiratory motion-induced errors in tumor quantification and delineation are highly dependent upon the motion amplitude, tumor location, tumor size, and choice of the attenuation map for PET image attenuation correction.
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