Impact of respiratory motion on the detection of solitary pulmonary nodules with SPECT tumor imaging of NeoTect
We have previously modeled the respiratory motion of solitary pulmonary nodules (SPN) based on the change of location of anatomic structures within the lungs identified on breath-held CT images of volunteers acquired at two different stages of respiration. The goal of this investigation is to make use of this modeling to investigate the impact of respiratory motion on the detection of solitary pulmonary nodules with single photon emission computed tomographic (SPECT) imaging using Tc-99m labeled NeoTect. To do this, end-expiration and respiration-averaged source and attenuation maps were created from the NCAT phantom and input to the SIMIND Monte Carlo package. Normal and SPECT projection sets containing lesions at 75 different locations were created with a clinically realistic noise level. One third of the locations were in the superior, middle, and inferior portion of the lungs to allow assessment of detection accuracy relative to the regional site of the lesion. These are reconstructed with filtered backprojection followed by 3D post-Butterworth filtering and with RBI using attenuation, scatter and resolution compensation followed by 3D post-Gaussian filtering. Herein, we report on the optimization of the reconstruction parameters by numerical-observer studies. Comparison of lesion detection by human-observer localization receiver operating characteristics (LROC) studies will then be made as a function of reconstruction strategy and lesion location, and for with and without the presence of respiratory motion.
