ABSTRACT
The objective of this investigation is to determine the impact of respiratory motion on the detection of small solitary pulmonary nodules (SPN) in single photon emission computed tomographic (SPECT) imaging. We have previously modeled the respiratory motion of 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. This information on respiratory motion within the lungs was combined with the end-expiration and time-averaged NCAT phantoms to allow the creation of source and attenuation maps for the normal background distribution of Tc-99m NeoTect. With the source and attenuation distribution thus defined, the SIMIND Monte Carlo program was used to produce SPECT projection data for the normal background and separately for each of 150 end-expiration and time-averaged simulated 1.0 cm tumors. Normal and tumor SPECT projection sets each containing one lesion were combined with a clinically realistic noise level and counts. These were reconstructed with RBI-EM using 1) no correction (NC), 2) attenuation correction (AC), 3) detector response correction (RC), and 4) attenuation correction, detector response correction, and scatter correction (AC_RC_SC). The post-reconstruction parameters of number of iterations and 3-D Gaussian filtering were optimized by human-observer studies. Comparison of lesion detection by human-observer LROC studies reveals that respiratory motion degrades tumor detection for all four reconstruction strategies, and that the magnitude of this effect is greatest for NC and RC, and least for AC_RC_SC. Additionally, the AC_RC_SC strategy results in the best detection of lesions.
ABSTRACT
A human-model observer for tumor detection-localization studies featuring multislice-multiview (or volumetric) image displays has been introduced. This volumetric observer, an extension of multiclass linear observers previously tested with single-slice and multislice displays, produces rating and localization data by integrating perception measurements from the different image views. A channelized NPW (CNPW) version of the observer was evaluated against humans for a background-known-exactly (BKE) detection task involving localization of Tc-99m Neotect lesions in simulated SPECT lung images. An LROC study evaluated two RBI reconstruction strategies that used different combinations of corrections for attenuation, scatter, and distance-dependent system resolution, and coronal, sagittal, and transverse slices were presented to the observers. Model-observer ranking of these strategies did not match that of the humans. Follow-up studies exploring several possible remedies for the model observer, including strategy-specific search regions and an internal-noise mechanism, showed little change. Future work will examine variations from the BKE assumption as a means of reconciling the rankings.
