ABSTRACT
<p><b>OBJECTIVE</b>To investigate whether fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) combined with thin-section CT improves the diagnostic performance for solitary pulmonary nodules (SPNs).</p><p><b>METHODS</b>A total of 267 patients underwent examinations withF-FDG PET/CT and thin-section CT for evaluating the SPNs with undetermined nature, which was further confirmed by pathological examination or clinical follow-up. The performance of two diagnostic criteria based on findings in PET/CT alone (Criterion 1) and in PET/CT combined with thin-section CT (Criterion 2) were compared.</p><p><b>RESULTS</b>Thin-section CT provided greater diagnostic information for SPNs in 84.2% of the patients. Compared with Criterion 1, the diagnosis based on Criterion 2 significantly increased the diagnostic sensitivity (80.4% vs 91%, P<0.01) and accuracy (76.4% vs 87.2%, P<0.01) for lung cancer. The lesion size and the CT features including lobulation, air bronchogram, and feeding vessel, but not SUVmax, were all helpful for characterizing non-solid SPNs. Thin-section CT rectified diagnostic errors in 50% (20/40) of the cancerous lesions, which had been diagnosed as benign by PET due to their low metabolism. For non-solid SPNs, Criterion 2 showed a significantly higher diagnostic sensitivity than Criterion 1 (90.0% vs 40.0%, P=0.000) but their diagnostic specificity were comparable (75.2% vs 58.3%, P=0.667). For solid nodules, the use of thin-section CT resulted in no significant improvement in the diagnostic performance (P<0.05).</p><p><b>CONCLUSION</b>The combination of PET/CT and thin-section CT creates a synergistic effect for the characterization of SPNs, especially non-solid nodules.</p>
ABSTRACT
We propose a method using total variation (TV) regularization in deconvolution for partial volume correction in PET imaging. In the degraded image model, we used TV regularization procedure in Van Cittert (VC) and Richardson-Lucy (RL) deconvolution algorithms. These methods were tested in simulated NCAT images and images of NEMA NU4-2008 IQ phantom and tumor-bearing mouse scanned by Simens Invoen microPET. The simulated experiment and tumor-bearing mouse experiment showed that the algorithms using TV regularization provided superior qualitative and quantitative appearance compared with traditional VC and RL algorithms. When the mean intensity of the tumor increased by (10±1.8)%, the SD increase percentage was decreased from 49.98% to 14.26% and from 42.76% to 4.70%, suggesting the efficiency of the proposed algorithms for reducing PVEs in PET.