PURPOSE: To investigate differences in volumetric measurement of pulmonary nodules caused by changing the reconstruction parameters for multi-detector row CT. MATERIALS AND METHODS: Thirty-nine pulmonary nodules less than 2 cm in diameter were examined by multi-slice CT. All nodules were solid, and located in the peripheral part of the lungs. The resultant 48 parameters images were reconstructed by changing slice thickness (1.25, 2.5, 3.75, or 5 mm), field of view (FOV: 10, 20, or 30 cm), algorithm (high-spatial frequency algorithm or low-spatial frequency algorithm) and reconstruction interval (reconstruction with 50% overlapping of the reconstructed slices or non-overlapping reconstruction). Volumetric measurements were calculated using commercially available software. The differences between nodule volumes were analyzed by the Kruskal-Wallis test and the Wilcoxon Signed-Ranks test. RESULTS: The diameter of the nodules was 8.7+/-2.7 mm on average, ranging from 4.3 to 16.4mm. Pulmonary nodule volume did not change significantly with changes in slice thickness or FOV (p>0.05), but was significantly larger with the high-spatial frequency algorithm than the low-spatial frequency algorithm (p<0.05), except for one reconstruction parameter. The volumes determined by non-overlapping reconstruction were significantly larger than those of overlapping reconstruction (p<0.05), except for a 1.25 mm thickness with 10 cm FOV with the high-spatial frequency algorithm, and 5mm thickness. The maximum difference in measured volume was 16% on average between the 1.25 mm slice thickness/10 cm FOV/high-spatial frequency algorithm parameters and overlapping reconstruction. CONCLUSION: Volumetric measurements of pulmonary nodules differ with changes in the reconstruction parameters, with a tendency toward larger volumes in high-spatial frequency algorithm and non-overlapping reconstruction compared to the low-spatial frequency algorithm and overlapping reconstruction.
PURPOSE: To investigate differences in volumetric measurement of pulmonary nodules caused by changing the reconstruction parameters for multi-detector row CT. MATERIALS AND METHODS: Thirty-nine pulmonary nodules less than 2 cm in diameter were examined by multi-slice CT. All nodules were solid, and located in the peripheral part of the lungs. The resultant 48 parameters images were reconstructed by changing slice thickness (1.25, 2.5, 3.75, or 5 mm), field of view (FOV: 10, 20, or 30 cm), algorithm (high-spatial frequency algorithm or low-spatial frequency algorithm) and reconstruction interval (reconstruction with 50% overlapping of the reconstructed slices or non-overlapping reconstruction). Volumetric measurements were calculated using commercially available software. The differences between nodule volumes were analyzed by the Kruskal-Wallis test and the Wilcoxon Signed-Ranks test. RESULTS: The diameter of the nodules was 8.7+/-2.7 mm on average, ranging from 4.3 to 16.4mm. Pulmonary nodule volume did not change significantly with changes in slice thickness or FOV (p>0.05), but was significantly larger with the high-spatial frequency algorithm than the low-spatial frequency algorithm (p<0.05), except for one reconstruction parameter. The volumes determined by non-overlapping reconstruction were significantly larger than those of overlapping reconstruction (p<0.05), except for a 1.25 mm thickness with 10 cm FOV with the high-spatial frequency algorithm, and 5mm thickness. The maximum difference in measured volume was 16% on average between the 1.25 mm slice thickness/10 cm FOV/high-spatial frequency algorithm parameters and overlapping reconstruction. CONCLUSION: Volumetric measurements of pulmonary nodules differ with changes in the reconstruction parameters, with a tendency toward larger volumes in high-spatial frequency algorithm and non-overlapping reconstruction compared to the low-spatial frequency algorithm and overlapping reconstruction.
Authors: M F Rinaldi; T Bartalena; L Braccaioli; N Sverzellati; S Mattioli; E Rimondi; G Rossi; M Zompatori; G Battista; R Canini Journal: Radiol Med Date: 2010-01-15 Impact factor: 3.469
Authors: James G Ravenel; William M Leue; Paul J Nietert; James V Miller; Katherine K Taylor; Gerard A Silvestri Journal: Radiology Date: 2008-05 Impact factor: 11.105
Authors: Jane P Ko; Erika J Berman; Manmeen Kaur; James S Babb; Elan Bomsztyk; Alissa K Greenberg; David P Naidich; Henry Rusinek Journal: Radiology Date: 2011-12-09 Impact factor: 11.105