OBJECTIVES: To optimize the slice thickness/overlap parameters for image reconstruction and to study the effect of iterative reconstruction (IR) on detectability and characterization of small non-calcified pulmonary nodules during low-dose thoracic CT. MATERIALS AND METHODS: Data was obtained from computer simulations, phantom, and patient CTs. Simulations and phantom CTs were performed with 9 nodules (5, 8, and 10 mm with 100, -630, and -800 HU). Patient data were based on 11 ground glass opacities (GGO) and 9 solid nodules. For each analysis the nodules were reconstructed with filtered back projection and IR algorithms using 10 different combinations of slice thickness/overlap (0.5-5 mm). The attenuation (CT#) and the contrast to noise ratio (CNR) were measured. Spearman's coefficient was used to correlate the error in CT# measurements and slice thickness. Paired Student's t test was used to measure the significance of the errors. RESULTS: CNR measurements: CNR increases with increasing slice thickness/overlap for large nodules and peaks at 4.0/2.0 mm for smaller ones. Use of IR increases the CNR of GGOs by 60 %. CT# measurements: Increasing slice thickness/overlap above 3.0/1.5 mm results in decreased CT# measurement accuracy. CONCLUSION: Optimal detection of small pulmonary nodules requires slice thickness/overlap of 4.0/2.0 mm. Slice thickness/overlap of 2.0/2.0 mm is required for optimal nodule characterization. IR improves conspicuity of small ground glass nodules through a significant increase in nodule CNR. KEY POINTS: • Slice thickness/overlap affects the accuracy of pulmonary nodule detection and characterization. • Slice thickness ≥3 mm increases the risk of misclassifying small nodules. • Optimal nodule detection during low-dose CT requires 4.0/2.0-mm reconstructions. • Optimal nodule characterization during low-dose CT requires 2.0/2.0-mm reconstructions. • Iterative reconstruction improves the CNR of ground glass nodules by 60 %.
OBJECTIVES: To optimize the slice thickness/overlap parameters for image reconstruction and to study the effect of iterative reconstruction (IR) on detectability and characterization of small non-calcified pulmonary nodules during low-dose thoracic CT. MATERIALS AND METHODS: Data was obtained from computer simulations, phantom, and patient CTs. Simulations and phantom CTs were performed with 9 nodules (5, 8, and 10 mm with 100, -630, and -800 HU). Patient data were based on 11 ground glass opacities (GGO) and 9 solid nodules. For each analysis the nodules were reconstructed with filtered back projection and IR algorithms using 10 different combinations of slice thickness/overlap (0.5-5 mm). The attenuation (CT#) and the contrast to noise ratio (CNR) were measured. Spearman's coefficient was used to correlate the error in CT# measurements and slice thickness. Paired Student's t test was used to measure the significance of the errors. RESULTS: CNR measurements: CNR increases with increasing slice thickness/overlap for large nodules and peaks at 4.0/2.0 mm for smaller ones. Use of IR increases the CNR of GGOs by 60 %. CT# measurements: Increasing slice thickness/overlap above 3.0/1.5 mm results in decreased CT# measurement accuracy. CONCLUSION: Optimal detection of small pulmonary nodules requires slice thickness/overlap of 4.0/2.0 mm. Slice thickness/overlap of 2.0/2.0 mm is required for optimal nodule characterization. IR improves conspicuity of small ground glass nodules through a significant increase in nodule CNR. KEY POINTS: • Slice thickness/overlap affects the accuracy of pulmonary nodule detection and characterization. • Slice thickness ≥3 mm increases the risk of misclassifying small nodules. • Optimal nodule detection during low-dose CT requires 4.0/2.0-mm reconstructions. • Optimal nodule characterization during low-dose CT requires 2.0/2.0-mm reconstructions. • Iterative reconstruction improves the CNR of ground glass nodules by 60 %.
Authors: P Therasse; S G Arbuck; E A Eisenhauer; J Wanders; R S Kaplan; L Rubinstein; J Verweij; M Van Glabbeke; A T van Oosterom; M C Christian; S G Gwyther Journal: J Natl Cancer Inst Date: 2000-02-02 Impact factor: 13.506
Authors: B M Gramer; D Muenzel; V Leber; A-K von Thaden; H Feussner; A Schneider; M Vembar; N Soni; E J Rummeny; A M Huber Journal: Eur Radiol Date: 2012-07-03 Impact factor: 5.315
Authors: Heber MacMahon; John H M Austin; Gordon Gamsu; Christian J Herold; James R Jett; David P Naidich; Edward F Patz; Stephen J Swensen Journal: Radiology Date: 2005-11 Impact factor: 11.105
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: C I Henschke; D I McCauley; D F Yankelevitz; D P Naidich; G McGuinness; O S Miettinen; D M Libby; M W Pasmantier; J Koizumi; N K Altorki; J P Smith Journal: Lancet Date: 1999-07-10 Impact factor: 79.321