OBJECTIVE: The purpose of this study is to investigate the effect of a novel reconstruction algorithm, adaptive iterative dose reduction using 3D processing, on emphysema quantification by low-dose CT. MATERIALS AND METHODS: Twenty-six patients who had undergone standard-dose (150 mAs) and low-dose (25 mAs) CT scans were included in this retrospective study. Emphysema was quantified by several quantitative measures, including emphysema index given by the percentage of lung region with low attenuation (lower than -950 HU), the 15th percentile of lung density, and size distribution of low-attenuation lung regions, on standard-dose CT images reconstructed without adaptive iterative dose reduction using 3D processing and on low-dose CT images reconstructed both without and with adaptive iterative dose reduction using 3D processing. The Bland-Altman analysis was used to assess whether the agreement between emphysema quantifications on low-dose CT and on standard-dose CT was improved by the use of adaptive iterative dose reduction using 3D processing. RESULTS: For the emphysema index, the mean differences between measurements on low-dose CT and on standard-dose CT were 1.98% without and -0.946% with the use of adaptive iterative dose reduction using 3D processing. For 15th percentile of lung density, the mean differences without and with adaptive iterative dose reduction using 3D processing were -6.67 and 1.28 HU, respectively. For the size distribution of low-attenuation lung regions, the ranges of the mean relative differences without and with adaptive iterative dose reduction using 3D processing were 21.4-85.5% and -14.1% to 11.2%, respectively. For 15th percentile of lung density and the size distribution of low-attenuation lung regions, the agreement was thus improved by the use of adaptive iterative dose reduction using 3D processing. CONCLUSION: The use of adaptive iterative dose reduction using 3D processing resulted in greater consistency of emphysema quantification by low-dose CT, with quantification by standard-dose CT.
OBJECTIVE: The purpose of this study is to investigate the effect of a novel reconstruction algorithm, adaptive iterative dose reduction using 3D processing, on emphysema quantification by low-dose CT. MATERIALS AND METHODS: Twenty-six patients who had undergone standard-dose (150 mAs) and low-dose (25 mAs) CT scans were included in this retrospective study. Emphysema was quantified by several quantitative measures, including emphysema index given by the percentage of lung region with low attenuation (lower than -950 HU), the 15th percentile of lung density, and size distribution of low-attenuation lung regions, on standard-dose CT images reconstructed without adaptive iterative dose reduction using 3D processing and on low-dose CT images reconstructed both without and with adaptive iterative dose reduction using 3D processing. The Bland-Altman analysis was used to assess whether the agreement between emphysema quantifications on low-dose CT and on standard-dose CT was improved by the use of adaptive iterative dose reduction using 3D processing. RESULTS: For the emphysema index, the mean differences between measurements on low-dose CT and on standard-dose CT were 1.98% without and -0.946% with the use of adaptive iterative dose reduction using 3D processing. For 15th percentile of lung density, the mean differences without and with adaptive iterative dose reduction using 3D processing were -6.67 and 1.28 HU, respectively. For the size distribution of low-attenuation lung regions, the ranges of the mean relative differences without and with adaptive iterative dose reduction using 3D processing were 21.4-85.5% and -14.1% to 11.2%, respectively. For 15th percentile of lung density and the size distribution of low-attenuation lung regions, the agreement was thus improved by the use of adaptive iterative dose reduction using 3D processing. CONCLUSION: The use of adaptive iterative dose reduction using 3D processing resulted in greater consistency of emphysema quantification by low-dose CT, with quantification by standard-dose CT.
Authors: N Sakai; H Yabuuchi; M Kondo; Y Matsuo; T Kamitani; M Nagao; M Jinnouchi; M Yonezawa; T Kojima; Y Yano; H Honda Journal: Br J Radiol Date: 2015-07-08 Impact factor: 3.039
Authors: John Hoffman; Nastaran Emaminejad; Muhammad Wahi-Anwar; Grace H Kim; Matthew Brown; Stefano Young; Michael McNitt-Gray Journal: Med Phys Date: 2019-04-03 Impact factor: 4.071
Authors: David A Lynch; John H M Austin; James C Hogg; Philippe A Grenier; Hans-Ulrich Kauczor; Alexander A Bankier; R Graham Barr; Thomas V Colby; Jeffrey R Galvin; Pierre Alain Gevenois; Harvey O Coxson; Eric A Hoffman; John D Newell; Massimo Pistolesi; Edwin K Silverman; James D Crapo Journal: Radiology Date: 2015-05-11 Impact factor: 11.105
Authors: Davide Chiumello; Thomas Langer; Vittoria Vecchi; Simone Luoni; Andrea Colombo; Matteo Brioni; Sara Froio; Irene Cigada; Silvia Coppola; Alessandro Protti; Marco Lazzerini; Luciano Gattinoni Journal: Intensive Care Med Date: 2014-03-20 Impact factor: 17.440
Authors: Hendrik Joost Wisselink; Gert Jan Pelgrim; Mieneke Rook; Maarten van den Berge; Kees Slump; Yeshu Nagaraj; Peter van Ooijen; Matthijs Oudkerk; Rozemarijn Vliegenthart Journal: Br J Radiol Date: 2019-11-28 Impact factor: 3.039