Xin Sui1, Felix G Meinel2, Wei Song3, Xiaoli Xu4, Zixing Wang5, Yuyan Wang6, Zhengyu Jin7, Jiuhong Chen8, Rozemarijn Vliegenthart9, U Joseph Schoepf10. 1. Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China. Electronic address: lena_sui@163.com. 2. Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich, Germany. Electronic address: felix.meinel@gmail.com. 3. Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China. 4. Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China. Electronic address: xxllpositive@163.com. 5. Department of Epidemiology and Biostatistics, Institute of Basic Medical Science, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China. Electronic address: wangzi969@126.com. 6. Department of Epidemiology and Biostatistics, Institute of Basic Medical Science, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China. Electronic address: yuyang@163.com. 7. Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China. Electronic address: jin_zhengyu@163.com. 8. Siemens China, Beijing, China. Electronic address: jiuhong.chen@siemens.com. 9. Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; University of Groningen, University Medical Center Groningen, Center for Medical Imaging-North East Netherlands, Department of Radiology, Groningen, The Netherlands. Electronic address: r.vliegenthart@umcg.nl. 10. Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA. Electronic address: schoepf@musc.edu.
Abstract
BACKGROUND: In this study, the accuracy of ultra-low-dose computed tomography (CT) with iterative reconstruction (IR) for detection and measurement of pulmonary nodules was evaluated. METHODS: Eighty-four individuals referred for lung cancer screening (mean age: 54.5±10.8 years) underwent low-dose computed tomography (LDCT) and ultra-low-dose CT. CT examinations were performed with attenuation-based tube current modulation. Reference tube voltage and current were set to 120kV/25mÅs for LDCT and 80kV/4mÅs for ultra-low-dose CT. CT images were reconstructed with filtered back projection (FBP) for LDCT, and with FBP and IR for ultra-low-dose CT datasets. A reference standard was established by a consensus panel of 2 different radiologists on LDCT. Volume and diameter of the solid nodules were measured on LDCT with FBP and ultra-low dose CT with FBP and IR. Interobserver and interscan variability were analyzed and compared by the Bland-Altman method. RESULTS: A total of 127 nodules were identified, including 105 solid nodules, 15 part solid nodules, 7 ground glass nodules. On ultra-low-dose CT scans, the effective radiation dose was 0.13±0.11mSv. A total of 113 (88.9%) and 110 (86.6%) true-positive nodules with FBP versus 117 (92.1%) and 118(92.9%) with IR were detected by two observers, respectively. The volume and size of the 105 solid nodules were measured, with mean volume/diameter of 46.5±46.6 mm(3)/5.1±1.6mm. There was no significant difference in nodule volume or diameter measurements between ultra-low-dose CT and LDCT protocols for solid nodules. CONCLUSIONS: Ultra-low-dose CT with iterative reconstruction has high sensitivity for lung nodule detection without significant difference in nodule size and volume measurement compared to LDCT.
BACKGROUND: In this study, the accuracy of ultra-low-dose computed tomography (CT) with iterative reconstruction (IR) for detection and measurement of pulmonary nodules was evaluated. METHODS: Eighty-four individuals referred for lung cancer screening (mean age: 54.5±10.8 years) underwent low-dose computed tomography (LDCT) and ultra-low-dose CT. CT examinations were performed with attenuation-based tube current modulation. Reference tube voltage and current were set to 120kV/25mÅs for LDCT and 80kV/4mÅs for ultra-low-dose CT. CT images were reconstructed with filtered back projection (FBP) for LDCT, and with FBP and IR for ultra-low-dose CT datasets. A reference standard was established by a consensus panel of 2 different radiologists on LDCT. Volume and diameter of the solid nodules were measured on LDCT with FBP and ultra-low dose CT with FBP and IR. Interobserver and interscan variability were analyzed and compared by the Bland-Altman method. RESULTS: A total of 127 nodules were identified, including 105 solid nodules, 15 part solid nodules, 7 ground glass nodules. On ultra-low-dose CT scans, the effective radiation dose was 0.13±0.11mSv. A total of 113 (88.9%) and 110 (86.6%) true-positive nodules with FBP versus 117 (92.1%) and 118(92.9%) with IR were detected by two observers, respectively. The volume and size of the 105 solid nodules were measured, with mean volume/diameter of 46.5±46.6 mm(3)/5.1±1.6mm. There was no significant difference in nodule volume or diameter measurements between ultra-low-dose CT and LDCT protocols for solid nodules. CONCLUSIONS: Ultra-low-dose CT with iterative reconstruction has high sensitivity for lung nodule detection without significant difference in nodule size and volume measurement compared to LDCT.
Authors: Caroline Alexandra Burgard; Thomas Gaass; Madeleine Bonert; David Bondesson; Natalie Thaens; Maximilian Ferdinand Reiser; Julien Dinkel Journal: PLoS One Date: 2018-01-03 Impact factor: 3.240
Authors: Inge A H van den Berk; Maadrika M N P Kanglie; Tjitske S R van Engelen; Shandra Bipat; Marcel G W Dijkgraaf; Patrick M M Bossuyt; Wouter de Monyé; Jan M Prins; Jaap Stoker Journal: Diagn Progn Res Date: 2018-08-08