Pulmonary nodules: Effect of adaptive statistical iterative reconstruction (ASIR) technique on performance of a computer-aided detection (CAD) system - Comparison of performance between different-dose CT scans

European Journal of Radiology

Volumn 81, Issue 10, 2012, Pages 2877-2886

  Yanagawa, Masahiro ^a   Honda, Osamu ^a   Kikuyama, Ayano ^a   Gyobu, Tomoko ^a   Sumikawa, Hiromitsu ^a   Koyama, Mitsuhiro ^a   Tomiyama, Noriyuki ^a  

^a OSAKA UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

Author keywords

Adaptive statistical iterative reconstruction (ASIR); Chest CT; Computer aided detection (CAD); Radiation dose

Indexed keywords

ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION; ADULT; AGED; ARTICLE; BODY MASS; CLINICAL ARTICLE; COMPUTED TOMOGRAPHY SCANNER; COMPUTER AIDED DETECTION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED STUDY; DIAGNOSTIC TEST ACCURACY STUDY; FALSE POSITIVE RESULT; FEMALE; HUMAN; IMAGE RECONSTRUCTION; IMAGING SYSTEM; INTERMETHOD COMPARISON; LUNG NODULE; MALE; MULTIDETECTOR COMPUTED TOMOGRAPHY; PRIORITY JOURNAL; RADIATION DOSE; SENSITIVITY AND SPECIFICITY;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; MALE; MIDDLE AGED; RADIATION DOSAGE; RADIATION PROTECTION; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOLITARY PULMONARY NODULE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84865219227     PISSN: 0720048X     EISSN: 18727727     Source Type: Journal    
DOI: 10.1016/j.ejrad.2011.09.011     Document Type: Article

References (27)

1. M. Yanagawa, N. Tomiyama, and H. Osamu Multidetector CT of the lung: image quality with garnet-based detectors Radiology 255 3 2010 944 954
2. K. Knesaurek, J. Machac, and S. Vallabhajosula A new iterative reconstruction technique for attenuation correction in high-resolution positron emission tomography Eur J Nucl Med 23 6 1996 656 661
3. P. Prakash, M.K. Kalra, and J.B. Ackman Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique Radiology 256 1 2010 261 269
4. S. Singh, M.K. Kalra, and J. Hsieh Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques Radiology 257 2 2010 373 383
5. D. Marin, R.C. Nelson, and S.T. Schindera Low-tube-voltage, hightube-current multidetector abdominal CT: improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm - initial clinical experience Radiology 254 1 2010 145 153
6. P. Prakash, M.K. Kalra, and S.R. Digumarthy Radiation dose reduction with chest computed tomography using adaptive statistical iterative reconstruction technique: initial experience J Comput Assist Tomogr 34 1 2010 40 45
7. J. Leipsic, G. Nguyen, J. Brown, D. Sin, and J.R. Mayo A prospective evaluation of dose reduction and image quality in chest CT using adaptive statistical iterative reconstruction AJR Am J Roentgenol 195 5 2010 1095 1099
8. A.C. Silva, H.J. Lawder, A. Hara, J. Kujak, and W. Pavlicek Innovations in CT dose reduction strategy: application of the adaptive statistical iterative reconstruction algorithm AJR Am J Roentgenol 194 1 2010 191 199
9. M. Yanagawa, O. Honda, and S. Yoshida Commercially available computer-aided detection system for pulmonary nodules on thin-section images using 64 detectors-row CT: preliminary study of 48 cases Acad Radiol 16 8 2009 924 933
10. J.H. Austin, N.L. Müller, and P.J. Friedman Glossary of terms for CT of the lungs: recommendations of the Nomenclature Committee of the Fleischner Society Radiology 200 2 1996 327 331
11. Christner JA, Kofler JM, McCollough CH. Estimating effective dose for CT using dose-length product compared with using organ doses: consequences of adopting International Commission on Radiological Protection publication 103 or dual-energy scanning. AJR Am J Roentgenol 194:881-89. Erratum in: AJR Am J Roentgenol 2010; 194(4):1404.
12. M. Yanagawa, N. Tomiyama, and H. Sumikawa Thin-section CT of lung without ECG gating: 64-detector row CT can markedly reduce cardiac motion artifact which can simulate lung lesions Eur J Radiol 69 1 2009 102 107
13. J.S. Kim, J.H. Kim, G. Cho, and K.T. Bae Automated detection of pulmonary nodules on CT images: effect of section thickness and reconstruction interval-initial results Radiology 236 1 2005 295 299
14. F. Beyer, L. Zierott, and E.M. Fallenberg Comparison of sensitivity and reading time for the use of computer-aided detection (CAD) of pulmonary nodules at MDCT as concurrent or second reader Eur Radiol 17 11 2007 2941 2947
15. B. Sahiner, H.P. Chan, and L.M. Hadjiiski Effect of CAD on radiologists' detection of lung nodules on thoracic CT scans: analysis of an observer performance study by nodule size Acad Radiol 16 12 2009 1518 1530
16. K. Marten, A. Grillhösl, T. Seyfarth, S. Obenauer, E.J. Rummeny, and C. Engelke Computer-assisted detection of pulmonary nodules: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings Eur Radiol 15 2 2005 203 212
17. G.D. Rubin, J.K. Lyo, and D.S. Paik Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection Radiology 234 1 2005 274 283
18. M. Das, G. Mühlenbruch, and A.H. Mahnken Small pulmonary nodules: effect of two computer-aided detection systems on radiologist performance Radiology 241 2 2006 564 571
19. T. Hirose, N. Nitta, and J. Shiraishi Evaluation of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector row computed tomography (MDCT): JAFROC study for the improvement in radiologists' diagnostic accuracy Acad Radiol 15 12 2008 1505 1512
20. Q. Li, F. Li, and K. Doi Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier Acad Radiol 15 2 2008 165 175
21. S.G. Armato 3rd, M.B. Altmann, and P.J. La Riviere Automated detection of lung nodules in CT scans: effect of image reconstruction algorithm Med Phys 30 6 2003 461 472
22. J. Hwang, M.J. Chung, Y. Bae, K.M. Shin, S.Y. Jeong, and K.S. Lee Computed-aided detection of lung nodules: influence of the image reconstruction kernel for computed-aided detection performance J Comput Assist Tomogr 34 1 2010 31 34
23. J.R. Mayo, W.R. Webb, and R. Gould High-resolution CT of the lungs: an optimal approach Radiology 163 2 1987 507 510
24. International Commission on Radiological Protection 1990 recommendations of the International Commission on Radiological Protection. ICRP publication 60 1991 Pergamon Oxford, England
25. C.I. Henschke, D.I. McCauley, and D.F. Yankelevitz Early lung cancer action project: overall design and findings from baseline screening Lancet 354 9173 1999 99 105
26. S.J. Swensen, J.R. Jett, and T.E. Hartman Lung cancer screening with CT: Mayo Clinic experience Radiology 226 3 2003 756 761
27. K. Suzuki A supervised 'lesion-enhancement' filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD) Phys Med Biol 54 18 2009 31 45