Abstract
Early detection and treatment of lung cancer is one of the most effective means of reducing cancer mortality, and to this end, chest X-ray radiography has been widely used as a screening method. A related technique based on the development of computer analysis and a flat panel detector (FPD) has enabled the functional evaluation of respiratory kinetics in the chest and is expected to be introduced into clinical practice in the near future. In this study, we developed a computer analysis algorithm to detect lung nodules and to evaluate quantitative kinetics. Breathing chest radiographs obtained by modified FPD and breath synchronization utilizing diaphragmatic analysis of vector movement were converted into four static images by sequential temporal subtraction processing, morphological enhancement processing, kinetic visualization processing, and lung region detection processing. An artificial neural network analyzed these density patterns to detect the true nodules and draw their kinetic tracks. Both the algorithm performance and the evaluation of clinical effectiveness of seven normal patients and simulated nodules showed sufficient detecting capability and kinetic imaging function without significant differences. Our technique can quantitatively evaluate the kinetic range of nodules and is effective in detecting a nodule on a breathing chest radiograph. Moreover, the application of this technique is expected to extend computer-aided diagnosis systems and facilitate the development of an automatic planning system for radiation therapy.










Similar content being viewed by others
References
Ministry of Health, Labour and Welfare: Annual Statistical Report of National Health Conditions, Tokyo: Health and Welfare Statistics Association, 2005
Tanaka R, Sanada S, Suzuki M, Matsui T, Uoyama Y: New method of screening chest radiography with computer analysis of respiratory kinetics. Nippon Hoshasen Gijutsu Gakkai Zasshi 58:665–669, 2002
Tanaka R, Sanada S, Kobayashi T, Suzuki M, Matsui T, Inoue H: Development of breathing chest radiography—study of exposure timing. Nippon Hoshasen Gijutsu Gakkai Zasshi 59:984–992, 2003
Tanaka R, Sanada S, Suzuki M, Matsui T, Uoyama Y: New screening chest radiography with computer analysis of pulmonary marking movement and change in regional density. Nippon Hoshasen Gijutsu Gakkai Zasshi 58:1489–1496, 2002
Tanaka R, Sanada S, Suzuki M, Kobayashi T, Matsui T, Inoue H, Yoshihisa N: Breathing chest radiography using a dynamic flat-panel detector (FPD) with computer analysis for a screening examination. Med Phys 31:2254–2262, 2004
Tanaka R, Sanada S, Kobayashi T, Suzuki M, Matsui T, Matsui O: Computerized methods for determining respiratory phase on dynamic chest radiographs obtained by a dynamic flat-panel detector (FPD) system. J Digit Imaging 19:41–51, 2006
Tanaka R, Sanada S, Okazaki N, Kobayashi T, Nakayama K, Matsui T, Hayashi N, Matsui O: Quantification and visualization of relative local ventilation on dynamic chest radiographs. Proc SPIE 6143:6143Y-1–6143Y-8, 2006
Kobayashi T, Xu X-W, MacMahon H, Metz CE, Doi K: Effect of an computer-aided diagnosis scheme on radiologists performance in detection of lung nodules on radiographs. Radiology 199:843–848, 1996
Aoyama M, Li Q, Katsuragawa S, MacMahon H, Doi K: Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images. Med Phys 29:701–708, 2002
Ishida TS, Katsuragawa K, Nakamura K, MacMahon H, Doi K: Iterative image warping technique for temporal subtraction of sequential chest radiographs to detect interval change. Med Phys 26:1320–1329, 1999
Kakeda S, Nakamura K, Kameda K, Watanabe H, Nakata H, Katsuragawa S, Doi K: Improved detection of lung nodules by using a temporal subtraction technique. Radiology 224:145–151, 2002
Wei J, Hagihara Y, Kobatake H: Convergence index filter for detection of lung nodule candidates. IEICE Trans Inf Syst D-II(1):118–125, 2000
Xu XW, Doi K: Image feature analysis for computer-aided diagnosis: accurate determination of ribcage boundary in chest radiographs. Med Phys 22:617–626, 1995
Li L, Zheng Y, Kallergi M, Clark RA: Improved method for automatic identification of lung region on chest radiographs. Acad Radiol 8:629–638, 2001
Tsuchiya Y, Kodera Y: Development of a kinetic analysis technique for PACS management and a screening examination in dynamic radiography. Nippon Hoshasen Gijutsu Gakkai Zasshi 61:1666–1674, 2005
Rosenblatt F: The perceptron: a probabilistic model for information storage and organization in the brain. Phychol Rev 65:386–408, 1958
Minsky M, Papert S: Preceptron, Cambridge, MA: MIT, 1969
Rumelhart DE, Hinton GE, Williams RJ: Learning internal representations by error propagation. In: Rumelhart DE, McClelland JL Eds. Parallel Distributed Processing: Explorations in the Microstructures of Cognition 1. Cambridge, MA: MIT, 1986, pp. 318–362
Chakraborty DP, Breatnach ES, Yester MV: Digital and conventional chest imaging: a method ROC study of observer performance using simulated nodules. Radiology 158:35–39, 1986
Chakraborty DP: Maximum likelihood analysis of free-response receiver operating characteristic (FROC) data. Med Phys 16:561–568, 1989
Shiraishi J, Kosakai K, Hatagata M, Higashida M, Watanabe S: Study of simple data sampling on free-response receiver operating (FROC) analysis. Nippon Hoshasen Gijutsu Gakkai Zasshi 47:620–626, 1991
Fujita H, Shimura K, Shiraishi J, Nishihara S, Higashida Y, Yamashita K: Fundamentals of ROC analysis and its recent progress. Nippon Hoshasen Gijutsu Gakkai Zasshi 49:1685–1703, 1993
Powell GF, Doi K, Katsuragawa S: Localization of inter-ribspaces for lung texture analysis and computer-aided diagnosis in digital chest images. Med Phys 15:581–587, 1988
International Commission on Radiation Units and Measurements: ICRU Report No. 62. Prescribing, Recording and Reporting Photon Beam Therapy (Supplement to ICRU Report 50), Bethesda, MD: ICRU, 1999
Acknowledgments
We would like to acknowledge the students of Kodera Laboratory, Nagoya University, Japan, for their cooperation in the experiments and helpful discussions.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Tsuchiya, Y., Kodera, Y., Tanaka, R. et al. Quantitative Kinetic Analysis of Lung Nodules Using the Temporal Subtraction Technique in Dynamic Chest Radiographies Performed with a Flat Panel Detector. J Digit Imaging 22, 126–135 (2009). https://doi.org/10.1007/s10278-008-9116-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10278-008-9116-1