Tae Iwasawa1, Tetsu Kanauchi2, Toshiko Hoshi2,3, Takashi Ogura4, Tomohisa Baba4, Toshiyuki Gotoh5, Mari S Oba6. 1. Department of Radiology, Kanagawa Cardiovascular and Respiratory Center, 6-16-1, Tomioka-higashi, Kanazawa-ku, Yokohama, Kanagawa, 236-8651, Japan. tae_i_md@wb3.so-net.ne.jp. 2. Department of Radiology, Saitama Cardiovascular and Respiratory Center, Saitama, Japan. 3. Department of Radiology, Saitama Jikei Hospital, Saitama, Japan. 4. Department of Respiratory Medicine, Kanagawa Cardiovascular and Respiratory Center, Kanagawa, Japan. 5. Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan. 6. Department of Biostatistics and Epidemiology, School of Medicine, Yokohama City University, Yokohama, Japan.
Abstract
PURPOSE: To evaluate the feasibility of automated quantitative analysis with a three-dimensional (3D) computer-aided system (i.e., Gaussian histogram normalized correlation, GHNC) of computed tomography (CT) images from different scanners. MATERIALS AND METHODS: Each institution's review board approved the research protocol. Informed patient consent was not required. The participants in this multicenter prospective study were 80 patients (65 men, 15 women) with idiopathic pulmonary fibrosis. Their mean age was 70.6 years. Computed tomography (CT) images were obtained by four different scanners set at different exposures. We measured the extent of fibrosis using GHNC, and used Pearson's correlation analysis, Bland-Altman plots, and kappa analysis to directly compare the GHNC results with manual scoring by radiologists. Multiple linear regression analysis was performed to determine the association between the CT data and forced vital capacity (FVC). RESULTS: For each scanner, the extent of fibrosis as determined by GHNC was significantly correlated with the radiologists' score. In multivariate analysis, the extent of fibrosis as determined by GHNC was significantly correlated with FVC (p < 0.001). There was no significant difference between the results obtained using different CT scanners. CONCLUSION: Gaussian histogram normalized correlation was feasible, irrespective of the type of CT scanner used.
PURPOSE: To evaluate the feasibility of automated quantitative analysis with a three-dimensional (3D) computer-aided system (i.e., Gaussian histogram normalized correlation, GHNC) of computed tomography (CT) images from different scanners. MATERIALS AND METHODS: Each institution's review board approved the research protocol. Informed patient consent was not required. The participants in this multicenter prospective study were 80 patients (65 men, 15 women) with idiopathic pulmonary fibrosis. Their mean age was 70.6 years. Computed tomography (CT) images were obtained by four different scanners set at different exposures. We measured the extent of fibrosis using GHNC, and used Pearson's correlation analysis, Bland-Altman plots, and kappa analysis to directly compare the GHNC results with manual scoring by radiologists. Multiple linear regression analysis was performed to determine the association between the CT data and forced vital capacity (FVC). RESULTS: For each scanner, the extent of fibrosis as determined by GHNC was significantly correlated with the radiologists' score. In multivariate analysis, the extent of fibrosis as determined by GHNC was significantly correlated with FVC (p < 0.001). There was no significant difference between the results obtained using different CT scanners. CONCLUSION: Gaussian histogram normalized correlation was feasible, irrespective of the type of CT scanner used.
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