Chisako Muramatsu1, Kazuki Horiba2, Tatsuro Hayashi3, Tatsumasa Fukui4, Takeshi Hara2, Akitoshi Katsumata4, Hiroshi Fujita2. 1. Department of Intelligent Image Information, Graduate School of Medicine, Gifu University, 1-1 Yanagido, Gifu, Gifu, 501-1194, Japan. chisa@fjt.info.gifu-u.ac.jp. 2. Department of Intelligent Image Information, Graduate School of Medicine, Gifu University, 1-1 Yanagido, Gifu, Gifu, 501-1194, Japan. 3. Media Co., Ltd, 3-26-6 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. 4. Department of Oral Radiology, Asahi University School of Dentistry, 1851 Hozumi, Mizuho, Gifu, 501-0296, Japan.
Abstract
PURPOSE: Studies reported that the mandibular cortical width (MCW) measured on dental panoramic radiographs (DPRs) was significantly correlated with bone mineral density. However, MCW is not a perfect index by itself, and studies suggest the added utility of mandibular cortical index (MCI). In this study, we propose a method for computerized estimation of mandibular cortical degree (MCD), a new continuous measure of MCI, for osteoporotic risk assessment. METHODS: The mandibular contour was automatically segmented using an active contour model. The regions of interest near mental foramen were extracted for MCW and MCD determination. The MCW was measured on the basis of residue-line detection results and pixel profiles. Image features including texture features based on gray-level co-occurrence matrices were determined. The MCD were estimated using support vector regression (SVR). The SVR was trained using previously collected 99 DPRs, including 26 osteoporotic cases, by a computed radiography system. The proposed scheme was tested using 99 DPRs obtained by a photon-counting system with data of bone mineral density at distal forearm. The number of osteoporotic, osteopenic, and control cases were 12, 18, and 69 cases, respectively. The subjective MCD by a dental radiologist was employed for training and evaluation. RESULTS: The correlation coefficients with the subjective MCD were -0.549 for MCW alone, 0.609 for the MCD by the features without MCW, and 0.617 for the MCD by the features and MCW. The correlation coefficients with the BMD were 0.619, -0.608, and -0.670, respectively. The areas under the receiver operating characteristic curves for detecting osteoporotic cases were 0.830, 0.884, and 0.901, respectively, whereas those for detecting high-risk cases were 0.835, 0.833, and 0.880, respectively. CONCLUSIONS: In conclusion, our scheme may have a potential to identify asymptomatic osteoporotic and osteopenic patients through dental examinations.
PURPOSE: Studies reported that the mandibular cortical width (MCW) measured on dental panoramic radiographs (DPRs) was significantly correlated with bone mineral density. However, MCW is not a perfect index by itself, and studies suggest the added utility of mandibular cortical index (MCI). In this study, we propose a method for computerized estimation of mandibular cortical degree (MCD), a new continuous measure of MCI, for osteoporotic risk assessment. METHODS: The mandibular contour was automatically segmented using an active contour model. The regions of interest near mental foramen were extracted for MCW and MCD determination. The MCW was measured on the basis of residue-line detection results and pixel profiles. Image features including texture features based on gray-level co-occurrence matrices were determined. The MCD were estimated using support vector regression (SVR). The SVR was trained using previously collected 99 DPRs, including 26 osteoporotic cases, by a computed radiography system. The proposed scheme was tested using 99 DPRs obtained by a photon-counting system with data of bone mineral density at distal forearm. The number of osteoporotic, osteopenic, and control cases were 12, 18, and 69 cases, respectively. The subjective MCD by a dental radiologist was employed for training and evaluation. RESULTS: The correlation coefficients with the subjective MCD were -0.549 for MCW alone, 0.609 for the MCD by the features without MCW, and 0.617 for the MCD by the features and MCW. The correlation coefficients with the BMD were 0.619, -0.608, and -0.670, respectively. The areas under the receiver operating characteristic curves for detecting osteoporotic cases were 0.830, 0.884, and 0.901, respectively, whereas those for detecting high-risk cases were 0.835, 0.833, and 0.880, respectively. CONCLUSIONS: In conclusion, our scheme may have a potential to identify asymptomatic osteoporotic and osteopenicpatients through dental examinations.
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