Keisuke Uemura1,2, Yoshito Otake3, Masaki Takao4, Hiroki Makino3, Mazen Soufi3, Makoto Iwasa5, Nobuhiko Sugano5, Yoshinobu Sato3. 1. Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan. surmountjp@gmail.com. 2. Department of Orthopaedic Medical Engineering, Osaka University Graduate School of Medicine, Suita, Osaka, Japan. surmountjp@gmail.com. 3. Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan. 4. Department of Orthopaedics, Osaka University Graduate School of Medicine, Suita, Osaka, Japan. 5. Department of Orthopaedic Medical Engineering, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Abstract
Commercial software is generally needed to measure the areal bone mineral density (aBMD) of the proximal femur from clinical computed tomography (CT) images. This study developed and verified an open-source reproducible system to quantify CT-aBMD to screen osteoporosis using clinical CT images. PURPOSE: For existing CT images acquired for various reasons other than osteoporosis, it might be beneficial to estimate areal BMD as assessed by dual-energy X-ray absorptiometry (DXA-based BMD) to ascertain the bone status based on DXA. In this study, we aimed to (1) develop an open-source reproducible measurement system to quantify DXA-based BMD from CT images and (2) validate its accuracy. METHODS: This study analyzed 75 pairs of hip CT and DXA images of women that were acquired for the preoperative assessment of total hip arthroplasty. From the CT images, the femur and a calibration phantom were automatically segmented using pre-trained codes/models available at https://github.com/keisuke-uemura . The proximal femoral region was isolated by manually selected landmarks and was projected onto the coronal plane to measure the areal density (CT-aHU). The calibration phantom was employed to convert the CT-aHU into CT-aBMD. Each parameter was correlated with DXA-based BMD, and the residual errors of CT images to estimate the T-scores in DXA were calculated using the standard error of estimate (SEE). RESULTS: The correlation coefficients of DXA-based BMD with CT-aHU and CT-aBMD were 0.947 and 0.950, respectively (both p < 0.001). The SEE for quantifying the T-scores in DXA were 0.51 and 0.50 for CT-aHU and CT-aBMD, respectively. CONCLUSION: With the method developed herein, CT permits estimation of the DXA-based BMD of the proximal femur within the standard DXA total hip region of interest with an SEE of 0.5 in T-scores. The radiation dose for CT acquisition needs consideration; therefore, our data do not provide a rationale for performing CT for screening osteoporosis. However, on CT images already acquired for clinical indications other than osteoporosis, researchers may use this open-source system to investigate osteoporosis status through the estimated DXA-based BMD of the proximal femur.
Commercial software is generally needed to measure the areal bone mineral density (aBMD) of the proximal femur from clinical computed tomography (CT) images. This study developed and verified an open-source reproducible system to quantify CT-aBMD to screen osteoporosis using clinical CT images. PURPOSE: For existing CT images acquired for various reasons other than osteoporosis, it might be beneficial to estimate areal BMD as assessed by dual-energy X-ray absorptiometry (DXA-based BMD) to ascertain the bone status based on DXA. In this study, we aimed to (1) develop an open-source reproducible measurement system to quantify DXA-based BMD from CT images and (2) validate its accuracy. METHODS: This study analyzed 75 pairs of hip CT and DXA images of women that were acquired for the preoperative assessment of total hip arthroplasty. From the CT images, the femur and a calibration phantom were automatically segmented using pre-trained codes/models available at https://github.com/keisuke-uemura . The proximal femoral region was isolated by manually selected landmarks and was projected onto the coronal plane to measure the areal density (CT-aHU). The calibration phantom was employed to convert the CT-aHU into CT-aBMD. Each parameter was correlated with DXA-based BMD, and the residual errors of CT images to estimate the T-scores in DXA were calculated using the standard error of estimate (SEE). RESULTS: The correlation coefficients of DXA-based BMD with CT-aHU and CT-aBMD were 0.947 and 0.950, respectively (both p < 0.001). The SEE for quantifying the T-scores in DXA were 0.51 and 0.50 for CT-aHU and CT-aBMD, respectively. CONCLUSION: With the method developed herein, CT permits estimation of the DXA-based BMD of the proximal femur within the standard DXA total hip region of interest with an SEE of 0.5 in T-scores. The radiation dose for CT acquisition needs consideration; therefore, our data do not provide a rationale for performing CT for screening osteoporosis. However, on CT images already acquired for clinical indications other than osteoporosis, researchers may use this open-source system to investigate osteoporosis status through the estimated DXA-based BMD of the proximal femur.
Authors: Pauline M Camacho; Steven M Petak; Neil Binkley; Dima L Diab; Leslie S Eldeiry; Azeez Farooki; Steven T Harris; Daniel L Hurley; Jennifer Kelly; E Michael Lewiecki; Rachel Pessah-Pollack; Michael McClung; Sunil J Wimalawansa; Nelson B Watts Journal: Endocr Pract Date: 2020-05 Impact factor: 3.443
Authors: Nicholas K Weber; Jeff L Fidler; Tony M Keaveny; Bart L Clarke; Sundeep Khosla; Joel G Fletcher; David C Lee; Darrell S Pardi; Edward V Loftus; Sunanda V Kane; John M Barlow; Naveen S Murthy; Brenda D Becker; David H Bruining Journal: Am J Gastroenterol Date: 2014-01-21 Impact factor: 10.864
Authors: Jeff L Fidler; Naveen S Murthy; Sundeep Khosla; Bart L Clarke; David H Bruining; David L Kopperdahl; David C Lee; Tony M Keaveny Journal: Radiology Date: 2015-07-22 Impact factor: 11.105
Authors: B C C Khoo; K Brown; C Cann; K Zhu; S Henzell; V Low; S Gustafsson; R I Price; R L Prince Journal: Osteoporos Int Date: 2008-12-24 Impact factor: 4.507