H Jeong1, J Kim, T Ishida, M Akiyama, Y Kim. 1. Department of Radiological Science, Baekseok Culture University, Chungchungnam-do, Republic of Korea.
Abstract
OBJECTIVE: To evaluate the geometric change of osteoporotic bone trabecular patterns using root mean square (RMS) values, first moment power spectrum (FMP) values and fractal dimension values. With the use of these methods, we attempted computerised analysis of osteoporotic bone patterns using texture parameters characterising bone architecture and computer-aided diagnosis of osteoporosis. METHODS: 32 patient cases from Korea University Guro Hospital were analysed. Patient ages ranged from 51 to 89 years, with a mean age of 65 years. Receiver operating characteristic curve analysis was performed with determination of the area under the curve (AUC). RESULTS: The bone mineral density (BMD) measurement (AUC=0.78) was a better indicator of bone quantity than the RMS, FMP and fractal dimension values (AUC=0.72) for diagnosis; therefore the combination of RMS, FMP and fractal dimension values was a better indicator of bone quality. CONCLUSION: Measurements that combined BMD measurement and RMS values and combined FMP and fractal dimension values (AUC=0.85) together produced better results than the use of the two parameter sets separately for a diagnosis of osteoporosis. ADVANCES IN KNOWLEDGE: For more effective application, additional study on more cases and data will be required.
OBJECTIVE: To evaluate the geometric change of osteoporotic bone trabecular patterns using root mean square (RMS) values, first moment power spectrum (FMP) values and fractal dimension values. With the use of these methods, we attempted computerised analysis of osteoporotic bone patterns using texture parameters characterising bone architecture and computer-aided diagnosis of osteoporosis. METHODS: 32 patient cases from Korea University Guro Hospital were analysed. Patient ages ranged from 51 to 89 years, with a mean age of 65 years. Receiver operating characteristic curve analysis was performed with determination of the area under the curve (AUC). RESULTS: The bone mineral density (BMD) measurement (AUC=0.78) was a better indicator of bone quantity than the RMS, FMP and fractal dimension values (AUC=0.72) for diagnosis; therefore the combination of RMS, FMP and fractal dimension values was a better indicator of bone quality. CONCLUSION: Measurements that combined BMD measurement and RMS values and combined FMP and fractal dimension values (AUC=0.85) together produced better results than the use of the two parameter sets separately for a diagnosis of osteoporosis. ADVANCES IN KNOWLEDGE: For more effective application, additional study on more cases and data will be required.
Authors: Muthu Rama Krishnan Mookiah; Thomas Baum; Kai Mei; Felix K Kopp; Georg Kaissis; Peter Foehr; Peter B Noel; Jan S Kirschke; Karupppasamy Subburaj Journal: J Bone Miner Metab Date: 2017-04-07 Impact factor: 2.626