Fengdan Wang1, Wangjiu Cidan2, Xiao Gu3, Shi Chen3, Wu Yin2, Yongliang Liu4, Lei Shi4, Hui Pan3, Zhengyu Jin1. 1. Department of Radiology, Peking Union Medical College Hospital, Beijing, China. 2. Department of Radiology, Tibet Autonomous Region People's Hospital, Lhasa, China. 3. Department of Endocrinology, Peking Union Medical College Hospital, Beijing, China. 4. Hangzhou YITU Healthcare Technology Co., Ltd, Hangzhou, China.
Abstract
OBJECTIVE: To investigate whether bone age (BA) of children living in Tibet Highland could be accurately assessed using a fully automated artificial intelligence (AI) system. METHODS：: Left hand radiographs of 385 children (300 Tibetan and 85 immigrant Han) aged 4-18 years who presented to the largest medical center of Tibet between September 2013 and November 2019 were consecutively collected. From these radiographs, BA was determined using the Greulich and Pyle (GP) method by experts in a consensus manner; furthermore, BA was estimated by a previously reported artificial intelligence (AI) BA system based on Han children from southern China. The performance of the AI system was compared with that of experts by using statistical analysis. RESULTS: Compared with the experts' results, the accuracy of the AI system for Tibetan and Han children within 1 year was 84.67 and 89.41%, respectively, and its mean absolute difference (MAD) was 0.65 and 0.56 years, respectively. The discrepancy in hand-wrist bone maturation was the main cause of low accuracy of the system in the 4- to 6-year-old group. CONCLUSION: The AI BA system developed for Han Chinese children living in flat regions could enable to assess BA accurately in Tibet where medical resources are limited. ADVANCES IN KNOWLEDGE: AI-based BA system may serve as an effective and efficient solution to assess BA in Tibet.
OBJECTIVE: To investigate whether bone age (BA) of children living in Tibet Highland could be accurately assessed using a fully automated artificial intelligence (AI) system. METHODS：: Left hand radiographs of 385 children (300 Tibetan and 85 immigrant Han) aged 4-18 years who presented to the largest medical center of Tibet between September 2013 and November 2019 were consecutively collected. From these radiographs, BA was determined using the Greulich and Pyle (GP) method by experts in a consensus manner; furthermore, BA was estimated by a previously reported artificial intelligence (AI) BA system based on Han children from southern China. The performance of the AI system was compared with that of experts by using statistical analysis. RESULTS: Compared with the experts' results, the accuracy of the AI system for Tibetan and Han children within 1 year was 84.67 and 89.41%, respectively, and its mean absolute difference (MAD) was 0.65 and 0.56 years, respectively. The discrepancy in hand-wrist bone maturation was the main cause of low accuracy of the system in the 4- to 6-year-old group. CONCLUSION: The AI BA system developed for Han Chinese children living in flat regions could enable to assess BA accurately in Tibet where medical resources are limited. ADVANCES IN KNOWLEDGE: AI-based BA system may serve as an effective and efficient solution to assess BA in Tibet.
Authors: Shahein H Tajmir; Hyunkwang Lee; Randheer Shailam; Heather I Gale; Jie C Nguyen; Sjirk J Westra; Ruth Lim; Sehyo Yune; Michael S Gee; Synho Do Journal: Skeletal Radiol Date: 2018-08-01 Impact factor: 2.199
Authors: Xue-Lian Zhou; Er-Gang Wang; Qiang Lin; Guan-Ping Dong; Wei Wu; Ke Huang; Can Lai; Gang Yu; Hai-Chun Zhou; Xiao-Hui Ma; Xuan Jia; Lei Shi; Yong-Sheng Zheng; Lan-Xuan Liu; Da Ha; Hao Ni; Jun Yang; Jun-Fen Fu Journal: Quant Imaging Med Surg Date: 2020-03
Authors: Safwan S Halabi; Luciano M Prevedello; Jayashree Kalpathy-Cramer; Artem B Mamonov; Alexander Bilbily; Mark Cicero; Ian Pan; Lucas Araújo Pereira; Rafael Teixeira Sousa; Nitamar Abdala; Felipe Campos Kitamura; Hans H Thodberg; Leon Chen; George Shih; Katherine Andriole; Marc D Kohli; Bradley J Erickson; Adam E Flanders Journal: Radiology Date: 2018-11-27 Impact factor: 29.146