Analysis of the current situation and development trend of bone age assessment of children in China based on questionnaires
10.3760/cma.j.cn112149-20231009-00268
- VernacularTitle:基于调查问卷分析国内儿童骨龄评估现状及发展趋势
- Author:
Fengsen BAI
1
;
Xinyu YUAN
;
Yimin MA
;
Yang YANG
;
Yuchun YAN
;
Haiyan XIN
;
Xiaoguang CHENG
Author Information
1. 首都儿科研究所附属儿童医院放射科，北京 100020
- Keywords:
Child;
Bone age;
Artificial intelligence;
X-ray
- From:
Chinese Journal of Radiology
2024;58(2):225-228
- CountryChina
- Language:Chinese
-
Abstract:
Objective:Based on the questionnaire, to analyze the current status of children′s bone age assessment in China, especially the application of artificial intelligence (AI)-assisted bone age assessment system in the clinic.Methods:This was a cross-sectional study. The questionnaire was adapted by ourselves through the literature method and expert interview method, and the whole volume included 22 questions, which were released in the form of WeChat applet questionnaire star to the physician groups of several associations and entrusted to the radiology and paediatricians with senior titles. The results of the different types of questions were summarised and analyzed, and the chi-square test was used to compare the count data.Results:A total of 450 valid questionnaires were collected from 162 medical institutions in 26 provinces and cities and autonomous regions, of which 232 (51.6%) were from 87 (53.7%) tertiary hospitals and 218 (48.4%) from 75 (46.3%) secondary hospitals. Of the respondents, 115 (25.6%) were senior, 137 (30.4%) middle and 198 (44.0%) junior. Child bone age measurement was performed at 75.9% (66/87) of tertiary care organizations and 26.7% (20/75) of secondary care organizations, and the difference was statistically significant ( χ2=39.10, P<0.001). Left wrist radiographs were predominantly used for bone age assessment (76.0%, 123/162), with 72.8% (118/162) of sites using the ATLAS method of assessment and 17.9% (29/162) using the scoring method. A total of 98.4% (443/450) of respondents agreed that AI technology should be used to assist in bone age assessment, but only 9.3% (15/162) of healthcare organizations used AI-assisted technology. Conclusion:At present, bone age assessment is widely used in medical institutions, but there are problems with non-standardized examination methods, inconsistent assessment standards, and imprecise assessment results. Expectations for AI technology-assisted diagnosis exist among a wide range of physicians, but there are fewer users.
