(주) 뷰노

Yonsei Med J.

Re-Assessment of Applicability of Greulich and Pyle-Based Bone Age to Korean Children Using Manual and Deep Learning-Based Automated Method

  • Jun. 2022

Abstract

Purpose

To evaluate the applicability of Greulich-Pyle (GP) standards to bone age (BA) assessment in healthy Korean children using manual and deep learning-based methods.

Materials and Methods

We collected 485 hand radiographs of healthy children aged 2–17 years (262 boys) between 2008 and 2017. Based on GP method, BA was assessed manually by two radiologists and automatically by two deep learning-based BA assessment (DLBAA), which estimated GP-assigned (original model) and optimal (modified model) BAs. Estimated BA was compared to chronological age (CA) using intraclass correlation (ICC), Bland-Altman analysis, linear regression, mean absolute error, and root mean square error. The proportion of children showing a difference >12 months between the estimated BA and CA was calculated.

Results

CA and all estimated BA showed excellent agreement (ICC ≥0.978, p<0>2≥0.935, p<0>p<0>12 months in 44.3%, 44.5%, 39.2%, and 36.1% for radiologist 1, radiologist 2, original, and modified DLBAA models, respectively.

Conclusion

Contemporary healthy Korean children showed different rates of skeletal development than GP standard-BA, and systemic bias should be considered when determining children’s skeletal maturation.

Keywords

Age determination by skeleton; radiography; hand bones; child; deep learning

Author

Jisun Hwang 1, Hee Mang Yoon 2, Jae-Yeon Hwang 3, Pyeong Hwa Kim 4, Boram Bak 5, Byeong Uk Bae 6, Jinkyeong Sung 6, Hwa Jung Kim 7, Ah Young Jung 4, Young Ah Cho 4, Jin Seong Lee

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#medical_image

#VUNO Med®-BoneAge™