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

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초록

Purpose: To evaluate the applicability of Greulich-Pyle (GP) standards to bone age (BA) assessment in healthy Korean childrenusing 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 and2017. Based on GP method, BA was assessed manually by two radiologists and automatically by two deep learning-based BA as sessment (DLBAA), which estimated GP-assigned (original model) and optimal (modified model) BAs. Estimated BA was com pared 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 wascalculated. Results: CA and all estimated BA showed excellent agreement (ICC ≥0.978, p<0.001) and significant positive linear correlations (R2≥0.935, p<0.001). The estimated BA of all methods showed systematic bias and tended to be lower than CA in younger patients, andhigher than CA in older patients (regression slopes ≤-0.11, p<0.001). The mean absolute error of radiologist 1, radiologist 2, origi nal, and modified DLBAA models were 13.09, 13.12, 11.52, and 11.31 months, respectively. The difference between estimatedBA and CA was >12 months in 44.3%, 44.5%, 39.2%, and 36.1% for radiologist 1, radiologist 2, original, and modified DLBAAmodels, respectively. Conclusion: Contemporary healthy Korean children showed different rates of skeletal development than GP standard-BA, andsystemic bias should be considered when determining children’s skeletal maturation.

Abstract

Purpose: To evaluate the applicability of Greulich-Pyle (GP) standards to bone age (BA) assessment in healthy Korean childrenusing 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 and2017. Based on GP method, BA was assessed manually by two radiologists and automatically by two deep learning-based BA as sessment (DLBAA), which estimated GP-assigned (original model) and optimal (modified model) BAs. Estimated BA was com pared 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 wascalculated. Results: CA and all estimated BA showed excellent agreement (ICC ≥0.978, p<0.001) and significant positive linear correlations (R2≥0.935, p<0.001). The estimated BA of all methods showed systematic bias and tended to be lower than CA in younger patients, andhigher than CA in older patients (regression slopes ≤-0.11, p<0.001). The mean absolute error of radiologist 1, radiologist 2, origi nal, and modified DLBAA models were 13.09, 13.12, 11.52, and 11.31 months, respectively. The difference between estimatedBA and CA was >12 months in 44.3%, 44.5%, 39.2%, and 36.1% for radiologist 1, radiologist 2, original, and modified DLBAAmodels, respectively. Conclusion: Contemporary healthy Korean children showed different rates of skeletal development than GP standard-BA, andsystemic bias should be considered when determining children’s skeletal maturation.

참고문헌 (21)

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관련 논문AI추천

Clinical validation of a deep-learning-based bone age software in healthy Korean childrenHong Suk-Joo, Lea Winnah Wu-In, Lee Kee-Hyoung, Nam Hyo-Kyoung, Noh Eunjin, Rhie Young-Jun, Yang Zepa대한소아내분비학회 · Annals of Pediatric Endocrinology & Metabolism2024 · 제29권 제2호Bone Age Estimation and Prediction of Final Adult Height Using Deep Learning권아름, 김수진, 김호성, 박소영, 서정환, 송경철, 오준석, 이명섭, 이해인, 정모경, 채현욱, 최영하, 최한샘, 허진경연세대학교의과대학 · Yonsei Medical Journal2023 · 제64권 제11호골연령 측정시 Greulich-Pyle 방법과Tanner-Whitehouse (TW3) 방법의 비교김수영, 신정연, 오연정, 이기형, 이영준대한소아내분비학회 · Annals of Pediatric Endocrinology & Metabolism2008 · 제13권 제1호골연령 검사를 시행한 환자들의 임상적 특성과 골연령 측정 방법 간의 상관성에 대한 후향적 연구김은진, 민상연, 최지우대한한방소아과학회 · 대한한방소아과학회지2023 · 제37권 제3호골 성숙도 단계의 골령 평가를 위한 Greulich-Pyle 방법을 이용한 인공지능 프로그램의 활용김지훈, 남옥형, 박소영, 서혜준, 신종현, 이은경, 정태성, 최성철대한소아치과학회 · 대한소아치과학회지2023 · 제50권 제1호성장을 주소로 한방병원에 내원한 환아의 한의치료 효과: Deep Learning 기반 골연령 판독 프로그램을 활용한 증례보고이보람, 한예지대한한방소아과학회 · 대한한방소아과학회지2023 · 제37권 제2호

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