Journal of the Korean Society of Radiology (대한영상의학회지)

The Korean Society of Radiology (대한영상의학회)
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Comparison of Bone Ages in Early Puberty: Computerized Greulich-Pyle Based Bone Age vs. Sauvegrain Method

초기 사춘기의 골연령 비교: 전산화된 Greulich-Pyle 기반 골연령 대비 Sauvegrain 방법

  • Sang Young Lee (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Soo Ah Im (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
  • 이상영 (가톨릭대학교 의과대학 서울성모병원 영상의학과) ;
  • 임수아 (가톨릭대학교 의과대학 서울성모병원 영상의학과)
  • Received : 2021.07.13
  • Accepted : 2021.11.22
  • Published : 2022.09.01
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Abstract

Purpose To compare the computerized Greulich-Pyle based bone age with elbow bone age. Materials and Methods A total of 2126 patients (1525 girls; 601 boys) whose elbow bone age was within the evaluable range by the Sauvegrain method, and who simultaneously underwent hand radiography, were enrolled in the study. The 1st-bone age and VUNO score of the hand were evaluated using VUNOMed-BoneAge software. The correlation between the hand and elbow bone age was analyzed according to the child's gender and the probability of 1st-bone age. Results The correlation between VUNO score and elbow bone age (r = 0.898) was higher than the correlation between 1st-bone age and elbow bone age (r = 0.879). Moreover, the VUNO score showed a better correlation with the elbow bone age in patients with a 1st-bone age probability of less than 70%, or in girls. Elbow bone age was more advanced compared to hand bone age, and this difference increased until the middle of puberty and gradually decreased in the latter half. Conclusion The computerized Greulich-Pyle based hand bone age showed a significant correlation with the elbow bone age at puberty. However, since the elbow bone age tends to advance faster than the hand bone age, caution is required while judging the bone age during puberty.

목적 Greulich-Pyle 기반 전산화된 손 골연령과 팔꿈치 골연령을 비교하고자 하였다. 대상과 방법 팔꿈치 골연령이 Sauvegrain 방법에 의해 평가 가능한 범위 내에 있고, 동시에 손 X선 사진을 촬영한 2126명의 환자(여아 1525명, 남아 601명)를 대상으로 하였다. VUNOMedBoneAge 소프트웨어를 이용하여 손의 1순위 골연령과 VUNO 점수를 얻었으며, 아동의 성별과 1순위 골연령 확률에 따라 손 골연령과 팔꿈치 골연령의 상관관계를 분석하였다. 결과 VUNO 점수와 팔꿈치 골연령의 상관관계(r = 0.898)가 1순위 골연령과 팔꿈치 골연령의 상관관계(r = 0.879)보다 높았다. 1순위 골연령 확률이 70% 미만이거나 여아인 경우, VUNO 점수를 사용하면 팔꿈치 골연령과 더 좋은 상관관계를 보였다. 팔꿈치 골연령은 손 골연령보다 진행된 경향을 보였으며 그 차이는 사춘기 중반까지 증가하다가 후반에 점차 감소하였다. 결론 사춘기 시기의 Greulich-Pyle 기반 전산화된 손 골연령은 팔꿈치 골연령과 유의한 상관관계를 보였다. 다만 팔꿈치 골연령은 손 골연령보다 빠른 경향이 있어 사춘기의 골연령 판단에 있어 주의가 필요하겠다.

Keywords

References

  1. Martin DD, Wit JM, Hochberg Z, Savendahl L, van Rijn RR, Fricke O, et al. The use of bone age in clinical practice - part 1. Horm Res Paediatr 2011;76:1-9 
  2. Greulich WW, Pyle SI. Radiographic atlas of skeletal development of the hand and wrist. 2nd ed. Paloalto: Stanford University Press 1959 
  3. Pose Lepe G, Villacres F, Silva Fuente-Alba C, Guiloff S. Correlation in radiological bone age determination using the Greulich and Pyle method versus automated evaluation using BoneXpert software. Rev Chil Pediatr 2018;89:606-611 
  4. Tanner JM, Healy MJR, Goldstein H, Cameron M. Assessment of skeletal maturity and prediction of adult height (TW3) method. 3rd ed. Philadelphia: Saunders 2001 
  5. Kim DH. Assessment of bone age during pubertal age. J Korean Soc Pediatr Endocrinol 2011;16:135-138 
  6. Eitel KB, Eugster EA. Differences in bone age readings between pediatric endocrinologists and radiologists. Endocr Pract 2020;26:328-331 
  7. Canavese F, Charles YP, Dimeglio A. Skeletal age assessment from elbow radiographs. Review of the literature. Chir Organi Mov 2008;92:1-6 
  8. Kim JR, Shim WH, Yoon HM, Hong SH, Lee JS, Cho YA, et al. Computerized bone age estimation using deep learning based program: evaluation of the accuracy and efficiency. AJR Am J Roentgenol 2017;209:1374-1380 
  9. Dimeglio A, Charles YP, Daures JP, de Rosa V, Kabore B. Accuracy of the Sauvegrain method in determining skeletal age during puberty. J Bone Joint Surg Am 2005;87:1689-1696 
  10. Martin DD, Sato K, Sato M, Thodberg HH, Tanaka T. Validation of a new method for automated determination of bone age in Japanese children. Horm Res Paediatr 2010;73:398-404 
  11. Zhang SY, Liu G, Ma CG, Han YS, Shen XZ, Xu RL, et al. Automated determination of bone age in a modern Chinese population. ISRN Radiol 2013;2013:874570 
  12. Martin DD, Meister K, Schweizer R, Ranke MB, Thodberg HH, Binder G. Validation of automatic bone age rating in children with precocious and early puberty. J Pediatr Endocrinol Metab 2011;24:1009-1014 
  13. Pan I, Baird GL, Mutasa S, Merck D, Ruzal-Shapiro C, Swenson DW, et al. Rethinking Greulich and Pyle: a deep learning approach to pediatric bone age assessment using pediatric trauma hand radiographs. Radiol Artif Intell 2020;2:e190198 
  14. Thodberg HH, Kreiborg S, Juul A, Pedersen KD. The BoneXpert method for automated determination of skeletal maturity. IEEE Trans Med Imaging 2009;28:52-66