Literature DB >> 27173981

Bone age assessment practices in infants and older children among Society for Pediatric Radiology members.

Micheál A Breen1, Andy Tsai2, Aymeric Stamm2, Paul K Kleinman2.   

Abstract

BACKGROUND: Numerous bone age estimation techniques exist, but little is known about what methods radiologists use in clinical practice.
OBJECTIVE: To determine which methods pediatric radiologists use to assess bone age in children, and their confidence in these methods.
MATERIALS AND METHODS: Society for Pediatric Radiology (SPR) members were invited to complete an online survey regarding bone age assessment. Respondents were asked to identify the methods used and their confidence with their technique for the following groups: Infants (<1 year old), 1- to 3-year-olds and 3- to 18-year-olds.
RESULTS: Of the 937 SPR members invited, 441 responded (47%). For infants, 70% of respondents use the hand/wrist method of Greulich and Pyle, 27% use a hemiskeleton method (e.g., Sontag or Elgenmark), and 14.4% use the knee method of Pyle and Hoerr. Of these respondents, 34% were not confident with their technique. For 1- to 3-year-olds, 86% used Greulich and Pyle, and 19% used a hemiskeleton method; 21% were not confident with their technique in this age group. For 3- to 18-year-olds, 97% used Greulich and Pyle, and only 6% of respondents were not confident with their technique in this category. A logistic regression analysis demonstrated that the chronological age of the patient had the greatest impact on reader confidence, with the odds ratios for confidence being 4 times greater in the 3- to 18-year-olds category compared to the younger groups.
CONCLUSION: For children older than 3 years, the majority of pediatric radiologists are very confident in their use of Greulich and Pyle for bone age assessment. However a variety of methodologies are used when assessing bone age in infants and younger children, and pediatric radiologists are less confident assessing bone age in these children. This survey highlights the need for a consensus protocol on bone age assessment of younger children and infants that provides readers with a higher degree of confidence.

Entities:  

Keywords:  Bone age; Children; Greulich and Pyle; Musculoskeletal; Radiography; Skeletal maturity

Mesh:

Year:  2016        PMID: 27173981     DOI: 10.1007/s00247-016-3618-7

Source DB:  PubMed          Journal:  Pediatr Radiol        ISSN: 0301-0449


  4 in total

1.  Response rates to mail surveys published in medical journals.

Authors:  D A Asch; M K Jedrziewski; N A Christakis
Journal:  J Clin Epidemiol       Date:  1997-10       Impact factor: 6.437

2.  Bone age assessment with conventional ultrasonography in healthy infants from 1 to 24 months of age.

Authors:  Monica Daneff; Claudia Casalis; Claudio H Bruno; Didier A Bruno
Journal:  Pediatr Radiol       Date:  2015-01-09

3.  [Reliability of the Sauvegrain and Nahum method to assess bone age in a contemporary population].

Authors:  K Chaumoître; N Colavolpe; Y Sayegh-Martin; N Pernoud; O Dutour; M Panuel
Journal:  J Radiol       Date:  2006-11

4.  Infant bone age estimation based on fibular shaft length: model development and clinical validation.

Authors:  Andy Tsai; Catherine Stamoulis; Sarah D Bixby; Micheál A Breen; Susan A Connolly; Paul K Kleinman
Journal:  Pediatr Radiol       Date:  2015-12-04
  4 in total
  7 in total

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Authors:  Simukayi Mutasa; Peter D Chang; Carrie Ruzal-Shapiro; Rama Ayyala
Journal:  J Digit Imaging       Date:  2018-08       Impact factor: 4.056

2.  Rethinking Greulich and Pyle: A Deep Learning Approach to Pediatric Bone Age Assessment Using Pediatric Trauma Hand Radiographs.

Authors:  Ian Pan; Grayson L Baird; Simukayi Mutasa; Derek Merck; Carrie Ruzal-Shapiro; David W Swenson; Rama S Ayyala
Journal:  Radiol Artif Intell       Date:  2020-07-29

3.  Intelligent Bone Age Assessment: An Automated System to Detect a Bone Growth Problem Using Convolutional Neural Networks with Attention Mechanism.

Authors:  Mohd Asyraf Zulkifley; Nur Ayuni Mohamed; Siti Raihanah Abdani; Nor Azwan Mohamed Kamari; Asraf Mohamed Moubark; Ahmad Asrul Ibrahim
Journal:  Diagnostics (Basel)       Date:  2021-04-24

4.  Dental and Skeletal Age Estimations in Lebanese Children: A Retrospective Cross-sectional Study.

Authors:  Antoine Saadé; Pascal Baron; Ziad Noujeim; Dany Azar
Journal:  J Int Soc Prev Community Dent       Date:  2017-05-22

5.  The Application of Magnetic Resonance Imaging in Skeletal Age Assessment.

Authors:  Khalaf Alshamrani
Journal:  Appl Bionics Biomech       Date:  2022-02-21       Impact factor: 1.781

6.  Alternative methods for skeletal maturity estimation with the EOS scanner-Experience from 934 patients.

Authors:  Ádám Tibor Schlégl; Ian O'Sullivan; Péter Varga; Péter Than; Csaba Vermes
Journal:  PLoS One       Date:  2022-05-06       Impact factor: 3.752

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

Authors:  Jisun Hwang; Hee Mang Yoon; Jae-Yeon Hwang; Pyeong Hwa Kim; Boram Bak; Byeong Uk Bae; Jinkyeong Sung; Hwa Jung Kim; Ah Young Jung; Young Ah Cho; Jin Seong Lee
Journal:  Yonsei Med J       Date:  2022-07       Impact factor: 3.052

  7 in total

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