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High performance for bone age estimation with an artificial intelligence solution.

Toan Nguyen1, Anne-Laure Hermann2, Jeanne Ventre3

  • 1Department of Pediatric Radiology, Hôpital Armand Trousseau AP-HP, 75012 Paris, France; Gleamer, 75010 Paris, France.

Diagnostic and Interventional Imaging
|April 24, 2023
PubMed
Summary
This summary is machine-generated.

An artificial intelligence (AI) solution demonstrated superior accuracy in bone age assessment compared to a general radiologist. The AI achieved a lower mean absolute error (MAE) in estimating Greulich and Pyle bone age for both boys and girls.

Keywords:
Artificial intelligenceBone ageGreulich and PyleHand radiographPediatrics

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Area of Science:

  • Radiology
  • Artificial Intelligence
  • Pediatric Imaging

Background:

  • Bone age assessment is crucial for evaluating growth and development in children.
  • Traditional methods rely on expert interpretation of hand radiographs.
  • Variability in interpretation can affect clinical decision-making.

Purpose of the Study:

  • To compare the performance of an artificial intelligence (AI) solution against a senior general radiologist for bone age assessment.
  • To evaluate the accuracy of AI in estimating Greulich and Pyle bone age.

Main Methods:

  • Retrospective collection of anteroposterior hand radiographs from 206 patients (5-17 years old).
  • Greulich and Pyle bone age estimation by two independent pediatric radiologists (reference standard).
  • Bone age determination by a senior general radiologist and an AI solution, with chronological age and sex provided.

Main Results:

  • The AI algorithm showed a significantly lower mean absolute error (MAE) than the general radiologist for both sexes (P < 0.007).
  • In boys, AI MAE was 0.488 years vs. 0.771 years for the reader.
  • In girls, AI MAE was 0.494 years vs. 0.673 years for the reader.

Conclusions:

  • The AI solution provides a more accurate estimation of Greulich and Pyle bone age compared to a general radiologist.
  • AI demonstrates potential to improve the consistency and accuracy of bone age assessment in clinical practice.