Comparison of bone age assessment methods using a hand radiography in patients with active growth plate and anteromedial knee instability

Abstract

Background Bone age is essential for pediatric patients with active growth zones and anteromedial instability to facilitate optimal treatment strategy and minimize postoperative complications. However, many people are unaware of various tools for determining bone age, including classical methods and modern machine learning techniques. The objective was to show and compare different methods for calculating bone age and determining surgical strategy for patients with anteromedial instability of the knee joint. Material and methods All-Inside anterior cruciate ligament reconstruction was performed for 20 patients. Wrist radiographs were performed for bone age assessment using the "point scoring system" of Tanner and Whitehouse and the "atlas matching" method of Greulich and Pyle. Machine learning programs were used in addition to standard bone age assessments. Results The findings showed an average difference of 21 months (80 %) in a group of 20 individuals with bone age ahead of the passport age and an average difference of 18 months (20 %) in patients with retarded bone age. Discussion The findings showed the difference between chronological and bone age and could be encountered in scientific articles on endocrinology and pediatrics. No scientific studies on the use of the methods could be found in the specialty “trauma and orthopaedics”. Conclusion Bone age assessment, prediction of children's target height are essential for surgical treatment of patients with open growth plates.

Keywords

• bone age
• children
• all-inside
• acl reconstruction
• active growth plate
• artificial intelligence