Performance of the Diagnostic Value of Bone Age Assessment Software Based on Deep Learning in Chinese Children

NCT05137301 | Unknown

• 1 other identifier: GenSci-GD-21001
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

High accuracy and precision bone age assessment is very important for the diagnosis and treatment monitoring of various pediatric diseases. The commonly used bone age assessment methods include GP atlas, TW3 score and Zhonghua 05. GP method is to compare wrist X-ray films with atlas reference X-ray films. Its main disadvantages are strong subjectivity and long atlas standard interval. Different from GP method, TW3 method is to grade and score each bone, add each epiphyseal score to calculate the total score of bone maturity, and obtain the corresponding final bone age value. Although TW3 scoring method is relatively accurate, it is complex and time-consuming, and there is great variability among evaluators. In order to evaluate bone age more efficiently and accurately, a method based on computer image automatic recognition technology can help to overcome these problems. In this study, 1000 children aged 1-18 in 5 hospitals are selected as the research objects. After taking bone age films with bone age instrument, the film reading results and evaluation time of AI Group, artificial group and standard group are recorded. One month later, the artificial group re-analyzes 1000 films with the assistance of AI system, and the evaluation time is recorded. Finally, the accuracy and time difference of artificial group, AI Group, artificial combined AI Group and standard group are compared. The purpose of this study is to use the most advanced artificial intelligence deep learning bone age evaluation software to explore the value of bone age instrument to improve the accuracy and diagnostic efficiency of bone age evaluation by pediatricians.

Conditions

Endocrine Diseases

Keywords

bone age; TW3; AI

Outcome Measures

Primary Outcomes (1)

• bone age

  The mean absolute error (MAE) and root mean square error (RSME) between the evaluation bone age results of different groups

  one month

Interventions

X-ray bone age instrument DEVICE

Bone age films were taken by X-ray bone age instrument

Eligibility Criteria

• Age: 1 Year - 18 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64)
• Sampling Method: Probability Sample

Study Population

Children aged 1-18 who need bone age assessment

You may qualify if:

• Children aged 1 to 18 years.
• Clinical diagnosis of requiring bone age examination.

You may not qualify if:

• There are obstructions or implants in the wrist bone, such as metal.
• Poor resolution, which affects the observation of bone characteristics.
• Poor shooting position of the wrist due to various reasons.

Sponsors & Collaborators

• Tongji Hospital: lead
• Changchun GeneScience Pharmaceutical Co., Ltd.: collaborator

Study Sites (1)

Tongji Hospital Tongji Medical College of Hust

Wuhan, Hubei, China

RECRUITING

MeSH Terms

Conditions

Endocrine System Diseases

Study Officials

• xiumin wang, director

  Shanghai Children's Medical Center

  PRINCIPAL INVESTIGATOR

• xinran cheng, director

  Chendu Women's and children's central hospital

  PRINCIPAL INVESTIGATOR

• xiaobo chen, director

  Children's Hospital of The Capital Institute of Pediatrics

  PRINCIPAL INVESTIGATOR

• ZE SU, director

  Shenzhen Children's Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Xiaoping Luo, director

CONTACT

13387522645; xpluo@tjh.tjmu.edu.cn

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Month
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director of Pediatrics

Study Record Dates

• First Submitted: November 11, 2021
• First Posted: November 30, 2021
• Study Start: February 21, 2022
• Primary Completion: December 31, 2024
• Study Completion: December 31, 2024
• Last Updated: April 20, 2023

Record last verified: 2023-04

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)